NeurIPSW 2024
2666 papers
♠ SPADE ♠ Split Peak Attention DEcomposition
Malcolm Wolff, Kin G. Olivares, Boris N. Oreshkin, Sunny Ruan, Sitan Yang, Abhinav Katoch, Shankar Ramasubramanian, Youxin Zhang, Michael W. Mahoney, Dmitry Efimov, Vincent Quenneville-Belair $\mathbb{X}$-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs
Vlad Sobal, Mark Ibrahim, Randall Balestriero, Vivien Cabannes, Diane Bouchacourt, Pietro Astolfi, Kyunghyun Cho, Yann LeCun $\mu$LO: Compute-Efficient Meta-Generalization of Learned Optimizers
Benjamin Thérien, Charles-Étienne Joseph, Boris Knyazev, Edouard Oyallon, Irina Rish, Eugene Belilovsky $\texttt{pfl-Research}$: Simulation Framework for Accelerating Research in Private Federated Learning
Filip Granqvist, Congzheng Song, Áine Cahill, Rogier van Dalen, Martin Pelikan, Yi Sheng Chan, Xiaojun Feng, Natarajan Krishnaswami, Vojta J, Mona Chitnis 3D Audio-Visual Segmentation
Artem Sokolov, Swapnil Bhosale, Xiatian Zhu 3D Interaction Geometric Pre-Training for Molecular Relational Learning
Namkyeong Lee, Yunhak Oh, Heewoong Noh, Gyoung S. Na, Tianfan Fu, Chanyoung Park 3D-GRAND: A Million-Scale Dataset for 3D-LLMs with Better Grounding and Less Hallucination
Jianing Yang, Xuweiyi Chen, Nikhil Madaan, Madhavan Iyengar, Shengyi Qian, David Fouhey, Joyce Chai A Bayesian Approach Towards Crowdsourcing the Truths from LLMs
Peiran Yao, Jerin George Mathew, Shehraj Singh, Donatella Firmani, Denilson Barbosa A Benchmark for Long-Form Medical Question Answering
Pedram Hosseini, Jessica M. Sin, Bing Ren, Bryceton G. Thomas, Elnaz Nouri, Ali Farahanchi, Saeed Hassanpour A Black-Box Watermarking Modulation for Semantic Segmentation Models
Mohammed Lansari, Lucas Mattioli, Boussad Addad, Paul-Marie Raffi, Martin Gonzalez, Katarzyna Kapusta A Case Study in Plural Governance Design
Joel Miller, Christopher Kanich, Glen Weyl A Causal Perspective in Brainwave Foundation Models
Konstantinos Barmpas, Yannis Panagakis, Dimitrios Adamos, Nikolaos Laskaris, Stefanos Zafeiriou A Chemically-Guided Generative Diffusion Model for Materials Synthesis Planning
Elton Pan, Soonhyoung Kwon, Sulin Liu, Mingrou Xie, Yifei Duan, Thorben Prein, Killian Sheriff, Yuriy Roman, Manuel Moliner, Rafael Gomez-Bombarelli, Elsa Olivetti A Closer Look at System Message Robustness
Norman Mu, Jonathan Lu, Michael Lavery, David Wagner A Cognitive Framework for Learning Debiased and Interpretable Representations via Debiasing Global Workspace
Jinyung Hong, Eun Som Jeon, Changhoon Kim, Keun Hee Park, Utkarsh Nath, Yezhou Yang, Pavan K. Turaga, Theodore P. Pavlic A Concept-Based Explainability Framework for Large Multimodal Models
Jayneel Parekh, Pegah Khayatan, Mustafa Shukor, Alasdair Newson, Matthieu Cord A Cosmic-Scale Benchmark for Symmetry-Preserving Data Processing
Julia Balla, Siddharth Mishra-Sharma, Carolina Cuesta-Lazaro, Tommi Jaakkola, Tess Smidt A Deep Generative Model for the Design of Synthesizable Ionizable Lipids
Yuxuan Ou, Jingyi Zhao, Austin Tripp, Morteza Rasoulianboroujeni, José Miguel Hernández-Lobato A Diagonal State Space Model on Loihi 2 for Efficient Streaming Sequence Processing
Svea Marie Meyer, Philipp Weidel, Plank Philipp, Leobardo Campos-Macias, Sumit Bam Shrestha, Philipp Stratmann, Jonathan Timcheck, Mathis Richter A False Sense of Privacy: Evaluating Textual Data Sanitization Beyond Surface-Level Privacy Leakage
Rui Xin, Niloofar Mireshghallah, Shuyue Stella Li, Michael Duan, Hyunwoo Kim, Yejin Choi, Yulia Tsvetkov, Sewoong Oh, Pang Wei Koh A False Sense of Privacy: Evaluating Textual Data Sanitization Beyond Surface-Level Privacy Leakage
Rui Xin, Niloofar Mireshghallah, Shuyue Stella Li, Hyunwoo Kim, Michael Duan, Yejin Choi, Yulia Tsvetkov, Sewoong Oh, Pang Wei Koh A Foundation Model for Metagenomic Sequences
Ollie Liu, Sami Jaghouar, Johannes Hagemann, Jeff Kaufman, Willie Neiswanger A Geometric Foundation Model for Crystalline Material Discovery
Shengchao Liu, Liang Yan, Weitao Du, Zhuoxinran Li, Zhiling Zheng, Omar M. Yaghi, Christian Borgs, Hongyu Guo, Anima Anandkumar, Jennifer T Chayes A Hessian View of Grokking in Mathematical Reasoning
Zhenshuo Zhang, Jerry Weihong Liu, Christopher Re, Hongyang R. Zhang A Hopfield Network Model of Neuromodulatory Arousal State
Mohammed Abdal Monium Osman, Kai Fox, Joshua Isaac Stern A Large Encoder-Decoder Polymer-Based Foundation Model
Eduardo Soares, Nathaniel Park, Emilio Vital Brazil, Victor Yukio Shirasuna A Large Encoder-Decoder Polymer-Based Foundation Model
Eduardo Soares, Nathaniel Park, Emilio Vital Brazil, Victor Yukio Shirasuna A Large Recurrent Action Model: xLSTM Enables Fast Inference for Robotics Tasks
Thomas Schmied, Thomas Adler, Vihang Prakash Patil, Maximilian Beck, Korbinian Pöppel, Johannes Brandstetter, Günter Klambauer, Razvan Pascanu, Sepp Hochreiter A Large-Scale Foundation Model for RNA Function and Structure Prediction
Shuxian Zou, Tianhua Tao, Sazan Mahbub, Caleb Ellington, Robin Jonathan Algayres, Dian Li, Yonghao Zhuang, Hongyi Wang, Le Song, Eric P. Xing A Layer Selection Approach to Test Time Adaptation
Sabyasachi Sahoo, Mostafa ElAraby, Jonas Ngnawe, Yann Batiste Pequignot, Frederic Precioso, Christian Gagné A Linear Network Theory of Iterated Learning
Devon Jarvis, Richard Klein, Benjamin Rosman, Andrew M Saxe A Machine Learning Approach to Contact Localization in Variable Density Three-Dimensional Tactile Artificial Skin
Mitchell Murray, Yutong Zhang, Carson Kohlbrenner, Caleb Escobedo, Thomas Dunnington, Nolan Stevenson, Nikolaus Correll, Alessandro Roncone A Mamba-Based Foundation Model for Chemistry
Emilio Vital Brazil, Eduardo Soares, Victor Yukio Shirasuna, Renato Cerqueira, Dmitry Zubarev, Kristin Schmidt A Mamba-Based Foundation Model for Chemistry
Emilio Vital Brazil, Eduardo Soares, Victor Yukio Shirasuna, Renato Cerqueira, Dmitry Zubarev, Kristin Schmidt A Method on Searching Better Activation Functions
Haoyuan Sun, Zihao Wu, Bo Xia, Pu Chang, Zibin Dong, Yifu Yuan, Yongzhe Chang, Xueqian Wang A Minimalistic Representation Model for Head Direction System
Minglu Zhao, Dehong Xu, Deqian Kong, Wenhao Zhang, Ying Nian Wu A Multi-Power Law for Loss Curve Prediction Across Learning Rate Schedules
Kairong Luo, Haodong Wen, Shengding Hu, Zhenbo Sun, Zhiyuan Liu, Maosong Sun, Kaifeng Lyu, Wenguang Chen A New Geometric Approach of Adaptive Neighborhood Selection for Classification
Alexandre Luís Magalhães Levada, Frank Nielsen, Michel Ferreira Cardia Haddad A Physics Enforced Neural Network to Predict Polymer Melt Viscosity
Ayush Jain, Rishi Gurnani, Arunkumar Rajan, Hang Jerry Qi, Rampi Ramprasad A Practitioner's Guide to Continual Multimodal Pretraining
Karsten Roth, Vishaal Udandarao, Sebastian Dziadzio, Ameya Prabhu, Mehdi Cherti, Oriol Vinyals, Olivier J Henaff, Samuel Albanie, Matthias Bethge, Zeynep Akata A Primer on in Vitro Biological Neural Networks
Frithjof Gressmann, Ashley Chen, Lily Hexuan Xie, Sarah Dowden, Nancy Amato, Lawrence Rauchwerger A Probabilistic Generative Method for Safe Physical System Control Problems
Peiyan Hu, Xiaowei Qian, Wenhao Deng, Rui Wang, Haodong Feng, Ruiqi Feng, Tao Zhang, Long Wei, Yue Wang, Zhi-Ming Ma, Tailin Wu A Proposal for Post-OCR Spelling Correction Using Language Models
Sávio Santos de Araújo, Byron Leite Dantas Bezerra, Arthur Flor de Sousa Neto, Cleber Zanchettin A Realistic Threat Model for Large Language Model Jailbreaks
Valentyn Boreiko, Alexander Panfilov, Vaclav Voracek, Matthias Hein, Jonas Geiping A Self-Supervised Framework for Learning Whole Slide Representations
Xinhai Hou, Cheng Jiang, Akhil Kondepudi, Yiwei Lyu, Asadur Zaman Chowdury, Honglak Lee, Todd C Hollon A Self-Supervised Model for Multi-Modal Stroke Risk Prediction
Camille Delgrange, Olga V. Demler, Samia Mora, Bjoern Menze, Ezequiel De la Rosa, Neda Davoudi A Single Goal Is All You Need
Grace Liu, Michael Tang, Benjamin Eysenbach A Textbook Remedy for Domain Shifts: Knowledge Priors for Medical Image Analysis
Yue Yang, Mona Gandhi, Yufei Wang, Yifan Wu, Michael S Yao, Chris Callison-Burch, James Gee, Mark Yatskar A Theoretical Framework for Federated Domain Generalization with Gradient Alignment
Mahdiyar Molahasani, Milad Soltany, Farhad Pourpanah, Michael Greenspan, Ali Etemad A Theory for Compressibility of Graph Transformers for Transductive Learning
Hamed Shirzad, Honghao Lin, Ameya Velingker, Balaji Venkatachalam, David Woodruff, Danica J. Sutherland A Theory of Initialisation's Impact on Specialisation
Devon Jarvis, Sebastian Lee, Clémentine Carla Juliette Dominé, Andrew M Saxe, Stefano Sarao Mannelli A Theory of Interpretable Approximations
Marco Bressan, Nicolò Cesa-Bianchi, Emmanuel Esposito, Yishay Mansour, Shay Moran, Maximilian Thiessen A Tighter Complexity Analysis of SparseGPT
Xiaoyu Li, Yingyu Liang, Zhenmei Shi, Zhao Song A Unified Convergence Theory for Large Language Model Efficient Fine-Tuning
Zhanhong Jiang, Nastaran Saadati, Aditya Balu, Minh Pham, Joshua Russell Waite, Nasla Saleem, Chinmay Hegde, Soumik Sarkar A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning
Khimya Khetarpal, Zhaohan Daniel Guo, Bernardo Avila Pires, Yunhao Tang, Clare Lyle, Mark Rowland, Nicolas Heess, Diana L Borsa, Arthur Guez, Will Dabney A Walsh Hadamard Derived Linear Vector Symbolic Architecture
Mohammad Mahmudul Alam, Alexander Oberle, Edward Raff, Stella Biderman, Tim Oates, James Holt Accelerating Quantum Emitter Characterization with Latent Neural Ordinary Differential Equations
Andrew H. Proppe, Kin Long Kelvin Lee, Weiwei Sun, Chantalle J. Krajewska, Oliver Tye, Moungi Bawendi ACCO: Accumulate While You Communicate, Hiding Communications in Distributed LLM Training
Adel Nabli, Louis Fournier, Pierre Erbacher, Louis Serrano, Eugene Belilovsky, Edouard Oyallon Accumulating Data Avoids Model Collapse
Joshua Kazdan, Apratim Dey, Rylan Schaeffer, Matthias Gerstgrasser, Rafael Rafailov, David L. Donoho, Sanmi Koyejo Accuracy Isn’t Everything: Understanding the Desiderata of AI Tools in Legal-Financial Settings
Sudhan Chitgopkar, Noah Dohrmann, Stephanie Monson, Jimmy Mendez, Finale Doshi-Velez, Weiwei Pan Accurate and General DNA Representations Emerge from Genome Foundation Models at Scale
Caleb Ellington, Ning Sun, Nicholas Ho, Tianhua Tao, Sazan Mahbub, Dian Li, Yonghao Zhuang, Hongyi Wang, Eric P. Xing, Le Song Active Learning for Affinity Prediction of Antibodies
Alexandra Gessner, Sebastian W. Ober, Owen Niall Vickery, Dino Oglic, Talip Ucar Active Learning for Neural PDE Solvers
Daniel Musekamp, Marimuthu Kalimuthu, David Holzmüller, Makoto Takamoto, Mathias Niepert Active Learning for Optimal Minimization of Experimental Characterization Uncertainty
Marcus Schwarting, Nathan Seifert, Logan Ward, Ben Blaiszik, Ian Foster, Yuxin Chen, Kirill Prozument Adapting Language Models via Token Translation
Zhili Feng, Tanya Marwah, Lester Mackey, David Alvarez-Melis, Nicolo Fusi Adapting Language Models via Token Translation
Zhili Feng, Tanya Marwah, Nicolo Fusi, David Alvarez-Melis, Lester Mackey Adapting Language Models via Token Translation
Zhili Feng, Tanya Marwah, Nicolo Fusi, David Alvarez-Melis, Lester Mackey Adapting TabPFN for Zero-Inflated Metagenomic Data
Giulia Perciballi, Federica Granese, Ahmad Fall, Farida Zehraoui, Edi Prifti, Jean-Daniel Zucker Adaptive Hybrid Model Pruning in Federated Learning Through Loss Exploration
Christian Internò, Elena Raponi, Niki van Stein, Thomas Bäck, Markus Olhofer, Yaochu Jin, Barbara Hammer Adaptive Information Routing for Multi Modal Time Series Forecasting
Jun Seo, Hyeokjun Choe, Seohui Bae, Soyeon Park, Jinseok Yang, Dongwan Kang, Woohyung Lim Adaptive LoRA Merging for Efficient Domain Incremental Learning
Eric Nuertey Coleman, Luigi Quarantiello, Julio Hurtado, Vincenzo Lomonaco Adaptive LoRA Merging for Efficient Domain Incremental Learning
Luigi Quarantiello, Eric Nuertey Coleman, Julio Hurtado, Vincenzo Lomonaco Adaptive Neighborhoods in Contrastive Regression Learning for Brain Age Prediction
Jakob Träuble, Lucy V Hiscox, Curtis Johnson, Carola-Bibiane Schönlieb, Gabriele S Kaminski Schierle, Angelica I Aviles-Rivero Addressing Uncertainty in LLMs to Enhance Reliability in Generative AI
Ramneet Kaur, Colin Samplawski, Adam D. Cobb, Anirban Roy, Brian Matejek, Manoj Acharya, Daniel Elenius, Alexander Michael Berenbeim, John A. Pavlik, Nathaniel D. Bastian, Susmit Jha Advancing Theorem Proving in LLMs Through Large-Scale Synthetic Data
Huajian Xin, Daya Guo, Zhihong Shao, Z.Z. Ren, Qihao Zhu, Bo Liu, Chong Ruan, Wenda Li, Xiaodan Liang AdvBDGen: Adversarially Fortified Prompt-Specific Fuzzy Backdoor Generator Against LLM Alignment
Pankayaraj Pathmanathan, Udari Madhushani Sehwag, Michael-Andrei Panaitescu-Liess, Furong Huang Adversarial Databases Improve Success in Retrieval-Based Large Language Models
Sean Wu, Michael Koo, Li Yo Kao, Andy Black, Lesley Blum, Fabien Scalzo, Ira Kurtz Adversarial Prompt Evaluation: Systematic Benchmarking of Guardrails Against Prompt Input Attacks on LLMs
Giulio Zizzo, Giandomenico Cornacchia, Kieran Fraser, Muhammad Zaid Hameed, Ambrish Rawat, Beat Buesser, Mark Purcell, Pin-Yu Chen, Prasanna Sattigeri, Kush R. Varshney AEGIS2.0: A Diverse AI Safety Dataset and Risks Taxonomy for Alignment of LLM Guardrails
Shaona Ghosh, Prasoon Varshney, Makesh Narsimhan Sreedhar, Aishwarya Padmakumar, Traian Rebedea, Jibin Rajan Varghese, Christopher Parisien AGATa: Attention-Guided Augmentation for Tabular Data in Contrastive Learning
Moonjung Eo, Kyungeun Lee, Min-Kook Suh, Hye-Seung Cho, Ye Seul Sim, Woohyung Lim Agent S: An Open Agentic Framework That Uses Computers like a Human
Saaket Agashe, Jiuzhou Han, Shuyu Gan, Jiachen Yang, Ang Li, Xin Eric Wang Agent Skill Acquisition for LLMs via CycleQD
So Kuroki, Taishi Nakamura, Takuya Akiba, Yujin Tang Agentic Anomaly Detection for Shipping
Alexander Timms, Abigail Langbridge, Fearghal O'Donncha AgentMerge: Enhancing Generalization in Fine-Tuned LLM Agents
Megh Thakkar, Léo Boisvert, Thibault Le Sellier de Chezelles, Alexandre Piché, Maxime Gasse, Alexandre Lacoste, Massimo Caccia AgentStudio: A Toolkit for Building General Virtual Agents
Longtao Zheng, Zhiyuan Huang, Zhenghai Xue, Xinrun Wang, Bo An, Shuicheng Yan Aggregating Data for Optimal and Private Learning
Sushant Agarwal, Yukti Makhija, Rishi Saket, Aravindan Raghuveer Agnostic Causality-Driven Enhancement of Chemical Foundation Models on Downstream Tasks
Victor Yukio Shirasuna, Eduardo Soares, Emilio Vital Brazil, Karen Fiorella Aquino Gutierrez, Renato Cerqueira, Dmitry Zubarev, Kristin Schmidt AI Red Teaming Through the Lens of Measurement Theory
Alexandra Chouldechova, A. Feder Cooper, Abhinav Palia, Dan Vann, Chad Atalla, Hannah Washington, Emily Sheng, Hanna Wallach AI Sandbagging: Language Models Can Selectively Underperform on Evaluations
Teun van der Weij, Felix Hofstätter, Oliver Jaffe, Samuel F. Brown, Francis Rhys Ward AI-Assisted Generation of Difficult Math Questions
Vedant Shah, Dingli Yu, Kaifeng Lyu, Simon Park, Jiatong Yu, Yinghui He, Nan Rosemary Ke, Michael Curtis Mozer, Yoshua Bengio, Sanjeev Arora, Anirudh Goyal AI-Generated Content and Public Persuasion: The Limited Effect of AI Authorship Labels
Isabel O. Gallegos, Chen Shani, Weiyan Shi, Federico Bianchi, Robb Willer, Dan Jurafsky AIHWKIT-Lightning: A Scalable HW-Aware Training Toolkit for Analog In-Memory Computing
Julian Büchel, William Andrew Simon, Corey Lammie, Giovanni Acampa, Kaoutar El Maghraoui, Manuel Le Gallo, Abu Sebastian Algorithmic Oversight for Deceptive Reasoning
Ege Onur Taga, Mingchen Li, Yongqi Chen, Samet Oymak Algorithmic Stability of Minimum-Norm Interpolating Deep Neural Networks
Ouns El Harzli, Yoonsoo Nam, Ilja Kuzborskij, Bernardo Cuenca Grau, Ard A. Louis Align and Fine-Tune: Enhancing LLMs for Time-Series Forecasting
Ching Chang, Wei-Yao Wang, Wen-Chih Peng, Tien-Fu Chen, Sagar Samtani Aligned Multi-Objective Optimization
Yonathan Efroni, Daniel Jiang, Ben Kretzu, Jalaj Bhandari, Zheqing Zhu, Karen Ullrich Aligning to What? Limits to RLHF Based Alignment
Logan Barnhart, Reza Akbarian Bafghi, Maziar Raissi, Stephen Becker Aligning Touch, Vision, and Language for Multimodal Perception
Letian Fu, Gaurav Datta, Huang Huang, William Chung-Ho Panitch, Jaimyn Drake, Joseph Ortiz, Mustafa Mukadam, Mike Lambeta, Roberto Calandra, Ken Goldberg Alpaca Against Vicuna: Using LLMs to Uncover Memorization of LLMs
Aly M. Kassem, Omar Mahmoud, Niloofar Mireshghallah, Hyunwoo Kim, Yulia Tsvetkov, Yejin Choi, Sherif Saad, Santu Rana ALTA: Compiler-Based Analysis of Transformers
Peter Shaw, James Cohan, Jacob Eisenstein, Kenton Lee, Jonathan Berant, Kristina Toutanova Amortized Bayesian Workflow (Extended Abstract)
Marvin Schmitt, Chengkun Li, Aki Vehtari, Luigi Acerbi, Paul-Christian Bürkner, Stefan T. Radev Amortized Decision-Aware Bayesian Experimental Design
Daolang Huang, Yujia Guo, Luigi Acerbi, Samuel Kaski An Adversarial Perspective on Machine Unlearning for AI Safety
Jakub Łucki, Boyi Wei, Yangsibo Huang, Peter Henderson, Florian Tramèr, Javier Rando An Adversarial Perspective on Machine Unlearning for AI Safety
Jakub Łucki, Boyi Wei, Yangsibo Huang, Peter Henderson, Florian Tramèr, Javier Rando An Autonomy-Based Classification: Liability in the Age of AI Agents
Julia Smakman, Lisa Soder, Connor Dunlop, Weiwei Pan, Siddharth Swaroop An Elementary Predictor Obtaining 2\sqrt{T} Distance to Calibration
Eshwar Ram Arunachaleswaran, Natalie Collina, Aaron Roth, Mirah Shi An Information Criterion for Controlled Disentanglement of Multimodal Data
Chenyu Wang, Sharut Gupta, Xinyi Zhang, Sana Tonekaboni, Stefanie Jegelka, Tommi Jaakkola, Caroline Uhler An Information-Theoretic Analysis of Thompson Sampling for Logistic Bandits
Amaury Gouverneur, Borja Rodríguez Gálvez, Tobias Oechtering, Mikael Skoglund Analog Computing for AI Sometimes Needs Correction by Digital Computing: Why and When
Changdae Kim, Daegun Yoon, Taehoon Kim, Yeonjeong Jeong, Kangho Kim, Kwangwon Koh, Eunji Pak Analysing the Residual Stream of Language Models Under Knowledge Conflicts
Yu Zhao, Xiaotang Du, Giwon Hong, Aryo Pradipta Gema, Alessio Devoto, Hongru Wang, Xuanli He, Kam-Fai Wong, Pasquale Minervini Analyzing (In)Abilities of SAEs via Formal Languages
Abhinav Menon, Manish Shrivastava, Ekdeep Singh Lubana, David Krueger Analyzing Human Questioning Behavior and Causal Curiosity Through Natural Queries
Roberto Ceraolo, Dmitrii Kharlapenko, Amélie Reymond, Rada Mihalcea, Bernhard Schölkopf, Mrinmaya Sachan, Zhijing Jin Analyzing Probabilistic Methods for Evaluating Agent Capabilities
Axel Højmark, Govind Pimpale, Arjun Panickssery, Marius Hobbhahn, Jérémy Scheurer Analyzing Reward Functions via Trajectory Alignment
Calarina Muslimani, Suyog Chandramouli, Serena Booth, W. Bradley Knox, Matthew E. Taylor Anchored Optimization and Contrastive Revisions: Addressing Reward Hacking in Alignment
Karel D'Oosterlinck, Winnie Xu, Chris Develder, Thomas Demeester, Amanpreet Singh, Christopher Potts, Douwe Kiela, Shikib Mehri Annealing Machine-Assisted Learning of Graph Neural Network for Combinatorial Optimization
Pablo Loyola, Kento Hasegawa, Andrés Hoyos-Idrobo, Kazuo Ono, Toyotaro Suzumura, Yu Hirate, Masanao Yamaoka Antibody Library Design by Seeding Linear Programming with Inverse Folding and Protein Language Models
Conor F. Hayes, Andre R Goncalves, Steven Alan Magana-Zook, Ahmet Can Solak, Daniel Faissol, Mikel Landajuela AnyPrefer: An Automatic Framework for Preference Data Synthesis
Yiyang Zhou, Zhaoyang Wang, Tianle Wang, Shangyu Xing, Peng Xia, Bo Li, Kaiyuan Zheng, Zijian Zhang, Zhaorun Chen, Wenhao Zheng, Xuchao Zhang, Chetan Bansal, Weitong Zhang, Ying Wei, Mohit Bansal, Huaxiu Yao AnySkin: Plug-and-Play Skin Sensing for Robotic Touch
Raunaq Bhirangi, Venkatesh Pattabiraman, Mehmet Enes Erciyes, Yifeng Cao, Tess Hellebrekers, Lerrel Pinto Application of Contrastive Learning on ECG Data: Evaluating Performance in Japanese and Classification with Around 100 Labels
Junichiro Takahashi, JingChuan Guan, Masataka Sato, Kaito Baba, Kazuto Haruguchi, Daichi Nagashima, Satoshi Kodera, Norihiko Takeda Applications of Fractional Calculus in Learned Optimization
Teodor Alexandru Szente, James Harrison, Mihai Zanfir, Cristian Sminchisescu Applications of Modular Co-Design for De Novo 3D Molecule Generation
Danny Reidenbach, Filipp Nikitin, Olexandr Isayev, Saee Gopal Paliwal Approximate Top-K for Increased Parallelism
Oscar Key, Luka Ribar, Alberto Cattaneo, Luke Hudlass-Galley, Douglas Orr AptaBLE: A Deep Learning Platform for SELEX Optimization
Sawan Patel, Keith Fraser, Zhangzhi Peng, Adam D. Friedman, Owen Yao, Pranam Chatterjee, Sherwood Yao Are Capsule Networks Texture or Shape Biased?
Riccardo Renzulli, Dominik Vranay, Marco Grangetto Are Expressive Models Truly Necessary for Offline RL?
Guan Wang, Haoyi Niu, Jianxiong Li, Li Jiang, Jianming Hu, Xianyuan Zhan Are UFOs Driving Innovation? the Illusion of Causality in Large Language Models
María Victoria Carro, Francisca Gauna Selasco, Denise Alejandra Mester, Mario Leiva ASPred: Identification of Antigen Specific B-Cell Receptors from Single V(D)J Sequences Using Large Language Models
Karen Paco, Mariana Paco, Zihao Zhang, Isabel Condori, Sanaz Zebardast, Peace Olatoyinbo, Dhruv Patel, Jonathan Felix, Tristan Yang, Jordan Lay, Ilya Tolstorukov, Karine Le Roch, Matthew Sazinsky, Jeniffer Hernandez, Stefano Lonardi, Animesh Ray Assessing Interaction Recovery of Predicted Protein-Ligand Poses
David Errington, Constantin Schneider, Cédric Bouysset, Frederic A Dreyer Assisted Few-Shot Learning for Vision-Language Models in Agricultural Stress Phenotype Identification
Muhammad Arbab Arshad, Talukder Zaki Jubery, Asheesh K Singh, Arti Singh, Chinmay Hegde, Baskar Ganapathysubramanian, Aditya Balu, Adarsh Krishnamurthy, Soumik Sarkar AtmosArena: Benchmarking Foundation Models for Atmospheric Sciences
Tung Nguyen, Prateik Sinha, Advit Deepak, Karen A. McKinnon, Aditya Grover Attack Atlas: A Practitioner's Perspective on Challenges and Pitfalls in Red Teaming GenAI
Ambrish Rawat, Stefan Schoepf, Giulio Zizzo, Giandomenico Cornacchia, Muhammad Zaid Hameed, Kieran Fraser, Erik Miehling, Beat Buesser, Elizabeth M. Daly, Mark Purcell, Prasanna Sattigeri, Pin-Yu Chen, Kush R. Varshney AudioSetCaps: Enriched Audio Captioning Dataset Generation Using Large Audio Language Models
Jisheng Bai, Haohe Liu, Mou Wang, Dongyuan Shi, Wenwu Wang, Mark D Plumbley, Woon-Seng Gan, Jianfeng Chen Auditing Empirical Privacy Protection of Private LLM Adaptations
Lorenzo Rossi, Bartłomiej Marek, Vincent Hanke, Xun Wang, Michael Backes, Adam Dziedzic, Franziska Boenisch Automated, LLM Enabled Extraction of Synthesis Details for Reticular Materials from Scientific Literature
Viviane Torres da Silva, Alexandre Rademaker, Krystelle Lionti, Ronaldo Giro, Geisa Lima, Sandro Rama Fiorini, Marcelo Archanjo, Breno W S R Carvalho, Rodrigo Neumann Barros Ferreira, Anaximandro Souza, João Pedro Gandarela de Souza, Gabriela de Valnisio, Carmen Paz, Renato Cerqueira, Mathias B Steiner Automatic Solid Form Classification in Pharmaceutical Drug Development
Julius Lange, Leonid Komissarov, Rene Lang, Dennis Dimo Enkelmann, Andrea Anelli Automating Enterprise Data Engineering with LLMs
Jan-Micha Bodensohn, Ulf Brackmann, Liane Vogel, Anupam Sanghi, Carsten Binnig Automating Thought of Search: A Journey Towards Soundness and Completeness
Daniel Yiming Cao, Michael Katz, Harsha Kokel, Kavitha Srinivas, Shirin Sohrabi Autonomous Robotic Experimentation System for Powder X-Ray Diffraction
Yuto Yotsumoto, YusakuNakajima, Ryusei Takamoto, Yasuo Takeichi, Kanta Ono Autotelic LLM-Based Exploration for Goal-Conditioned RL
Guillaume Pourcel, Thomas Carta, Grgur Kovač, Pierre-Yves Oudeyer Avoiding Post-Processing with Context: Texture Boundary Detection in Metallography
Inbal Cohen, Julien Robitaille, Francis Quintal Lauzon, Ofer Beeri, Shai Avidan, Gal Oren Balancing Cost and Effectiveness of Synthetic Data Generation Strategies for LLMs
Yung-Chieh Chan, George Pu, Apaar Shanker, Parth Suresh, Penn Jenks, John Heyer, Samuel Marc Denton Batch Size Invariant Adam
Xi Wang, Laurence Aitchison BatchTopK Sparse Autoencoders
Bart Bussmann, Patrick Leask, Neel Nanda Bayesian Online Non-Stationary Detection for Robust Reinforcement Learning
Alexander Shmakov, Pankaj Rajak, Yuhao Feng, Wojciech Kowalinski, Fei Wang Bayesian Optimization of Antibodies Informed by a Generative Model of Evolving Sequences
Alan Nawzad Amin, Nate Gruver, Yucen Lily Li, Yilun Kuang, Hunter Elliott, Calvin McCarter, Aniruddh Raghu, Peyton Greenside, Andrew Gordon Wilson Bayesian Optimization of High-Dimensional Outputs with Human Feedback
Qing Feng, Zhiyuan Jerry Lin, Yujia Zhang, Benjamin Letham, Jelena Markovic-Voronov, Ryan-Rhys Griffiths, Peter I. Frazier, Eytan Bakshy Bayesian Outcome Weighted Learning
Nikki L. B. Freeman, Sophia Yazzourh Bayesian Rashomon Sets for Model Uncertainty: A Critical Comparison
Aparajithan Venkateswaran, Anirudh Sankar, Arun Chandrasekhar, Tyler McCormick Behavioral Sequence Modeling with Ensemble Learning
Maxime Kawawa-Beaudan, Srijan Sood, Soham Palande, Ganapathy Mani, Tucker Balch, Manuela Veloso Being Considerate as a Pathway Towards Pluralistic Alignment for Agentic AI
Parand A. Alamdari, Toryn Q. Klassen, Rodrigo Toro Icarte, Sheila A. McIlraith Benchmarking CNN-Based Systems for Corn Leaf Pest Detection Using Fine-Tuning
Mariana Risco Cosavalente, Sulei Jackeline Chang Román, Carlos Arturo Cortegana Silva Benchmarking Neural Lossless Compression Algorithms on Multi-Purpose Astronomical Image Data
Tuan Truong, Rithwik Sudharsan, Yibo Yang, Peter Xiangyuan Ma, Ruihan Yang, Stephan Mandt, Joshua S. Bloom Benchmarking Self-Supervised Learning for Single-Cell Data
Philip Toma, Olga Ovcharenko, Imant Daunhawer, Julia E Vogt, Florian Barkmann, Valentina Boeva Benchmarking Transcriptomics Foundation Models for Perturbation Analysis : One PCA Still Rules Them All
Ihab Bendidi, Shawn T. Whitfield, Kian Kenyon-Dean, Hanene Ben Yedder, Yassir El Mesbahi, Emmanuel Noutahi, Alisandra Kaye Denton Benign Overfitting in Single-Head Attention
Roey Magen, Shuning Shang, Zhiwei Xu, Spencer Frei, Wei Hu, Gal Vardi Best Practices for Multi-Fidelity Bayesian Optimization in Materials and Molecular Research
Victor Sabanza Gil, Riccardo Barbano, Daniel Pacheco Gutiérrez, Jeremy Scott Luterbacher, José Miguel Hernández-Lobato, Philippe Schwaller, Loïc Roch Best Unpacking DPO and PPO: Disentangling Practices for Learning from Preference Feedback
Hamish Ivison, Yizhong Wang, Jiacheng Liu, Zeqiu Wu, Valentina Pyatkin, Nathan Lambert, Noah A. Smith, Yejin Choi, Hannaneh Hajishirzi Better Prompt Compression Without Multi-Layer Perceptrons
Edouardo Honig, Andrew Lizarraga, Zijun Frank Zhang, Ying Nian Wu Beyond Closure Models: Learning Chaotic-Systems via Physics-Informed Neural Operators
Chuwei Wang, Julius Berner, Zongyi Li, Di Zhou, Jiayun Wang, Jane Bae, Anima Anandkumar Beyond Demographics: Aligning Role-Playing LLM-Based Agents Using Human Belief Networks
Yun-Shiuan Chuang, Krirk Nirunwiroj, Zach Studdiford, Agam Goyal, Vincent V. Frigo, Sijia Yang, Dhavan V. Shah, Junjie Hu, Timothy T. Rogers Beyond Directed Acyclic Computation Graph with Cyclic Neural Network
Liangwei Yang, Hengrui Zhang, Weizhi Zhang, Zihe Song, Jing Ma, Jiawei Zhang, Philip S. Yu BigDocs: An Open and Permissively-Licensed Dataset for Training Multimodal Models on Document and Code Tasks
Juan A. Rodriguez, Xiangru Jian, Siba Smarak Panigrahi, Tianyu Zhang, Aarash Feizi, Abhay Puri, Akshay Kalkunte Suresh, François Savard, Ahmed Masry, Shravan Nayak, Rabiul Awal, Mahsa Massoud, Amirhossein Abaskohi, Zichao Li, Suyuchen Wang, Pierre-Andre Noel, Mats Leon Richter, Saverio Vadacchino, Shubham Agarwal, Sanket Biswas, Sara Shanian, Ying Zhang, Kurt MacDonald, Sathwik Tejaswi Madhusudhan, Joao Monteiro, Krishnamurthy Dj Dvijotham, Torsten Scholak, Nicolas Chapados, Sepideh Kharaghani, Sean Hughes, M. Özsu, Siva Reddy, Marco Pedersoli, Yoshua Bengio, Christopher Pal, Issam H. Laradji, Spandana Gella, Perouz Taslakian, David Vazquez, Sai Rajeswar BinaryDM: Accurate Weight Binarization for Efficient Diffusion Models
Xingyu Zheng, Xianglong Liu, Haotong Qin, Xudong Ma, Mingyuan Zhang, Haojie Hao, Jiakai Wang, Zixiang Zhao, Jinyang Guo, Michele Magno Bio-xLSTM: Generative Modeling, Representation and In-Context Learning of Biological and Chemical Sequences
Niklas Schmidinger, Lisa Schneckenreiter, Philipp Seidl, Johannes Schimunek, Pieter-Jan Hoedt, Johannes Brandstetter, Andreas Mayr, Sohvi Luukkonen, Sepp Hochreiter, Günter Klambauer Biomedical SAM-2: Segment Anything in Biomedical Images and Videos
Zhiling Yan, Weixiang Sun, Rong Zhou, Zhengqing Yuan, Kai Zhang, Yiwei Li, Sekeun Kim, Sifan Song, Hui Ren, Tianming Liu, Quanzheng Li, Xiang Li, Lifang He, Lichao Sun BiRNA-BERT: Adaptive Tokenization for Efficient RNA Language Modeling
Md Toki Tahmid, Haz Sameen Shahgir, Sazan Mahbub, Yue Dong, Md Shamsuzzoha Bayzid BLAP: Bootstrapping Language-Audio Pre-Training for Music Captioning
Luca A Lanzendörfer, Constantin Pinkl, Nathanaël Perraudin, Roger Wattenhofer Bongard in Wonderland: Visual Puzzles That Still Make AI Go Mad?
Antonia Wüst, Tim Tobiasch, Lukas Helff, Devendra Singh Dhami, Constantin A. Rothkopf, Kristian Kersting Boosting Unsupervised Segmentation Learning
Alp Eren Sari, Francesco Locatello, Paolo Favaro Bottom-up and Top-Down Analysis of Values, Agendas, and Observations in Corpora and LLMs
Scott E. Friedman, Noam Benkler, Drisana Mosaphir, Jeffrey Rye, Sonja M. Schmer-Galunder, Micah Goldwater, Matthew McLure, Ruta Wheelock, Jeremy Gottlieb, Robert P. Goldman, Christopher Miller Bridging Biomolecular Modalities for Knowledge Transfer in Bio-Language Models
Mangal Prakash, Artem Moskalev, Peter DiMaggio Jr., Steven Combs, Tommaso Mansi, Justin Scheer, Rui Liao Bridging the Gap Between Database Search and \emph{De Novo} Peptide Sequencing with SearchNovo
Jun Xia, Sizhe Liu, Jingbo Zhou, Shaorong Chen, Hongxin Xiang, Zicheng Liu, Yue Liu, Stan Z. Li Buffer Overflow in Mixture of Experts
Jamie Hayes, Ilia Shumailov, Itay Yona Bulk Bitwise Accumulation in Commercial DRAM
Tatsuya Kubo, Masayuki Usui, Tomoya Nagatani, Daichi Tokuda, Lei Qu, Ting Cao, Shinya Takamaeda-Yamazaki Can Editing LLMs Inject Harm?
Canyu Chen, Baixiang Huang, Zekun Li, Zhaorun Chen, Shiyang Lai, Xiongxiao Xu, Jia-Chen Gu, Jindong Gu, Huaxiu Yao, Chaowei Xiao, Xifeng Yan, William Yang Wang, Philip Torr, Dawn Song, Kai Shu Can Generic LLMs Help Analyze Child-Adult Interactions Involving Children with Autism in Clinical Observation?
Tiantian Feng, Anfeng Xu, Rimita Lahiri, Sudarsana Reddy Kadiri, Helen Tager-Flusberg, So Hyun Kim, Somer Bishop, Catherine Lord, Shrikanth Narayanan Can Knowledge Editing Really Correct Hallucinations?
Baixiang Huang, Canyu Chen, Xiongxiao Xu, Ali Payani, Kai Shu Can Models Learn Skill Composition from Examples?
Haoyu Zhao, Simran Kaur, Dingli Yu, Anirudh Goyal, Sanjeev Arora Can Watermarking Large Language Models Prevent Copyrighted Text Generation and Hide Training Data?
Michael-Andrei Panaitescu-Liess, Zora Che, Bang An, Yuancheng Xu, Pankayaraj Pathmanathan, Souradip Chakraborty, Sicheng Zhu, Tom Goldstein, Furong Huang Can We Pre-Train ICL-Based SFMs for the Zero-Shot Inference of the 1d CDR Problem with Noisy Data?
Mingu Kang, Dongseok Lee, Woojin Cho, Kookjin Lee, Anthony Gruber, Nathaniel Trask, Youngjoon Hong, Noseong Park Causal Order: The Key to Leveraging Imperfect Experts in Causal Inference
Aniket Vashishtha, Abbavaram Gowtham Reddy, Abhinav Kumar, Saketh Bachu, Vineeth N. Balasubramanian, Amit Sharma Causal World Representation in the GPT Model
Raanan Yehezkel Rohekar, Yaniv Gurwicz, Sungduk Yu, Vasudev Lal Causally Testing Gender Bias in LLMs: A Case Study on Occupational Bias
Yuen Chen, Vethavikashini Chithrra Raghuram, Justus Mattern, Rada Mihalcea, Zhijing Jin Cell Ontology Guided Transcriptome Foundation Model
Xinyu Yuan, Zhihao Zhan, Zuobai Zhang, Manqi Zhou, Jianan Zhao, Boyu Han, Yue Li, Jian Tang Cell Ontology Guided Transcriptome Foundation Model
Xinyu Yuan, Zhihao Zhan, Zuobai Zhang, Manqi Zhou, Jianan Zhao, Boyu Han, Yue Li, Jian Tang Cell Ontology Guided Transcriptome Foundation Model
Xinyu Yuan, Zhihao Zhan, Zuobai Zhang, Manqi Zhou, Jianan Zhao, Boyu Han, Yue Li, Jian Tang Century: A Dataset of Sensitive Historical Images
Canfer Akbulut, Kevin Robinson, Maribeth Rauh, Isabela Albuquerque, Olivia Wiles, Laura Weidinger, Verena Rieser, Yana Hasson, Nahema Marchal, Iason Gabriel, William Isaac, Lisa Anne Hendricks Certifying Robustness via Topological Representations
Jens Agerberg, Andrea Guidolin, Andrea Martinelli, Pepijn Roos Hoefgeest, David Eklund, Martina Scolamiero Chain-of-Imagination for Reliable Instruction Following in Decision Making
Enshen Zhou, Yiran Qin, Zhenfei Yin, Yuzhou Huang, Ruimao Zhang, Lu Sheng, Yu Qiao, Jing Shao Challenge on Sound Scene Synthesis: Evaluating Text-to-Audio Generation
Junwon Lee, Modan Tailleur, Laurie M. Heller, Keunwoo Choi, Mathieu Lagrange, Brian McFee, Keisuke Imoto, Yuki Okamoto Characterizing Stable Regions in the Residual Stream of LLMs
Jett Janiak, Jacek Karwowski, Chatrik Singh Mangat, Giorgi Giglemiani, Nora Petrova, Stefan Heimersheim ChatBug: A Common Vulnerability of Aligned LLMs Induced by Chat Templates
Fengqing Jiang, Zhangchen Xu, Luyao Niu, Bill Yuchen Lin, Radha Poovendran ChemDFM: A Large Language Foundation Model for Chemistry
Zihan Zhao, Da Ma, Lu Chen, Liangtai Sun, Zihao Li, Yi Xia, Hongshen Xu, Zichen Zhu, Su Zhu, Shuai Fan, Guodong Shen, Kai Yu, Xin Chen ChemLit-QA: A Human Evaluated Dataset for Chemistry RAG Tasks
Geemi Wellawatte, Huixuan Guo, Magdalena Lederbauer, Anna Borisova, Matthew Hart, Marta Brucka, Philippe Schwaller CinePile: A Long Video Question Answering Dataset and Benchmark
Ruchit Rawal, Khalid Saifullah, Ronen Basri, David Jacobs, Gowthami Somepalli, Tom Goldstein CITER: Collaborative Inference for Efficient Large Language Model Decoding with Token-Level Routing
Wenhao Zheng, Yixiao Chen, Weitong Zhang, Souvik Kundu, Yun Li, Zhengzhong Liu, Eric P. Xing, Hongyi Wang, Huaxiu Yao Click & Describe: Multimodal Grounding and Tracking for Aerial Objects
Rupanjali Kukal, Jay Patravali, Fuxun Yu, Simranjit Singh, Nikolaos Karianakis, Rishi Madhok ClinicalBench: Can LLMs Beat Traditional ML Models in Clinical Prediction?
Canyu Chen, Jian Yu, Shan Chen, Che Liu, Zhongwei Wan, Danielle Bitterman, Fei Wang, Kai Shu CLoG: Benchmarking Continual Learning of Image Generation Models
Haotian Zhang, Junting Zhou, Haowei Lin, Hang Ye, Jianhua Zhu, Zihao Wang, Liangcai Gao, Yizhou Wang, Yitao Liang Coarse-to-Fine Text-to-Music Latent Diffusion
Luca A Lanzendörfer, Tongyu Lu, Nathanaël Perraudin, Dorien Herremans, Roger Wattenhofer Cognitive Bias for Human-AI Ad Hoc Teamwork
Shray Bansal, Jin Xu, Miguel Morales, Jonathan Streater, Ayanna Howard, Charles Jr. Cold Posterior Effect Towards Adversarial Robustness
Bruce Rushing, Antonios Alexos, Harrison Espino, Nicholas Cohen, Pierre Baldi Collaborative Training
Ariana Mirella Villegas Suarez Combining Domain and Alignment Vectors to Achieve Better Knowledge-Safety Trade-Offs in LLMs
Megh Thakkar, Yash More, Quentin Fournier, Matthew Riemer, Pin-Yu Chen, Amal Zouaq, Payel Das, Sarath Chandar Communication Compression for Tensor Parallel LLM Inference
Jan Hansen-Palmus, Michael Truong Le, Oliver Hausdörfer, Alok Verma Communication Subspaces Align with Training in ANNs
Peter G. L. Poggi, Stefan Mihalas, Dana Mastrovito Communication-Efficient Algorithms Under Generalized Smoothness Assumptions
Sarit Khirirat, Abdurakhmon Sadiev, Artem Riabinin, Eduard Gorbunov, Peter Richtárik Comparing Human and LLM Ratings of Music-Recommendation Quality with User Context
Sherol Chen, Yuri Vasilevski, Andrew Kyle Lampinen, Amnah Ahmad, Ndaba Ndebele, Sally Goldman, Michael Curtis Mozer, Jie Ren Comparing Implicit and Denoising Score-Matching Objectives
Artem Artemev, Ayan Das, Farhang Nabiei, Alberto Bernacchia Comparing the Local Information Geometry of Image Representations
David Lipshutz, Jenelle Feather, Sarah E Harvey, Alex H Williams, Eero P Simoncelli Comparison Visual Instruction Tuning
Wei Lin, Muhammad Jehanzeb Mirza, Sivan Doveh, Rogerio Feris, Raja Giryes, Sepp Hochreiter, Leonid Karlinsky Compliance Cards: Automated EU AI Act Compliance Analyses Amidst a Complex AI Supply Chain
Bill Marino, Yaqub Chaudhary, Yulu Pi, Rui-Jie Yew, Preslav Aleksandrov, Carwyn Rahman, William F. Shen, Isaac Robinson, Nicholas Donald Lane Compositional Generalization Across Distributional Shifts with Sparse Tree Operations
Paul Soulos, Henry Conklin, Mattia Opper, Paul Smolensky, Jianfeng Gao, Roland Fernandez Compositional Risk Minimization
Divyat Mahajan, Mohammad Pezeshki, Ioannis Mitliagkas, Kartik Ahuja, Pascal Vincent Compositional Visual Reasoning with SlotSSMs
Jindong Jiang, Fei Deng, Gautam Singh, Minseung Lee, Sungjin Ahn Compressing Recurrent Neural Networks for FPGA-Accelerated Implementation in Fluorescence Lifetime Imaging
Ismail Erbas, Vikas Pandey, Aporva Amarnath, Naigang Wang, Karthik Swaminathan, Stefan T. Radev, Xavier Intes Computation-Aware Robust Gaussian Processes
Marshal Arijona Sinaga, Julien Martinelli, Samuel Kaski Concept Denoising Score Matching for Responsible Text-to-Image Generation
Silpa Vadakkeeveetil Sreelatha, Sauradip Nag, Serge Belongie, Muhammad Awais, Anjan Dutta Concept Unlearning for Large Language Models
Tomoya Yamashita, Takayuki Miura, Yuuki Yamanaka, Toshiki Shibahara, Masanori Yamada ConceptDrift: Uncovering Biases Through the Lens of Foundation Models
Cristian Daniel Paduraru, Antonio Barbalau, Radu Filipescu, Andrei Liviu Nicolicioiu, Elena Burceanu CONCLAD: COntinuous Novel CLAss Detector
Amanda Sofie Rios, Ibrahima Jacques Ndiour, Parual Datta, Omesh Tickoo, Nilesh Ahuja Conditional Language Policy: A General Framework for Steerable Multi-Objective Finetuning
Kaiwen Wang, Rahul Kidambi, Ryan Sullivan, Alekh Agarwal, Christoph Dann, Andrea Michi, Marco Gelmi, Yunxuan Li, Raghav Gupta, Kumar Avinava Dubey, Alexandre Rame, Johan Ferret, Geoffrey Cideron, Le Hou, Hongkun Yu, Amr Ahmed, Aranyak Mehta, Leonard Hussenot, Olivier Bachem, Edouard Leurent Conic Activation Functions
Changqing Fu, Laurent D. Cohen Consistency-Diversity-Realism Pareto Fronts of Conditional Image Generative Models
Pietro Astolfi, Melissa Hall, Jakob Verbeek, Marlene Careil, Oscar Mañas, Matthew J. Muckley, Adriana Romero-Soriano, Michal Drozdzal Constrained Multi-Objective Bayesian Optimization
Diantong Li, Fengxue Zhang, Chong Liu, Yuxin Chen Context Is Key: A Benchmark for Forecasting with Essential Textual Information
Arjun Ashok, Andrew Robert Williams, Étienne Marcotte, Valentina Zantedeschi, Jithendaraa Subramanian, Roland Riachi, James Requeima, Alexandre Lacoste, Irina Rish, Nicolas Chapados, Alexandre Drouin Contextual Evaluation of Large Language Models for Classifying Tropical and Infectious Diseases
Mercy Nyamewaa Asiedu, Nenad Tomasev, Chintan Ghate, Tiya Tiyasirichokchai, Awa Dieng, Oluwatosin Wuraola Akande, Geoffrey Siwo, Steve Adudans, Sylvanus Oliver Aitkins, Odianosen Ehiakhamen, Eric M. Ndombi, Katherine A Heller Contextual Evaluation of Large Language Models for Classifying Tropical and Infectious Diseases
Mercy Nyamewaa Asiedu, Nenad Tomasev, Chintan Ghate, Tiya Tiyasirichokchai, Awa Dieng, Geoffrey Siwo, Steve Adudans, Oluwatosin Wuraola Akande, Katherine A Heller Contextualizing Biological Perturbation Experiments Through Language
Menghua Wu, Russell Littman, Jacob Levine, Lin Qiu, Tommaso Biancalani, David Richmond, Jan-Christian Huetter Contrastive Language–Structure Pre-Training Driven by Materials Science Literature
Yuta Suzuki, Tatsunori Taniai, Ryo Igarashi, Kotaro Saito, Naoya Chiba, Yoshitaka Ushiku, Kanta Ono Contrastive Lyrics Alignment with a Timestamp-Informed Loss
Timon Kick, Florian Grötschla, Luca A Lanzendörfer, Roger Wattenhofer Controlling Multimodal LLMs via Reward-Guided Decoding
Oscar Mañas, Pierluca D'Oro, Koustuv Sinha, Adriana Romero-Soriano, Michal Drozdzal, Aishwarya Agrawal Convergence of Manifold Filter-Combine Networks
David R Johnson, Joyce Chew, Siddharth Viswanath, Edward De Brouwer, Deanna Needell, Smita Krishnaswamy, Michael Perlmutter Coordinated Robustness Evaluation Framework for Vision Language Models
Ashwin Ramesh Babu, Sajad Mousavi, Desik Rengarajan, Vineet Gundecha, Sahand Ghorbanpour, Avisek Naug, Antonio Guillen, Ricardo Luna Gutierrez, Soumyendu Sarkar CopRA: A Progressive LoRA Training Strategy
Zhan Zhuang, Xiequn Wang, Yulong Zhang, Wei Li, Yu Zhang, Ying Wei CopyBench: Measuring Literal and Non-Literal Reproduction of Copyright-Protected Text in Language Model Generation
Tong Chen, Akari Asai, Niloofar Mireshghallah, Sewon Min, James Grimmelmann, Yejin Choi, Hannaneh Hajishirzi, Luke Zettlemoyer, Pang Wei Koh CopyBench: Measuring Literal and Non-Literal Reproduction of Copyright-Protected Text in Language Model Generation
Tong Chen, Akari Asai, Niloofar Mireshghallah, Sewon Min, James Grimmelmann, Yejin Choi, Hannaneh Hajishirzi, Luke Zettlemoyer, Pang Wei Koh COrAL: Order-Agnostic Language Modeling for Efficient Iterative Refinement
Yuxi Xie, Anirudh Goyal, Xiaobao Wu, Xunjian Yin, Xiao Xu, Min-Yen Kan, Liangming Pan, William Yang Wang CoS: Enhancing Personalization with Context Steering
Sashrika Pandey, Jerry Zhi-Yang He, Mariah L Schrum, Anca Dragan CoS: Enhancing Personalization with Context Steering
Sashrika Pandey, Jerry Zhi-Yang He, Mariah L Schrum, Anca Dragan CoS: Enhancing Personalization with Context Steering
Sashrika Pandey, Jerry Zhi-Yang He, Mariah L Schrum, Anca Dragan Cost-Effective Reduced-Order Modeling via Bayesian Active Learning
Amir Hossein Rahmati, Nathan Urban, Byung-Jun Yoon, Xiaoning Qian Counterfactual Explanations via Riemannian Latent Space Traversal
Paraskevas Pegios, Aasa Feragen, Andreas Abildtrup Hansen, Georgios Arvanitidis Counterfactual Token Generation in Large Language Models
Ivi Chatzi, Nina L. Corvelo Benz, Eleni Straitouri, Stratis Tsirtsis, Manuel Gomez Rodriguez CRAB: Cross-Platfrom Agent Benchmark for Multi-Modal Embodied Language Model Agents
Tianqi Xu, Linyao Chen, Dai-Jie Wu, Yanjun Chen, Zecheng Zhang, Xiang Yao, Zhiqiang Xie, Yongchao Chen, Shilong Liu, Bochen Qian, Philip Torr, Bernard Ghanem, Guohao Li Cradle: Empowering Foundation Agents Towards General Computer Control
Weihao Tan, Wentao Zhang, Xinrun Xu, Haochong Xia, Gang Ding, Boyu Li, Bohan Zhou, Junpeng Yue, Jiechuan Jiang, Yewen Li, Ruyi An, Molei Qin, Chuqiao Zong, Longtao Zheng, YuJie Wu, Xiaoqiang Chai, Yifei Bi, Tianbao Xie, Pengjie Gu, Xiyun Li, Ceyao Zhang, Long Tian, Chaojie Wang, Xinrun Wang, Börje F. Karlsson, Bo An, Shuicheng Yan, Zongqing Lu Cream: Consistency Regularized Self-Rewarding Language Models
Zhaoyang Wang, Weilei He, Zhiyuan Liang, Xuchao Zhang, Chetan Bansal, Ying Wei, Weitong Zhang, Huaxiu Yao Critique-Out-Loud Reward Models
Zachary Ankner, Mansheej Paul, Brandon Cui, Jonathan Daniel Chang, Prithviraj Ammanabrolu CrossCheckGPT: Universal Hallucination Ranking for Multimodal Foundation Models
Guangzhi Sun, Potsawee Manakul, Adian Liusie, Kunat Pipatanakul, Chao Zhang, Phil Woodland, Mark Gales Crosslingual Capabilities and Knowledge Barriers in Multilingual Large Language Models
Lynn Chua, Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chulin Xie, Chiyuan Zhang Crystal Design Amidst Noisy DFT Signals: A Reinforcement Learning Approach
Prashant Govindarajan, Mathieu Reymond, Santiago Miret, Mariano Phielipp, Sarath Chandar CSRec: Rethinking Sequential Recommendation from a Causal Perspective.
Xiaoyu Liu, Jiaxin Yuan, Yuhang Zhou, Jingling Li, Furong Huang, Wei Ai CTRL-O: Language-Controllable Object-Centric Visual Representation Learning
Aniket Rajiv Didolkar, Andrii Zadaianchuk, Rabiul Awal, Maximilian Seitzer, Efstratios Gavves, Aishwarya Agrawal CUAL: Continual Uncertainty-Aware Active Learner
Amanda Sofie Rios, Ibrahima Jacques Ndiour, Jaroslaw Sydir, Parual Datta, Omesh Tickoo, Nilesh Ahuja Curiosity-Driven Red Teaming for Large Language Models
Zhang-Wei Hong, Idan Shenfeld, Tsun-Hsuan Wang, Yung-Sung Chuang, Aldo Pareja, James R. Glass, Akash Srivastava, Pulkit Agrawal DADA: Dual Averaging with Distance Adaptation
Mohammad Moshtaghifar, Anton Rodomanov, Daniil Vankov, Sebastian U Stich DafnyBench: A Benchmark for Formal Software Verification
Chloe R Loughridge, Qinyi Sun, Seth Ahrenbach, Federico Cassano, Chuyue Sun, Ying Sheng, Anish Mudide, Md Rakib Hossain Misu, Nada Amin, Max Tegmark DARD: A Multi-Agent Approach for Task-Oriented Dialog Systems
Aman Gupta, Anirudh Ravichandran, Ziji Zhang, Swair Shah, Anurag Beniwal, Narayanan Sadagopan Debiasing Global Workspace: A Cognitive Neural Framework for Learning Debiased and Interpretable Representations
Jinyung Hong, Eun Som Jeon, Changhoon Kim, Keun Hee Park, Utkarsh Nath, Yezhou Yang, Pavan K. Turaga, Theodore P. Pavlic Debiasing Large Vision-Language Models by Ablating Protected Attribute Representations
Neale Ratzlaff, Matthew Lyle Olson, Musashi Hinck, Shao-Yen Tseng, Vasudev Lal, Phillip Howard Decision-Driven Calibration for Cost-Sensitive Uncertainty Quantification
Gregory Canal, Vladimir Leung, John J. Guerrerio, Philip Sage, I-Jeng Wang Decoding Biases: An Analysis of Automated Methods and Metrics for Gender Bias Detection in Language Models
Shachi H. Kumar, Saurav Sahay, Sahisnu Mazumder, Eda Okur, Ramesh Manuvinakurike, Nicole Marie Beckage, Hsuan Su, Hung-yi Lee, Lama Nachman DeComFL: Federated Learning with Dimension-Free Communication
Zhe Li, Bicheng Ying, Zidong Liu, Chaosheng Dong, Haibo Yang Decompose, Recompose, and Conquer: Multi-Modal LLMs Are Vulnerable to Compositional Adversarial Attacks in Multi-Image Queries
Julius Broomfield, George Ingebretsen, Reihaneh Iranmanesh, Sara Pieri, Ethan Kosak-Hine, Tom Gibbs, Reihaneh Rabbany, Kellin Pelrine Decompose, Recompose, and Conquer: Multi-Modal LLMs Are Vulnerable to Compositional Adversarial Attacks in Multi-Image Queries
Julius Broomfield, George Ingebretsen, Reihaneh Iranmanesh, Sara Pieri, Ethan Kosak-Hine, Tom Gibbs, Reihaneh Rabbany, Kellin Pelrine Decomposing Complex Visual Comprehension into Atomic Visual Skills for Vision Language Models
Hyunsik Chae, Seungwoo Yoon, Chloe Yewon Chun, Gyehun Go, Yongin Cho, Gyeongmin Lee, Ernest K. Ryu Deconstructing What Makes a Good Optimizer for Language Models
Rosie Zhao, Depen Morwani, David Brandfonbrener, Nikhil Vyas, Sham M. Kakade Deep Clustering with Associative Memories
Bishwajit Saha, Dmitry Krotov, Mohammed J Zaki, Parikshit Ram DeepInception: Hypnotize Large Language Model to Be Jailbreaker
Xuan Li, Zhanke Zhou, Jianing Zhu, Jiangchao Yao, Tongliang Liu, Bo Han Deliberate Practice with Synthetic Data
Reyhane Askari-Hemmat, Mohammad Pezeshki, Pietro Astolfi, Melissa Hall, Florian Bordes, Jakob Verbeek, Michal Drozdzal, Adriana Romero-Soriano Demo: An Exploration of LLM-Guided Conversation in Reminiscence Therapy
Jinhao Duan, Xinyu Zhao, Zhuoxuan Zhang, Eunhye Grace Ko, Lily Boddy, Chenan Wang, Tianhao Li, Alexander Rasgon, Junyuan Hong, Min Kyung Lee, Chenxi Yuan, Qi Long, Ying Ding, Tianlong Chen, Kaidi Xu Demographic Bias of Expert-Level Vision-Language Foundation Models in Medical Imaging
Yuzhe Yang, Yujia Liu, Xin Liu, Avanti Gulhane, Domenico Mastrodicasa, Wei Wu, Edward J Wang, Dushyant Sahani, Shwetak Patel Denoising for Manifold Extrapolation
Zeyu Yun, Galen Chuang, Derek Dong, Yubei Chen Dense Backpropagation Improves Routing for Sparsely-Gated Mixture-of-Experts
Ashwinee Panda, Vatsal Baherwani, Zain Sarwar, Benjamin Thérien, Stephen Rawls, Sambit Sahu, Supriyo Chakraborty, Tom Goldstein Dense Backpropagation Improves Routing for Sparsely-Gated Mixture-of-Experts
Ashwinee Panda, Vatsal Baherwani, Zain Sarwar, Benjamin Thérien, Stephen Rawls, Sambit Sahu, Supriyo Chakraborty, Tom Goldstein Derivative-Free Guidance in Continuous and Discrete Diffusion Models with Soft Value-Based Decoding
Xiner Li, Yulai Zhao, Chenyu Wang, Gabriele Scalia, Gökcen Eraslan, Surag Nair, Tommaso Biancalani, Shuiwang Ji, Aviv Regev, Sergey Levine, Masatoshi Uehara Designing Algorithmic Delegates
Sophie Greenwood, Karen Levy, Solon Barocas, Jon Kleinberg, Hoda Heidari Designing Polaritonic Integrated Circuits for Quantum Processing
Mathias Van Regemortel, Wolfger Peelaers, Thomas Van Vaerenbergh Detection of RNA Editing Sites by GPT Fine-Tuning
Zohar Rosenwasser, Erez Levanon, Michael Levitt, Gal Oren Developing a Foundation Model for Predicting Material Failure
Agnese Marcato, Javier E. Santos, Aleksandra Pachalieva, Kai Gao, Ryley Hill, Esteban Rougier, Qinjun Kang, Jeffrey Hyman, Abigail Hunter, Janel Chua, Earl Lawrence, Hari Viswanathan, Daniel O'Malley Developing Story: Case Studies of Generative AI’s Use in Journalism
Natalie Grace Brigham, Chongjiu Gao, Tadayoshi Kohno, Franziska Roesner, Niloofar Mireshghallah Device-Directed Speech Detection for Follow-up Conversations Using Large Language Models
Ognjen Rudovic, Pranay Dighe, Yi Su, Vineet Garg, Sameer Dharur, Xiaochuan Niu, Ahmed Hussen Abdelaziz, Saurabh Adya, Ahmed Tewfik DFM: Interpolant-Free Dual Flow Matching
Denis A Gudovskiy, Tomoyuki Okuno, Yohei Nakata DIETing: Self-Supervised Learning with Instance Discrimination Learns Identifiable Features
Attila Juhos, Alice Bizeul, Patrik Reizinger, David Klindt, Randall Balestriero, Mark Ibrahim, Julia E Vogt, Wieland Brendel DIETing: Self-Supervised Learning with Instance Discrimination Learns Identifiable Features
Attila Juhos, Alice Bizeul, Patrik Reizinger, Randall Balestriero, David Klindt, Mark Ibrahim, Julia E Vogt, Wieland Brendel DiffBatt: A Diffusion Model for Battery Degradation Prediction and Synthesis
Hamidreza Eivazi, André Hebenbrock, Raphael Ginster, Steffen Blömeke, Stefan Wittek, Christoph Hermann, Thomas S. Spengler, Thomas Turek, Andreas Rausch Differentiable Attention
Yancheng Wang, Dongfang Sun, Yingzhen Yang Differentially Private Continual Learning Using Pre-Trained Models
Marlon Tobaben, Marcus Klasson, Rui Li, Arno Solin, Antti Honkela Differentially Private Sequential Data Synthesis with Structured State Space Models and Diffusion Models
Tomoya Matsumoto, Takayuki Miura, Toshiki Shibahara, Masanobu Kii, Kazuki Iwahana, Osamu Saisho, Shingo Okamura DiffTextPure: Defending Large Language Models with Diffusion Purifiers
Huanran Chen, Ziruo Wang, Yihan Yang, Shuo Zhang, Zeming Wei, Fusheng Jin, Yinpeng Dong Diffusion Models with Learned Adaptive Noise
Subham Sekhar Sahoo, Aaron Gokaslan, Christopher De Sa, Volodymyr Kuleshov Diffusion Models with Learned Adaptive Noise Processes
Subham Sekhar Sahoo, Aaron Gokaslan, Christopher De Sa, Volodymyr Kuleshov Dimension Deficit: Is 3D a Step Too Far for Optimizing Molecules?
Andres Guzman Cordero, Luca Thiede, Gary Tom, Alan Aspuru-Guzik, Felix Strieth-Kalthoff, Agustinus Kristiadi Dipper: Diversity in Prompts for Producing Large Language Model Ensembles in Reasoning Tasks
Gregory Kang Ruey Lau, Wenyang Hu, Liu Diwen, Chen Jizhuo, See-Kiong Ng, Bryan Kian Hsiang Low Discrete Diffusion Schrödinger Bridge Matching for Graph Transformation
Jun Hyeong Kim, Seonghwan Kim, Seokhyun Moon, Hyeongwoo Kim, Jeheon Woo, Woo Youn Kim Discrete-Continuous Variational Optimization with Local Gradients
Jonathan H Warrell, Francesco Alesiani, Cameron Smith, Anja Mösch, Martin Renqiang Min Disentangling Multi-Instrument Music Audio for Source-Level Pitch and Timbre Manipulation
Yin-Jyun Luo, Kin Wai Cheuk, Woosung Choi, Wei-Hsiang Liao, Keisuke Toyama, Toshimitsu Uesaka, Koichi Saito, Chieh-Hsin Lai, Yuhta Takida, Simon Dixon, Yuki Mitsufuji Dissecting Adversarial Robustness of Multimodal LM Agents
Chen Henry Wu, Rishi Rajesh Shah, Jing Yu Koh, Russ Salakhutdinov, Daniel Fried, Aditi Raghunathan Distillation of Discrete Diffusion Through Dimensional Correlations
Satoshi Hayakawa, Yuhta Takida, Masaaki Imaizumi, Hiromi Wakaki, Yuki Mitsufuji Distilling Structural Representations into Protein Sequence Models
Jeffrey Ouyang-Zhang, Chengyue Gong, Yue Zhao, Philipp Kraehenbuehl, Adam Klivans, Daniel Jesus Diaz Distilling System 2 into System 1
Ping Yu, Jing Xu, Jason E Weston, Ilia Kulikov Diverging Preferences: When Do Annotators Disagree and Do Models Know?
Michael JQ Zhang, Zhilin Wang, Jena D. Hwang, Yi Dong, Olivier Delalleau, Yejin Choi, Eunsol Choi, Xiang Ren, Valentina Pyatkin DiversityMedQA: A Benchmark for Assessing Demographic Biases in Medical Diagnosis Using Large Language Models
Rajat Rawat, Hudson McBride, Rajarshi Ghosh, Dhiyaan Chakkresh Nirmal, Jong Moon, Dhruv Alamari, Kevin Zhu, Sean O'Brien Do Large Language Models Have Shared Weaknesses in Medical Question Answering?
Andrew Michael Bean, Karolina Korgul, Felix Krones, Robert McCraith, Adam Mahdi Do LLMs Estimate Uncertainty Well in Instruction-Following?
Juyeon Heo, Miao Xiong, Christina Heinze-Deml, Jaya Narain Do LLMs Internally ``know'' When They Follow Instructions?
Juyeon Heo, Christina Heinze-Deml, Oussama Elachqar, Shirley You Ren, Kwan Ho Ryan Chan, Udhyakumar Nallasamy, Andrew Miller, Jaya Narain Does Equivariance Matter at Scale?
Johann Brehmer, Sönke Behrends, Pim De Haan, Taco Cohen Does Maximizing Neural Regression Scores Teach Us About the Brain?
Rylan Schaeffer, Mikail Khona, Sarthak Chandra, Mitchell Ostrow, Brando Miranda, Sanmi Koyejo Does Safety Training of LLMs Generalize to Semantically Related Natural Prompts?
Sravanti Addepalli, Yerram Varun, Arun Suggala, Karthikeyan Shanmugam, Prateek Jain Domain Adaptation for Robust Model Routing
Christoph Dann, Yishay Mansour, Teodor Vanislavov Marinov, Mehryar Mohri Dreaming Learning
Alessandro Londei, Matteo Benati, Denise Lanzieri, Vittorio Loreto DuoDiff: Accelerating Diffusion Models with a Dual-Backbone Approach
Daniel Gallo Fernández, Răzvan-Andrei Matișan, Alejandro Monroy Muñoz, Ana Maria Vasilcoiu, Janusz Partyka, Tin Hadži Veljković, Metod Jazbec Dyadic Learning in Recurrent and Feedforward Models
Rasmus Høier, Kirill Kalinin, Maxence Ernoult, Christopher Zach Dyadic Learning in Recurrent and Feedforward Models
Rasmus Høier, Kirill Kalinin, Maxence Ernoult, Christopher Zach Dynamic Negative Guidance of Diffusion Models: Towards Immediate Content Removal
Felix Koulischer, Johannes Deleu, Gabriel Raya, Thomas Demeester, Luca Ambrogioni Dynamic Planning with a LLM
Gautier Dagan, Frank Keller, Alex Lascarides Dynamics Based Neural Encoding with Inter-Intra Region Connectivity
Mai Gamal, Mohamed Rashad Abdel Hamid, Eman Ehab Nasef, Seif Eldawlatly, Mennatullah Siam Dynamics of Concept Learning and Compositional Generalization
Yongyi Yang, Core Francisco Park, Ekdeep Singh Lubana, Maya Okawa, Wei Hu, Hidenori Tanaka dZiner: Rational Inverse Design of Materials with AI Agents
Mehrad Ansari, Jeffrey Watchorn, Carla E. Brown, Joseph S Brown Economics Arena for Large Language Models
Shangmin Guo, Haochuan Wang, Haoran Bu, Yi Ren, Dianbo Sui, Yu-Ming Shang, Siting Estee Lu Effective Protein-Protein Interaction Exploration with PPIretrieval
Chenqing Hua, Connor W. Coley, Guy Wolf, Doina Precup, Shuangjia Zheng Effectively Leveraging Exogenous Information Across Neural Forecasters
Andres Potapczynski, Kin G. Olivares, Malcolm Wolff, Andrew Gordon Wilson, Dmitry Efimov, Vincent Quenneville-Belair Efficacy of the SAGE-RT Dataset for Model Safety Alignment: A Comparative Study
Tanay Baswa, Nitin Aravind Birur, Divyanshu Kumar, Jatan Loya, Anurakt Kumar, Prashanth Harshangi, Sahil Agarwal Efficient and Effective Uncertainty Quantification for LLMs
Miao Xiong, Andrea Santilli, Michael Kirchhof, Adam Golinski, Sinead Williamson Efficient Autoencoder Pipeline for Discovering High Entropy Alloys with Molecular Dynamics Data
Amirhossein Naghdi Dorabati, Grzegorz Kaszuba, Stefanos Papanikolaou, Andrzej Jaszkiewicz, Piotr Sankowski Efficient Design-and-Control Automation with Reinforcement Learning and Adaptive Exploration
Jiajun Fan, Hongyao Tang, Michael Przystupa, Mariano Phielipp, Santiago Miret, Glen Berseth Efficient Fine-Tuning of Image-Conditional Diffusion Models for Depth and Surface Normal Estimation
Gonzalo Martin Garcia, Karim Abou Zeid, Christian Schmidt, Daan de Geus, Alexander Hermans, Bastian Leibe Efficient Model Compression Techniques with FishLeg
Jamie McGowan, Wei Sheng Lai, Weibin Chen, Henry Aldridge, Jools Clarke, Jezabel R Garcia, Rui Xia, Yilei Liang, Guillaume Hennequin, Alberto Bernacchia Efficient Reinforcement Learning via Large Language Model-Based Search
Siddhant Bhambri, Amrita Bhattacharjee, Huan Liu, Subbarao Kambhampati Efficient Subgraph GNNs via Graph Products and Coarsening
Guy Bar-Shalom, Yam Eitan, Fabrizio Frasca, Haggai Maron Eliminating Position Bias of Language Models: A Mechanistic Approach
Ziqi Wang, Hanlin Zhang, Xiner Li, Kuan-Hao Huang, Chi Han, Shuiwang Ji, Sham M. Kakade, Hao Peng, Heng Ji Embodied LLM Agents Learn to Cooperate in Organized Teams
Xudong Guo, Kaixuan Huang, Jiale Liu, Wenhui Fan, Natalia Vélez, Qingyun Wu, Huazheng Wang, Thomas L. Griffiths, Mengdi Wang Embodied-RAG: General Non-Parametric Embodied Memory for Retrieval and Generation
Quanting Xie, So Yeon Min, Tianyi Zhang, Kedi Xu, Aarav Bajaj, Russ Salakhutdinov, Matthew Johnson-Roberson, Yonatan Bisk Embodied-RAG: General Non-Parametric Embodied Memory for Retrieval and Generation
Quanting Xie, So Yeon Min, Tianyi Zhang, Kedi Xu, Aarav Bajaj, Russ Salakhutdinov, Matthew Johnson-Roberson, Yonatan Bisk Emergence in Non-Neural Models: Grokking Modular Arithmetic via Average Gradient Outer Product
Neil Rohit Mallinar, Daniel Beaglehole, Libin Zhu, Adityanarayanan Radhakrishnan, Parthe Pandit, Mikhail Belkin Emergence of Hierarchical Emotion Representations in Large Language Models
Bo Zhao, Maya Okawa, Eric J Bigelow, Rose Yu, Tomer Ullman, Hidenori Tanaka Emergence of Steganography Between Large Language Models
Yohan Mathew, Robert McCarthy, Joan Velja, Ollie Matthews, Nandi Schoots, Dylan Cope Emergence of Text Semantics in CLIP Image Encoders
Sreeram Vennam, Shashwat Singh, Anirudh Govil, Ponnurangam Kumaraguru Empowering Neural Networks with Control and Planning Abilities
Shuyuan Wang, Philip D Loewen, Bhushan Gopaluni, Michael Forbes Empowerment and Causal Learning
Annya Dahmani, Aly Lidayan, Alison Gopnik EncCluster: Bringing Functional Encryption in Federated Foundational Models
Vasileios Tsouvalas, Samaneh Mohammadi, Ali Balador, Tanir Özçelebi, Francesco Flammini, Nirvana Meratnia Energy-Based Conceptual Diffusion Model
Yi Qin, Xinyue Xu, Hao Wang, Xiaomeng Li Energy-Efficient Random Number Generation Using Stochastic Magnetic Tunnel Junctions
Nicolas Alder, Shivam Nitin Kajale, Milin Tunsiricharoengul, Deblina Sarkar, Ralf Herbrich Enhance Time Series Modeling by Integrating LLM
Can Chen, Gabriel L. Oliveira, Hossein Sharifi-Noghabi, Tristan Sylvain Enhanced Exploration via Variational Learned Priors
Jessica Nicholson, Joseph S Goodier, Akshil Patel, Özgür Şimşek Enhancing Biomedical Schema Matching with LLM-Based Training Data Generation
Yurong Liu, Aécio Santos, Eduardo H. M. Pena, Roque Lopez, Eden Wu, Juliana Freire Enhancing Language Model Calibration to Human Responses in Ethical Ambiguity via Fine-Tuning
Pranav Senthilkumar, Visshwa Balasubramanian, Prisha Jain, Aneesa Maity, Jonathan Lu, Kevin Zhu Enhancing Medical VQA with Multimodal Determination Rationales
Xiaotang Gai, Chenyi Zhou, Jiaxiang Liu, Yang Feng, Jian Wu, Zuozhu Liu Enhancing Table Representations with LLM-Powered Synthetic Data Generation
Dayu Yang, Natawut Monaikul, Amanda Ding, Bozhao Tan, Kishore Mosaliganti, Giri Iyengar Ensemble Mashups: A Simple Recipe for Better Bayesian Optimization
Anand Ravishankar, Fernando Llorente, Yuanqing Song, Petar Djuric Ensembling Finetuned Language Models for Text Classification
Sebastian Pineda Arango, Maciej Janowski, Lennart Purucker, Arber Zela, Frank Hutter, Josif Grabocka EnsemW2S: Can an Ensemble of LLMs Be Leveraged to Obtain a Stronger LLM?
Aakriti Agrawal, Mucong Ding, Zora Che, Chenghao Deng, Anirudh Satheesh, John Langford, Furong Huang EnzymeFlow: Generating Reaction-Specific Enzyme Catalytic Pockets Through Flow Matching and Co-Evolutionary Dynamics
Chenqing Hua, Yong Liu, Dinghuai Zhang, Odin Zhang, Sitao Luan, Kevin K Yang, Guy Wolf, Doina Precup, Shuangjia Zheng Episodic Novelty Through Temporal Distance
Yuhua Jiang, Qihan Liu, Yiqin Yang, Xiaoteng Ma, Dianyu Zhong, Bo Xu, Jun Yang, Bin Liang, Chongjie Zhang, Qianchuan Zhao Epistemic Integrity in Large Language Models
Bijean Ghafouri, Shahrad Mohammadzadeh, James Zhou, Pratheeksha Nair, Jacob-Junqi Tian, Mayank Goel, Reihaneh Rabbany, Jean-François Godbout, Kellin Pelrine EqNIO: Subequivariant Neural Inertial Odometry
Royina Karegoudra Jayanth, Yinshuang Xu, Daniel Gehrig, Ziyun Wang, Evangelos Chatzipantazis, Kostas Daniilidis Equitable Access to Justice: Logical LLMs Show Promise
Manuj Kant, Marzieh Nabi, Manav Kant, Preston Carlson, Megan Ma Estimating Effects of Tokens in Preference Learning
Hsiao-Ru Pan, Maximilian Mordig, Bernhard Schölkopf Estimating Effects of Tokens in Preference Learning
Hsiao-Ru Pan, Maximilian Mordig, Bernhard Schölkopf Evaluating Chemistry Prompts for Large-Language Model Fine-Tuning
Carmelo Gonzales, Michael Martin Pieler, Kevin Maik Jablonka, Santiago Miret Evaluating Explanations Through LLMs: Beyond Traditional User Studies
Francesco Bombassei De Bona, Gabriele Dominici, Tim Miller, Marc Langheinrich, Martin Gjoreski Evaluating Interventional Reasoning Capabilities of Large Language Models
Tejas Kasetty, Divyat Mahajan, Gintare Karolina Dziugaite, Alexandre Drouin, Dhanya Sridhar Evaluating Loss Landscapes from a Topology Perspective
Tiankai Xie, Caleb Geniesse, Jiaqing Chen, Yaoqing Yang, Dmitriy Morozov, Michael W. Mahoney, Ross Maciejewski, Gunther H. Weber Evaluating Synergies Among Generative Design Models for Multi-Objective Optimization of Drug-like Proteins
Jung-Eun Shin, Nathan J Rollins, Jordan M Anderson, Grace Carey, Allison Colthart, Thomas Hopf, Ivan Mascanfroni, Jyothsna Visweswaraiah, Yi Xing, Kevin L. Otipoby, Nathan Higginson-Scott, Ryan Peckner Evaluating the Prompt Steerability of Large Language Models
Erik Miehling, Michael Desmond, Karthikeyan Natesan Ramamurthy, Elizabeth M. Daly, Pierre Dognin, Jesus Rios, Djallel Bouneffouf, Miao Liu Event-Based Backpropagation on the Neuromorphic Platform SpiNNaker2
Gabriel Béna, Timo Wunderlich, Mahmoud Akl, Bernhard Vogginger, Christian Mayr, Hector Andres Gonzalez Evolving Alignment via Asymmetric Self-Play
Ziyu Ye, Rishabh Agarwal, Tianqi Liu, Rishabh Joshi, Sarmishta Velury, Quoc V Le, Qijun Tan, Yuan Liu Examining Data Compartmentalization for AI Governance
Nicole Elyse Mitchell, Eleni Triantafillou, Peter Kairouz EXAQ: Exponent Aware Quantization for LLMs Acceleration
Moran Shkolnik, Maxim Fishman, Brian Chmiel, Hilla Ben-Yaacov, Ron Banner, Kfir Yehuda Levy Explainable AI-Based Analysis of Human Pancreas Sections Detects Traits of Type 2 Diabetes
Lukas Klein, Sebastian Ziegler, Felicia Gerst, Yanni Morgenroth, Karol Gotkowski, Eyke Schöniger, Nicole Kipke, Annika Seiler, Ellen Geibelt, Martin Heni, Silvia Wagner, Silvio Nadalin, Falko Fend, Daniela Aust, Andre Mihaljevic, Daniel Hartmann, Jurgen Weitz, Reiner Jumpertz-von Schwartzenberg, Marius Distler, Andreas Birkefeld, Susanne Ullrich, Paul F Jaeger, Fabian Isensee, Michele Solimena, Robert Wagner Explainable, Generalizable and Responsible AI Model to Triage Emergency Patients
Jemal A Fulli, Berihun T Alemayehu, Omer K Yasin, Abubeker S Ahmed, Muhammed A Sualih Explicit Regularisation, Sharpness and Calibration
Israel Mason-Williams, Fredrik Ekholm, Ferenc Huszár Exploring Fairness in Long-Term Prediction of Type 2 Diabetes Microvascular Complications
Elizabeth Remfry, Rafael Henkin, Zainab Awan, Rohini Mathur, Michael R Barnes, Aakanksha Naik Exploring Intrinsic Fairness in Stable Diffusion
Eunji Kim, Siwon Kim, Robin Rombach, Rahim Entezari, Sungroh Yoon Exploring the Limits of Feature Learning in Continual Learning
Jacopo Graldi, Giulia Lanzillotta, Lorenzo Noci, Benjamin F Grewe, Thomas Hofmann ExpressivityArena: Can LLMs Express Information Implicitly?
Joshua Tint, Som Sagar, Aditya Taparia, Caleb Liu, Kelly Raines, Bimsara Pathiraja, Ransalu Senanayake Extracting Paragraphs from LLM Token Activations
Nicky Pochinkov, Angelo Benoit, Lovkush Agarwal, Zainab Ali Majid, Lucile Ter-Minassian Extracting Parallelism from Large Language Model Queries
Steven Kolawole, Keshav Santhanam, Virginia Smith, Pratiksha Thaker Extracting Unlearned Information from LLMs with Activation Steering
Atakan Seyitoğlu, Aleksei Kuvshinov, Leo Schwinn, Stephan Günnemann Failure Prediction from Few Expert Demonstrations
Anjali Parashar, Kunal Garg, Joseph Zhang, Chuchu Fan Failures to Find Transferable Image Jailbreaks Between Vision-Language Models
Rylan Schaeffer, Dan Valentine, Luke Bailey, James Chua, Zane Durante, Cristobal Eyzaguirre, Joe Benton, Brando Miranda, Henry Sleight, Tony Tong Wang, John Hughes, Rajashree Agrawal, Mrinank Sharma, Scott Emmons, Sanmi Koyejo, Ethan Perez Failures to Find Transferable Image Jailbreaks Between Vision-Language Models
Rylan Schaeffer, Dan Valentine, Luke Bailey, James Chua, Zane Durante, Cristobal Eyzaguirre, Joe Benton, Brando Miranda, Henry Sleight, Tony Tong Wang, John Hughes, Rajashree Agrawal, Mrinank Sharma, Scott Emmons, Sanmi Koyejo, Ethan Perez Fairness of AI Models in Vector Embedded Chest X-Ray Representations
Gebreyowhans Hailekiros Bahre, Hassan Hamidi, Francesco Calimeri, Andrew Sellergren, Leo Anthony Celi, Laleh Seyyed-Kalantari Fast Convergence of SoftMax Policy Mirror Ascent for Bandits & Tabular MDPs
Reza Asad, Reza Babanezhad Harikandeh, Issam H. Laradji, Nicolas Le Roux, Sharan Vaswani Faster Slot Decoding Using Masked Transformer
Akihiro Nakano, Masahiro Suzuki, Yutaka Matsuo Faster, More Efficient RLHF Through Off-Policy Asynchronous Learning
Michael Noukhovitch, Shengyi Huang, Sophie Xhonneux, Arian Hosseini, Rishabh Agarwal, Aaron Courville FC-Aligner: A Lightweight Regressor Model for Embedding Space Conversion
André Luiz Buarque Vieira e Silva, René G. Ferrari, Álvaro Spies Nolibos, Gustavo Zanoni Felipe FEABench: Evaluating Language Models on Real World Physics Reasoning Ability
Nayantara Mudur, Hao Cui, Subhashini Venugopalan, Paul Raccuglia, Michael Brenner, Peter Christian Norgaard FEABench: Evaluating Language Models on Real World Physics Reasoning Ability
Nayantara Mudur, Hao Cui, Subhashini Venugopalan, Paul Raccuglia, Michael Brenner, Peter Christian Norgaard Federated GNNs for EEG-Based Stroke Assessment
Andrea Protani, Lorenzo Giusti, Albert Sund Aillet, Simona Sacco, Paolo Manganotti, Lucio Marinelli, Diogo Reis Santos, Pierpaolo Brutti, Pietro Caliandro, Luigi Serio Federated Learning with Generative Content
Rui Ye, Xinyu Zhu, Jingyi Chai, Lingjuan Lyu, Chen Xie, Yanfeng Wang, Siheng Chen Federated Learning with Quantum Computing and Fully Homomorphic Encryption: A Novel Computing Paradigm Shift in Privacy-Preserving ML
Siddhant Dutta, Pavana P Karanth, Pedro Maciel Xavier, Iago Leal de Freitas, Nouhaila Innan, Sadok Ben Ben Yahia, Muhammad Shafique, David E. Bernal Neira Fine-Grained Visual Recognition in the Age of Multimodal LLMs
Hari Chandana Kuchibhotla, Abbavaram Gowtham Reddy, Sai Srinivas Kancheti, Vineeth N. Balasubramanian Fine-Tuning Discrete Diffusion Models via Reward Optimization with Applications to DNA and Protein Design
Chenyu Wang, Masatoshi Uehara, Yichun He, Amy Wang, Tommaso Biancalani, Avantika Lal, Tommi Jaakkola, Sergey Levine, Hanchen, Aviv Regev Fine-Tuning LLM Agents with Retrospective In-Context Online Learning
Wentse Chen, Jiayu Chen, Fahim Tajwar, Hao Zhu, Xintong Duan, Russ Salakhutdinov, Jeff Schneider Fine-Tuning Vision Classifiers on a Budget
Sunil Kumar, Ted Sandler, Paulina Varshavskaya Fine-Tuning Web Agents: It Works, but It's Trickier than You Think
Massimo Caccia, Megh Thakkar, Léo Boisvert, Thibault Le Sellier de Chezelles, Alexandre Piché, Nicolas Chapados, Alexandre Drouin, Maxime Gasse, Alexandre Lacoste FinerCut: Finer-Grained Interpretable Layer Pruning for Large Language Models
Yang Zhang, Yawei Li, Xinpeng Wang, Qianli Shen, Barbara Plank, Bernd Bischl, Mina Rezaei, Kenji Kawaguchi Fitness Aware Human Motion Generation with Fine-Tuning
Kiril Bikov, Shiye Su, Deepro Choudhury, Zhilin Guo, Weihao Xia, Mehmet Salih Çeliktenyıldız, Chenliang Zhou, Param Hanji, Cengiz Oztireli Flat-LoRA: Low-Rank Adaption over a Flat Loss Landscape
Tao Li, Zhengbao He, Yujun Li, Yasheng Wang, Lifeng Shang, Xiaolin Huang Flexible Image Decoding in Learned Image Compression
Hossein Motamednia, Azadeh Mansouri, Fariba Saadati Monem, Ahmad Mahmoudi-Aznaveh FlickerFusion: Intra-Trajectory Domain Generalizing Multi-Agent RL
Woosung Koh, Wonbeen Oh, Siyeol Kim, Suhin Shin, Hyeongjin Kim, Jaein Jang, Junghyun Lee, Se-Young Yun Force-Controlled Robotic Mechanochemical Synthesis
YusakuNakajima, Kai Kawasaki, Yasuo Takeichi, Masashi Hamaya, Yoshitaka Ushiku, Kanta Ono Formal Representation and Solution of Plane Geometric Problems
Xiaokai Zhang, Na Zhu, Cheng Qin, Yang Li, Zhenbing Zeng, Tuo Leng Formalizing Limits of Knowledge Distillation Using Partial Information Decomposition
Pasan Dissanayake, Faisal Hamman, Barproda Halder, Ilia Sucholutsky, Qiuyi Zhang, Sanghamitra Dutta Foundation Models and the EU AI Act
Rishi Bommasani, Alice Hau, Kevin Klyman, Percy Liang FPGA-Gym: An FPGA-Accelerated Reinforcement Learning Environment Simulation Framework
Jiayi Li, Hongxiao Zhao, Wenshuo Yue, Yihan Fu, Daijing Shi, Anjunyi Fan, Qinghao Wang, Yaodong Yang, Bonan Yan FRACTAL: Fine-Grained Scoring from Aggregate Text Labels
Yukti Makhija, Priyanka Agrawal, Rishi Saket, Aravindan Raghuveer From Causal to Concept-Based Representation Learning
Goutham Rajendran, Simon Buchholz, Bryon Aragam, Bernhard Schölkopf, Pradeep Kumar Ravikumar From Lazy to Rich: Exact Learning Dynamics in Deep Linear Networks
Clémentine Carla Juliette Dominé, Nicolas Anguita, Alexandra Maria Proca, Lukas Braun, Daniel Kunin, Pedro A. M. Mediano, Andrew M Saxe From Lazy to Rich: Exact Learning Dynamics in Deep Linear Networks
Clémentine Carla Juliette Dominé, Nicolas Anguita, Alexandra Maria Proca, Lukas Braun, Daniel Kunin, Pedro A. M. Mediano, Andrew M Saxe From One to Zero: RAG-IM Adapts Language Models for Interpretable Zero-Shot Clinical Predictions
Sazan Mahbub, Caleb Ellington, Sina Alinejad, Kevin Wen, Yingtao Luo, Ben Lengerich, Eric P. Xing From Text to Emoji: How PEFT-Driven Personality Manipulation Unleashes the Emoji Potential in LLMs
Navya Jain, Zekun Wu, Cristian Enrique Munoz Villalobos, Airlie Hilliard, Adriano Koshiyama, Emre Kazim, Philip Colin Treleaven From Text to Pose to Image: Improving Diffusion Model Control and Quality
Clément Bonnet, Ariel N. Lee, Franck Wertel, Antoine Tamano, Tanguy Cizain, Pablo Ducru FSD: Acoustic Echo Cancellation with Fewer Step Diffusion
Yang Liu, Li Wan, Yiteng Huang, Ming Sun, Changsheng Zhao, Zhaoheng Ni, Xinhao Mei, Yangyang Shi, Florian Metze Fully-Inductive Node Classification on Arbitrary Graphs
Jianan Zhao, Mikhail Galkin, Hesham Mostafa, Michael M. Bronstein, Zhaocheng Zhu, Jian Tang FV-NeRV: Neural Compression for Free Viewpoint Videos
Takuya Fujihashi, Sorachi Kato, Toshiaki Koike-Akino G-RAG: Knowledge Expansion in Material Science
Radeen Mostafa, Mirza Nihal Baig, Mashaekh Tausif Ehsan, Jakir Hasan Galois Features: Nearly-Complete Invariants on Symmetric Matrices
Ben Blum-Smith, Ningyuan Teresa Huang, Marco Cuturi, Soledad Villar GaLore-Mini: Low Rank Gradient Learning with Fewer Learning Rates
Weihao Huang, Zhenyu Zhang, Yushun Zhang, Zhi-Quan Luo, Ruoyu Sun, Zhangyang Wang GameBench: Evaluating Strategic Reasoning Abilities of LLM Agents
Anthony Costarelli, Mat Allen, Roman Hauksson, Grace Sodunke, Suhas Hariharan, Carlson Cheng, Wenjie Li, Joshua M Clymer, Arjun Yadav GAMformer: Exploring In-Context Learning for Generalized Additive Models
Andreas C Mueller, Julien Siems, Harsha Nori, David Salinas, Arber Zela, Rich Caruana, Frank Hutter GAMformer: Exploring In-Context Learning for Generalized Additive Models
Andreas C Mueller, Julien Siems, Harsha Nori, Rich Caruana, Frank Hutter Gaze-Assisted Medical Image Segmentation
Leila Khaertdinova, Ilya Pershin, Tatyana Shmykova, Bulat Ibragimov GenAudit: Fixing Factual Errors in Language Model Outputs with Evidence
Kundan Krishna, Sanjana Ramprasad, Prakhar Gupta, Byron C Wallace, Zachary Chase Lipton, Jeffrey P. Bigham Gender Bias in LLM-Generated Interview Responses
Haein Kong, Yongsu Ahn, Sangyub Lee, Yunho Maeng GeneGench: Systematic Evaluation of Genomic Foundation Models and Beyond
Zicheng Liu, Jiahui Li, Lei Xin, Siyuan Li, Chang Yu, Zelin Zang, Cheng Tan, Yufei Huang, Yajingbai, Jun Xia, Stan Z. Li General Causal Imputation via Synthetic Interventions
Marco Jiralerspong, Thomas Jiralerspong, Vedant Shah, Dhanya Sridhar, Gauthier Gidel General-Purpose Brain Foundation Models for Time-Series Neuroimaging Data
Mohammad Javad Darvishi Bayazi, Hena Ghonia, Roland Riachi, Bruno Aristimunha, Arian Khorasani, Md Rifat Arefin, Amin Darabi, Guillaume Dumas, Irina Rish Generalization vs Specialization Under Concept Shift
Alex Nguyen, David J. Schwab, Vudtiwat Ngampruetikorn Generalized Flow Matching for Transition Dynamics Modeling
Haibo Wang, Yuxuan Qiu, Yanze Wang, Rob Brekelmans, Yuanqi Du Generalized Open-World Semi-Supervised Object Detection
Garvita Allabadi, Ana Lucic, Siddarth Aananth, Tiffany Yang, Yu-Xiong Wang, Vikram S. Adve Generating Vocals from Lyrics and Musical Accompaniment
Georg Streich, Luca A Lanzendörfer, Florian Grötschla, Roger Wattenhofer Generative Adapter: Contextualizing Language Models in Parameters with a Single Forward Pass
Tong Chen, Hao Fang, Patrick Xia, Xiaodong Liu, Benjamin Van Durme, Luke Zettlemoyer, Jianfeng Gao, Hao Cheng Generative AI in the Hospital: A Participatory Assessment of Healthcare Needs and Challenges
Giorgia Carra, Bogdan Kulynych, François Bastardot, Noémie Boillat-Blanco, Jean Louis Raisaro Generative Flows on Synthetic Pathway for Drug Design
Seonghwan Seo, Minsu Kim, Tony Shen, Martin Ester, Jinkyoo Park, Sungsoo Ahn, Woo Youn Kim Generative Model for Synthesizing Ionizable Lipids: A Monte Carlo Tree Search Approach
Jingyi Zhao, Yuxuan Ou, Austin Tripp, Morteza Rasoulianboroujeni, José Miguel Hernández-Lobato Generative Models in Protein Engineering: A Comprehensive Survey
Chen Xinhui, Yiwen Yuan, Joseph Liu, Chak Tou Leong, Xiaoye Zhu, Jiaqi Chen Generative Timelines for Instructed Visual Assembly
Alejandro Pardo, Jui-Hsien Wang, Bernard Ghanem, Josef Sivic, Bryan Russell, Fabian Caba Heilbron Generative Verifiers: Reward Modeling as Next-Token Prediction
Lunjun Zhang, Arian Hosseini, Hritik Bansal, Mehran Kazemi, Aviral Kumar, Rishabh Agarwal Generative Verifiers: Reward Modeling as Next-Token Prediction
Lunjun Zhang, Arian Hosseini, Hritik Bansal, Mehran Kazemi, Aviral Kumar, Rishabh Agarwal Getting Free Bits Back from Rotational Symmetries in LLMs
Jiajun He, Gergely Flamich, José Miguel Hernández-Lobato GFlowNet Pretraining with Inexpensive Rewards
Mohit Pandey, Gopeshh Subbaraj, Emmanuel Bengio GFlowNet Pretraining with Inexpensive Rewards
Mohit Pandey, Gopeshh Subbaraj, Emmanuel Bengio GIFT-Eval: A Benchmark for General Time Series Forecasting Model Evaluation
Taha Aksu, Gerald Woo, Juncheng Liu, Xu Liu, Chenghao Liu, Silvio Savarese, Caiming Xiong, Doyen Sahoo Give Me a Hint: Can LLMs Take a Hint to Solve Math Problems?
Vansh Agrawal, Pratham Singla, Amitoj Singh Miglani, Shivank Garg, Ayush Mangal GLEAM-AI: Neural Surrogate for Accelerated Epidemic Analytics and Forecasting
Mohammadmehdi Zahedi, Dongxia Wu, Jessica T. Davis, Yian Ma, Alessandro Vespignani, Rose Yu, Matteo Chinazzi GLEAM-AI: Neural Surrogate for Accelerated Epidemic Analytics and Forecasting
Mohammadmehdi Zahedi, Dongxia Wu, Jessica T. Davis, Yian Ma, Alessandro Vespignani, Rose Yu, Matteo Chinazzi Gradient of Clifford Neural Networks
Takashi Maruyama, Francesco Alesiani Gradient-Free Variational Learning with Conditional Mixture Networks
Conor Heins, Hao Wu, Dimitrije Markovic, Alexander Tschantz, Jeff Beck, Christopher Buckley Graph Agnostic Causal Bayesian Optimisation
Sumantrak Mukherjee, Mengyan Zhang, Seth Flaxman, Sebastian Josef Vollmer Graph Classification Gaussian Processes via Hodgelet Spectral Features
Mathieu Alain, So Takao, Bastian Rieck, Xiaowen Dong, Emmanuel Noutahi GraphText: Graph Reasoning in Text Space
Jianan Zhao, Le Zhuo, Yikang Shen, Meng Qu, Kai Liu, Michael M. Bronstein, Zhaocheng Zhu, Jian Tang Grid Cell-Inspired Fragmentation and Recall for Efficient mAP Building
Jaedong Hwang, Zhang-Wei Hong, Eric R Chen, Akhilan Boopathy, Pulkit Agrawal, Ila R Fiete Group Robust Best-of-K Decoding of Language Models for Pluralistic Alignment
Sangwoong Yoon, William Bankes, Seongho Son, Anja Petrovic, Shyam Sundhar Ramesh, Xiaohang Tang, Ilija Bogunovic GTA: A Benchmark for General Tool Agents
Jize Wang, Ma Zerun, Yining Li, Songyang Zhang, Cailian Chen, Kai Chen, Xinyi Le GuardFormer: Guardrail Instruction Pretraining for Efficient SafeGuarding
James O' Neill, Santhosh Subramanian, Eric Lin, Abishek Satish, Vaikkunth Mugunthan GUI-WORLD: A GUI-Oriented Video Dataset for Multimodal LLM-Based Agents
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Yue Lu, Mary Letey, Jacob A Zavatone-Veth, Anindita Maiti, Cengiz Pehlevan Inconsistencies in Consistency Models: Better ODE Solving Does Not Imply Better Samples
Noël Vouitsis, Rasa Hosseinzadeh, Brendan Leigh Ross, Valentin Villecroze, Satya Krishna Gorti, Jesse C. Cresswell, Gabriel Loaiza-Ganem Incorporating Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models
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Austin Meek, Artem Karpov, Seong Hah Cho, Raymond Koopmanschap, Lucy Farnik, Bogdan-Ionut Cirstea Infecting LLM Agents via Generalizable Adversarial Attack
Weichen Yu, Kai Hu, Tianyu Pang, Chao Du, Min Lin, Matt Fredrikson InfiMM-WebMath-40b: Advancing Multimodal Pre-Training for Enhanced Mathematical Reasoning
Xiaotian Han, Yiren Jian, Xuefeng Hu, Haogeng Liu, Yiqi Wang, Qihang Fan, Yuang Ai, Huaibo Huang, Ran He, Zhenheng Yang, Quanzeng You Influence Estimation in Self-Supervised Learning
Nidhin Harilal, Reza Akbarian Bafghi, Amit Kiran Rege, Maziar Raissi, Claire Monteleoni Infogent: An Agent-Based Framework for Web Information Aggregation
Revanth Gangi Reddy, Sagnik Mukherjee, Jeonghwan Kim, Zhenhailong Wang, Dilek Hakkani Tur, Heng Ji Informed Tree of Thought: Cost-Efficient Problem Solving with Large Language Models
Sajad Mousavi, Desik Rengarajan, Ashwin Ramesh Babu, Sahand Ghorbanpour, Vineet Gundecha, Avisek Naug, Soumyendu Sarkar Insights on Disagreement Patterns in Multimodal Safety Perception Across Diverse Rater Groups
Charvi Rastogi, Tian Huey Teh, Pushkar Mishra, Roma Patel, Zoe Ashwood, Aida Mostafazadeh Davani, Mark Diaz, Michela Paganini, Alicia Parrish, Ding Wang, Vinodkumar Prabhakaran, Lora Aroyo, Verena Rieser Instant Transformer Adaption via HyperLoRA
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Jack Brady, Julius von Kügelgen, Sebastien Lachapelle, Simon Buchholz, Wieland Brendel Interactive Semantic Interventions for VLMs: A Causality-Inspired Investigation of VLM Failures
Lukas Klein, Kenza Amara, Carsten T. Lüth, Hendrik Strobelt, Mennatallah El-Assady, Paul F Jaeger Interactive Semantic Interventions for VLMs: A Human-in-the-Loop Approach to Interpretability
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Jesus de la Fuente Cedeño, Robert Lehmann, Carlos Ruiz-Arenas, Irene Marín-Goñi, Jan Voges, Xabier Martinez de Morentin, David Gomez-Cabrero, Idoia Ochoa, Jesper Tegnér, Vincenzo Lagani, Mikel Hernaez Interpretable Concept Bottlenecks to Align Reinforcement Learning Agents
Quentin Delfosse, Sebastian Sztwiertnia, Mark Rothermel, Wolfgang Stammer, Kristian Kersting Invariant Learning with Annotation-Free Environments
Phuong Quynh Le, Christin Seifert, Jörg Schlötterer Inverse Attention Agent in Multi-Agent System
Qian Long, Ruoyan Li, Minglu Zhao, Tao Gao, Demetri Terzopoulos Inverse-Free Sparse Variational Gaussian Processes
Stefano Cortinovis, Laurence Aitchison, James Hensman, Stefanos Eleftheriadis, Mark van der Wilk InvestAlign: Align LLMs with Investor Decision-Making Under Herd Behavior
Huisheng Wang, Zhuoshi Pan, Hangjing Zhang, Mingxiao Liu, Yiqing Lin, H. Vicky Zhao Investigating Annotator Bias in Large Language Models for Hate Speech Detection
Amit Das, Zheng Zhang, Najib Hasan, Souvika Sarkar, Fatemeh Jamshidi, Tathagata Bhattacharya, Mostafa Rahgouy, Nilanjana Raychawdhary, Dongji Feng, Vinija Jain, Aman Chadha, Mary Sandage, Lauramarie Pope, Gerry Dozier, Cheryl Seals Investigating Causal Reasoning in Large Language Models
Atul Rawal, Adrienne Raglin, Qianlong Wang, Ziying Tang Investigating the Role of Modality and Training Objective on Representational Alignment Between Transformers and the Brain
Hyewon Willow Han, Ruchira Dhar, Qingqing Yang, Maryam Hoseini Behbahani, María Alejandra Martínez Ortiz, Tolulope Samuel Oladele, Diana C Dima, Hsin-Hung Li, Anders Søgaard, Yalda Mohsenzadeh Is Free Self-Alignment Possible?
Dyah Adila, Changho Shin, Yijing Zhang, Frederic Sala Is In-Context Learning Sufficient for Instruction Following in LLMs?
Hao Zhao, Maksym Andriushchenko, Francesco Croce, Nicolas Flammarion Is Network Fragmentation a Useful Complexity Measure?
Coenraad Mouton, Randle Rabe, Daniël Gerbrand Haasbroek, Marthinus Wilhelmus Theunissen, Hermanus Lambertus Potgieter, Marelie Hattingh Davel Is Saliency Really Captured by Gradient?
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Matthew Leigh, Samuel Klein, Francois Charton, Tobias Golling, Lukas Heinrich, Michael Kagan, Margarita Osadchy Is What You Ask for What You Get? Investigating Concept Associations in Text-to-Image Models
Salma Abdel Magid, Weiwei Pan, Simon Warchol, Grace Guo, Junsik Kim, Wanhua Li, Mahia Rahman, Hanspeter Pfister Isometry Pursuit
Samson J Koelle, Marina Meila Jailbreak Defense in a Narrow Domain: Failures of Existing Methods and Improving Transcript-Based Classifiers
Tony Tong Wang, John Hughes, Henry Sleight, Rylan Schaeffer, Rajashree Agrawal, Fazl Barez, Mrinank Sharma, Jesse Mu, Nir N Shavit, Ethan Perez Jailbreak Defense in a Narrow Domain: Failures of Existing Methods and Improving Transcript-Based Classifiers
Tony Tong Wang, John Hughes, Henry Sleight, Rylan Schaeffer, Rajashree Agrawal, Fazl Barez, Mrinank Sharma, Jesse Mu, Nir N Shavit, Ethan Perez Jailbreaking Large Language Models with Symbolic Mathematics
Emet Bethany, Mazal Bethany, Juan A. Nolazco-Flores, Sumit Kumar Jha, Peyman Najafirad Joint Embedding Go Temporal
Sofiane Ennadir, Siavash Golkar, Leopoldo Sarra Justice or Prejudice? Quantifying Biases in LLM-as-a-Judge
Jiayi Ye, Yanbo Wang, Yue Huang, Dongping Chen, Qihui Zhang, Nuno Moniz, Tian Gao, Werner Geyer, Chao Huang, Pin-Yu Chen, Nitesh V Chawla, Xiangliang Zhang Klein Model for Hyperbolic Neural Networks
Yidan Mao, Jing Gu, Marcus C. Werner, Dongmian Zou Knowledge Distillation for Teaching Symmetry Invariances
Patrick Odagiu, Nicole Nobili, Fabian Dionys Schrag, Yves Bicker, Yuhui Ding Knowledge Distillation for Teaching Symmetry Invariances
Patrick Odagiu, Nicole Nobili, Fabian Dionys Schrag, Yves Bicker, Yuhui Ding Knowledge Distillation: The Functional Perspective
Israel Mason-Williams, Gabryel Mason-Williams, Mark Sandler Known Unknowns: Out-of-Distribution Property Prediction in Materials and Molecules
Nofit Segal, Aviv Netanyahu, Kevin P. Greenman, Pulkit Agrawal, Rafael Gomez-Bombarelli Label Noise: Ignorance Is Bliss
Yilun Zhu, Jianxin Zhang, Aditya Gangrade, Clayton Scott LangDA: Language-Guided Domain Adaptive Semantic Segmentation
Chang Liu, Saad Hossain, C Thomas, Kwei-Herng Lai, Raviteja Vemulapalli, Sirisha Rambhatla, Alexander Wong Language Model Scaling Laws and Zero-Sum Learning
Andrei Mircea, Ekaterina Lobacheva, Supriyo Chakraborty, Nima Chitsazan, Irina Rish Language Models Can Articulate Their Implicit Goals
Jan Betley, Xuchan Bao, Martín Soto, Anna Sztyber-Betley, James Chua, Owain Evans Language Models for Text-Guided Protein Evolution
Zhanghan Ni, Shengchao Liu, Hongyu Guo, Anima Anandkumar Language Models Resist Alignment
Jiaming Ji, Kaile Wang, Tianyi Qiu, Boyuan Chen, Changye Li, Hantao Lou, Jiayi Zhou, Josef Dai, Yaodong Yang Language Repository for Long Video Understanding
Kumara Kahatapitiya, Kanchana Ranasinghe, Jongwoo Park, Michael S Ryoo Large Language Model Benchmarks Do Not Test Reliability
Joshua Vendrow, Edward Vendrow, Sara Beery, Aleksander Madry Large Language Model Compression with Neural Architecture Search
Rhea Sanjay Sukthanker, Benedikt Staffler, Frank Hutter, Aaron Klein Large Language Models Still Exhibit Bias in Long Text
Wonje Jeung, Dongjae Jeon, Ashkan Yousefpour, Jonghyun Choi Latent Adversarial Training Improves Robustness to Persistent Harmful Behaviors in LLMs
Aidan Ewart, Abhay Sheshadri, Phillip Huang Guo, Aengus Lynch, Cindy Wu, Vivek Hebbar, Henry Sleight, Asa Cooper Stickland, Ethan Perez, Dylan Hadfield-Menell, Stephen Casper Latent Concept-Based Explanation of NLP Models
Xuemin Yu, Fahim Dalvi, Nadir Durrani, Marzia Nouri, Hassan Sajjad Latent Concept-Based Explanation of NLP Models
Xuemin Yu, Fahim Dalvi, Nadir Durrani, Marzia Nouri, Hassan Sajjad Latent Diffusion Models for Controllable RNA Sequence Generation
Kaixuan Huang, Yukang Yang, Kaidi Fu, Yanyi Chu, Le Cong, Mengdi Wang Latent Spatial Dirichlet Allocation
Junsouk Choi, Veerabhadran Baladandayuthapani, Jian Kang Layer-Wise Quantization for Distributed Variational Inequalities
Anh Duc Nguyen, Ilia Markov, Ali Ramezani-Kebrya, Kimon Antonakopoulos, Dan Alistarh, Volkan Cevher Learning Biologically Relevant Features in a Pathology Foundation Model Using Sparse Autoencoders
Nhat Minh Le, Neel Patel, Ciyue Shen, Blake Martin, Alfred Eng, Chintan Shah, Sean Grullon, Dinkar Juyal Learning Diverse Attacks on Large Language Models for Robust Red-Teaming and Safety Tuning
Seanie Lee, Minsu Kim, Lynn Cherif, David Dobre, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Moksh Jain Learning from Personal Preferences
Kelly Jiang, Berk Ustun, Jessica Hullman Learning Mathematical Rules with Large Language Models
Antoine Gorceix, Bastien Le Chenadec, Ahmad Rammal, Nelson Vadori, Manuela Veloso Learning Molecular Representation in a Cell
Gang Liu, Srijit Seal, John Arevalo, Zhenwen Liang, Anne E Carpenter, Meng Jiang, Shantanu Singh Learning Multi-Cellular Representations of Single-Cell Transcriptomics Data Enables Characterization of Patient-Level Disease States
Tianyu Liu, Edward De Brouwer, Tony Kuo, Nathaniel Lee Diamant, Missarova Alsu, Minsheng Hao, Hanchen, Hector Corrada Bravo, Gabriele Scalia, Aviv Regev, Graham Heimberg Learning Precise, Contact-Rich Manipulation Through Uncalibrated Tactile Skins
Venkatesh Pattabiraman, Yifeng Cao, Siddhant Haldar, Lerrel Pinto, Raunaq Bhirangi Learning Reward and Policy Jointly from Demonstration and Preference Improves Alignment
Chenliang Li, Siliang Zeng, Zeyi Liao, Jiaxiang Li, Dongyeop Kang, Alfredo Garcia, Mingyi Hong Learning Stochastic Rainbow Networks
Vivian White, Muawiz Sajjad Chaudhary, Guy Wolf, Guillaume Lajoie, Kameron Decker Harris Learning Symmetric Contexts for Anomaly Detection
Alain Ryser, Thomas M. Sutter, Alexander Marx, Julia E Vogt Learning Temperature-Aware Representations from Millions of Annotated Protein Sequences
Mingchen Li, Liang Zhang, Zilan Wang, Bozitao Zhong, Pan Tan, Jiabei Cheng, Bingxin Zhou, Liang Hong, Huiqun Yu Learning to Cooperate with Humans Using Generative Agents
Yancheng Liang, Daphne Chen, Abhishek Gupta, Simon Shaolei Du, Natasha Jaques Learning to Forget Using Hypernetworks
Jose Miguel Lara Rangel, Usman Anwar, Stefan Schoepf, Jack Foster, David Krueger Learning via Imagination: Controlled Diffusion Image Augmentation
Judah A Goldfeder, Patrick Minwan Puma, Gabriel Guo, Gabriel Guerra Trigo, Hod Lipson LEMoN: Label Error Detection Using Multimodal Neighbors
Haoran Zhang, Aparna Balagopalan, Nassim Oufattole, Hyewon Jeong, Yan Wu, Jiacheng Zhu, Marzyeh Ghassemi Lessons from Red Teaming 100 Generative AI Products
Blake Bullwinkel, Amanda J. Minnich, Shiven Chawla, Gary David Lopez Munoz, Martin Pouliot, Whitney Maxwell, Joris de Gruyter, Katherine Pratt, Saphir Qi, Nina Chikanov, Roman Lutz, Raja Sekhar Rao Dheekonda, Bolor-Erdene Jagdagdorj, Rich Lundeen, Sam Vaughan, Victoria Westerhoff, Pete Bryan, Ram Shankar Siva Kumar, Yonatan Zunger, Mark Russinovich Levels of Autonomy: Liability in the Age of AI Agents
Lisa Soder, Julia Smakman, Connor Dunlop, Weiwei Pan, Siddharth Swaroop, Noam Kolt Leveraging Foundation Models for Data-Limited Ecological Applications
Kyle Doherty, Max A Gurinas, Erik Samsoe, Charles Casper, Beau G Larkin, Philip W. Ramsey, Brandon Trabucco, Russ Salakhutdinov Leveraging Periodicity for Robustness with Multi-Modal Mood Pattern Models
Jaya Narain, Qinhua Jenny Sun, Oussama Elachqar, Haraldur T Hallgrimsson, Feng Zhu, Shirley You Ren Lexically-Constrained Automated Prompt Augmentation: A Case Study Using Adversarial T2I Data
Jessica Quaye, Alicia Parrish, Oana Inel, Minsuk Kahng, Charvi Rastogi, Hannah Rose Kirk, Jess Tsang, Nathan L Clement, Rafael Mosquera, Juan Manuel Ciro, Vijay Janapa Reddi, Lora Aroyo Lie-Equivariant Quantum Graph Neural Networks
Jogi Suda Neto, Roy Thomas Forestano, Sergei Gleyzer, Kyoungchul Kong, Konstantin Matchev, Katia Matcheva Lightweight Correlation-Aware Table Compression
Mihail Stoian, Alexander van Renen, Jan Kobiolka, Ping-Lin Kuo, Josif Grabocka, Andreas Kipf Lightweight Neural App Control
Filippos Christianos, Georgios Papoudakis, Thomas Coste, Jianye Hao, Jun Wang, Kun Shao LiMTR: Time Series Motion Prediction for Diverse Road Users Through Multimodal Feature Integration
Camiel Oerlemans, Bram Grooten, Michiel Braat, Alaa Alassi, Emilia Silvas, Decebal Constantin Mocanu Linear Attention Sequence Parallelism
Weigao Sun, Zhen Qin, Dong Li, Xuyang Shen, Yu Qiao, Yiran Zhong Lion's Sign Noise Can Make Training More Stable
Simon Elistratov, Andrey Podivilov, Timofei Iuzhakov, Dmitry Vetrov Liquid Resistance Liquid Capacitance Networks
Mónika Farsang, Sophie A. Neubauer, Radu Grosu Llama Meets Cheburashka: Impact of Cultural Background for LLM Quiz Reasoning
Mikhail Lifar, Bogdan Protsenko, Daniil Kupriianenko, Nazar Chubkov, Kulaev Kirill Dmitrievich, Alexander Guda, Irina Piontkovskaya LLAVAGUARD: VLM-Based Safeguards for Vision Dataset Curation and Safety Assessment
Lukas Helff, Felix Friedrich, Manuel Brack, Kristian Kersting, Patrick Schramowski LLAVIDAL: Benchmarking Large Language Vision Models for Daily Activities of Living
Rajatsubhra Chakraborty, Arkaprava Sinha, Dominick Reilly, Manish Kumar Govind, Pu Wang, Francois Bremond, Srijan Das LLM Alignment Through Successive Policy Re-Weighting (SPR)
Xinnan Zhang, Siliang Zeng, Jiaxiang Li, Kaixiang Lin, Mingyi Hong LLM Alignment Using Soft Prompt Tuning: The Case of Cultural Alignment
Reem I. Masoud, Martin Ferianc, Philip Colin Treleaven, Miguel R. D. Rodrigues LLM and Simulation as Bilevel Optimizers: A New Paradigm to Advance Physical Scientific Discovery
Pingchuan Ma, Tsun-Hsuan Wang, Minghao Guo, Zhiqing Sun, Joshua B. Tenenbaum, Daniela Rus, Chuang Gan, Wojciech Matusik LLM Defenses Are Not Robust to Multi-Turn Human Jailbreaks yet
Nathaniel Li, Ziwen Han, Ian Steneker, Willow E. Primack, Riley Goodside, Hugh Zhang, Zifan Wang, Cristina Menghini, Summer Yue LLM Self-Correction with DeCRIM: Decompose, Critique, and Refine for Enhanced Following of Instructions with Multiple Constraints
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Sreeram Vennam, Anish R Joishy, Ponnurangam Kumaraguru LLM-Generated Black-Box Explanations Can Be Adversarially Helpful
Rohan Deepak Ajwani, Shashidhar Reddy Javaji, Frank Rudzicz, Zining Zhu LLM-Initialized Differentiable Causal Discovery
Shiv Kampani, David Hidary, Constantijn van der Poel, Martin Ganahl, Brenda Miao LLM2CLIP: Powerful Language Model Unlock Richer Visual Representation
Aoqi Wu, Weiquan Huang, Yifan Yang, Xufang Luo, Yuqing Yang, Chunyu Wang, Liang Hu, Xiyang Dai, Dongdong Chen, Chong Luo, Lili Qiu LLMForecaster: Improving Seasonal Event Forecasts with Unstructured Textual Data
Hanyu Zhang, Chuck Arvin, Dmitry Efimov, Michael W. Mahoney, Dominique Perrault-Joncas, Shankar Ramasubramanian, Andrew Gordon Wilson, Malcolm Wolff LLMs and Personalities: Inconsistencies Across Scales
Tosato Tommaso, Mahmood Hegazy, David Lemay, Mohammed Abukalam, Irina Rish, Guillaume Dumas LLMs Are Highly-Constrained Biophysical Sequence Optimizers
Angelica Chen, Samuel Don Stanton, Robert G Alberstein, Andrew Martin Watkins, Richard Bonneau, Vladimir Gligorijevic, Kyunghyun Cho, Nathan C. Frey Locality-Aware Concept Bottleneck Model
Sujin Jeon, Inwoo Hwang, Sanghack Lee, Byoung-Tak Zhang Long Context RAG Performance of Large Language Models
Quinn Leng, Jacob Portes, Sam Havens, Matei Zaharia, Michael Carbin Look-Ahead Selective Plasticity for Continual Learning of Visual Tasks
Rouzbeh Meshkinnejad, Jie Mei, Zeduo Zhang, Daniel J Lizotte, Yalda Mohsenzadeh Looped Transformers for Length Generalization
Ying Fan, Yilun Du, Kannan Ramchandran, Kangwook Lee LORC: Low-Rank Compression for LLMs KV Cache with a Progressive Compression Strategy
Rongzhi Zhang, Kuan Wang, Liyuan Liu, Shuohang Wang, Hao Cheng, Chao Zhang, Yelong Shen LoVA: Long-Form Video-to-Audio Generation
Xin Cheng, Xihua Wang, Yihan Wu, Yuyue Wang, Ruihua Song LSH-E Tells You What to Discard: An Adaptive Locality-Sensitive Strategy for KV Cache Compression
Tahseen Rabbani, Minghui Liu, Tony O'Halloran, Ananth Sankaralingam, Mary-Anne Hartley, Furong Huang Machine Learning Enables Engineering of Potent, Specific, and Therapeutically Developable Proteases
Jung-Eun Shin, Nathan J Rollins, Purvi Mande, Jordan M Anderson, Allison Colthart, Soumya Bengeri, Emily Hoyt, Alex Pellerin, Ivan Mascanfroni, Jyothsna Visweswaraiah, Yi Xing, Kevin L. Otipoby, Nathan Higginson-Scott, Ryan Peckner Machines and Mathematical Mutations: Using GNNs to Characterize Quiver Mutation Classes
Jesse He, Helen Jenne, Herman Chau, Davis Brown, Mark Raugas, Sara C. Billey, Henry Kvinge MagicPIG: LSH Sampling for Efficient LLM Generation
Zhuoming Chen, Ranajoy Sadhukhan, Zihao Ye, Yang Zhou, Jianyu Zhang, Niklas Nolte, Yuandong Tian, Matthijs Douze, Leon Bottou, Zhihao Jia, Beidi Chen Mallows-DPO: Fine-Tune Your LLM with Preference Dispersions
Haoxian Chen, Hanyang Zhao, Henry Lam, David Yao, Wenpin Tang Mamba4Cast: Efficient Zero-Shot Time Series Forecasting with State Space Models
Sathya Kamesh Bhethanabhotla, Omar Swelam, Julien Siems, David Salinas, Frank Hutter ManiPose: Manifold-Constrained Multi-Hypothesis 3D Human Pose Estimation
Cédric Rommel, Victor Letzelter, Nermin Samet, Renaud Marlet, Matthieu Cord, Patrick Perez, Eduardo Valle MAP: Model Merging with Amortized Pareto Front Using Limited Computation
Lu Li, Tianyu Zhang, Zhiqi Bu, Suyuchen Wang, Huan He, Jie Fu, Yonghui Wu, Jiang Bian, Yong Chen, Yoshua Bengio MAPLE: Memory-Aware Predict and Load for Efficient LLM Inference
Zhenyu Liu, Zhemin Zhang, Zirui Zhang, Yanyuan Qin, Jiayi Luo, Zhenyu Gu, Liu Liu MASAI: Modular Architecture for Software-Engineering AI Agents
Nalin Wadhwa, Atharv Sonwane, Daman Arora, Abhav Mehrotra, Saiteja Utpala, Ramakrishna B Bairi, Aditya Kanade, Nagarajan Natarajan Mastering Task Arithmetic: $\tau$Jp as a Key Indicator for Weight Disentanglement
Kotaro Yoshida, Yuji Naraki, Takafumi Horie, Ryosuke Yamaki, Ryotaro Shimizu, Yuki Saito, Julian McAuley, Hiroki Naganuma Math for AI: On the Generalization of Learning Mathematical Problem Solving
Ruochen Zhou, Minrui Xu, Shiqi Chen, Junteng Liu, Yunqi Li, Xinxin Lin, Zhengyu Chen, Junxian He Matryoshka Multimodal Models
Mu Cai, Jianwei Yang, Jianfeng Gao, Yong Jae Lee Maven: A Multimodal Foundation Model for Supernova Science
Gemma Zhang, Thomas Helfer, Alexander Thomas Gagliano, Siddharth Mishra-Sharma, V Ashley Villar Maven: A Multimodal Foundation Model for Supernova Science
Gemma Zhang, Thomas Helfer, Alexander Thomas Gagliano, Siddharth Mishra-Sharma, V Ashley Villar Maven: A Multimodal Foundation Model for Supernova Science
Gemma Zhang, Thomas Helfer, Alexander Thomas Gagliano, Siddharth Mishra-Sharma, V Ashley Villar MD-DiT: Step-Aware Mixture-of-Depths for Efficient Diffusion Transformers
Mingzhu Shen, Pengtao Chen, Peng Ye, Guoxuan Xia, Tao Chen, Christos-Savvas Bouganis, Yiren Zhao Measuring Implicit Bias in Explicitly Unbiased Large Language Models
Xuechunzi Bai, Angelina Wang, Ilia Sucholutsky, Thomas L. Griffiths Measuring Steerability in Large Language Models
Trenton Chang, Jenna Wiens, Tobias Schnabel, Adith Swaminathan MED-OMIT: Extrinsically-Focused Evaluation Metric for Omissions in Medical Summarization
Elliot Schumacher, Daniel Rosenthal, Dhruv Naik, Varun Nair, Luladay Price, Geoff Tso, Anitha Kannan MED: Exploring LLM Memorization of Encrypted Data
Panagiotis Christodoulou, Giulio Zizzo, Sergio Maffeis Medical Imaging Complexity and Its Effects on GAN Performance
William Cagas, Chan Ko, Blake T. Hsiao, Shryuk Grandhi, Rishi Bhattacharya, Kevin Zhu, Michael Lam MEDS-Torch: An ML Pipeline for Inductive Experiments for EHR Medical Foundation Models
Nassim Oufattole, Teya Bergamaschi, Pawel Renc, Aleksia Kolo, Matthew B.A. McDermott, Collin Stultz MeMDLM: De Novo Membrane Protein Design with Masked Discrete Diffusion Protein Language Models
Shrey Goel, Vishrut Thoutam, Edgar Mariano Marroquin, Aaron Gokaslan, Arash Firouzbakht, Sophia Vincoff, Volodymyr Kuleshov, Huong T. Kratochvil, Pranam Chatterjee Memorize and Rank: Elevating Large Language Models for Clinical Diagnosis Prediction
Mingyu Derek Ma, Xiaoxuan Wang, Yijia Xiao, Anthony Cuturrufo, Vijay S Nori, Eran Halperin, Wei Wang Memory Efficient Continual Learning with CLIP Models
Ryan King, Gang Li, Bobak J Mortazavi, Tianbao Yang Memory Retaining Finetuning via Distillation
Zitong Yang, Aonan Zhang, Sam Wiseman, Xiang Kong, Ke Ye, Dong Yin MemReasoner: A Memory-Augmented LLM Architecture for Multi-Hop Reasoning
Ching-Yun Ko, Sihui Dai, Payel Das, Georgios Kollias, Subhajit Chaudhury, Aurelie Lozano Metalic: Meta-Learning In-Context with Protein Language Models
Jacob Beck, Shikha Surana, Manus McAuliffe, Oliver Bent, Thomas D Barrett, Juan Jose Garau-Luis, Paul Duckworth MID-Space: Aligning Diverse Communities' Needs to Inclusive Public Spaces
Shravan Nayak, Rashid Mushkani, Hugo Berard, Allison Cohen, Shin Koseki, Hadrien Bertrand MIMIC: Multimodal Islamophobic Meme Identification and Classification
S M Jishanul Islam, Sahid Hossain Mustakim, Sadia Ahmmed, Md. Faiyaz Abdullah Sayeedi, Swapnil Khandoker, Syed Tasdid Azam Dhrubo, Nahid Hossain Mind the Gap: Examining the Self-Improvement Capabilities of Large Language Models
Yuda Song, Hanlin Zhang, Carson Eisenach, Sham M. Kakade, Dean Foster, Udaya Ghai Mitigating Downstream Model Risks via Model Provenance
Keyu Wang, Scott Schaffter, Abdullah Norozi Iranzad, Doina Precup, Jonathan Lebensold, Meg Risdal Mitigating Hallucinations in LVLMs via Summary-Guided Decoding
Kyungmin Min, Minbeom Kim, Kang-il Lee, Dongryeol Lee, Kyomin Jung Mix Data or Merge Models? Optimizing for Performance and Safety in Multilingual Contexts
Aakanksha, Arash Ahmadian, Seraphina Goldfarb-Tarrant, Beyza Ermis, Marzieh Fadaee, Sara Hooker Mixture of Experts Enable Efficient and Effective Protein Understanding and Design
Ning Sun, Shuxian Zou, Tianhua Tao, Sazan Mahbub, Dian Li, Yonghao Zhuang, Hongyi Wang, Xingyi Cheng, Le Song, Eric P. Xing Mixture of Experts for Time Series Foundation Models
Xu Liu, Juncheng Liu, Gerald Woo, Taha Aksu, Chenghao Liu, Silvio Savarese, Caiming Xiong, Doyen Sahoo Mixture of Parrots: Mixtures of Experts Improve Memorization More than Reasoning
Samy Jelassi, Clara Mohri, David Brandfonbrener, Alex Gu, Nikhil Vyas, Nikhil Anand, David Alvarez-Melis, Yuanzhi Li, Sham M. Kakade, Eran Malach ML-Driven Design of 3’ Untranslated Regions for mRNA Stability
Alyssa Kramer Morrow, Elise Duboscq Flynn, Emily Hoelzli, Ashley Thornal, Meimei Shan, Aniketh Janardhan Reddy, Gorkem Garipler, Rory Kirchner, Sophia Tabchouri, Ankit Gupta, Jean-Baptiste Michel, Uri Laserson MLADDC: Multi-Lingual Audio Deepfake Detection Corpus
Arth Juhul Shah, Ravindrakumar M. Purohit, Dharmendra H. Vaghera, Hemant Patil MM-SpuBench: Towards Better Understanding of Spurious Biases in Multimodal LLMs
Wenqian Ye, Guangtao Zheng, Yunsheng Ma, Xu Cao, Bolin Lai, James Matthew Rehg, Aidong Zhang MMed-RAG: Versatile Multimodal RAG System for Medical Vision Language Models
Peng Xia, Kangyu Zhu, Haoran Li, Tianze Wang, Weijia Shi, Sheng Wang, Linjun Zhang, James Zou, Huaxiu Yao MMed-RAG: Versatile Multimodal RAG System for Medical Vision Language Models
Peng Xia, Kangyu Zhu, Haoran Li, Tianze Wang, Weijia Shi, Linjun Zhang, James Zou, Huaxiu Yao MMIE: Massive Multimodal Interleaved Comprehension Benchmark for Large Vision-Language Models
Peng Xia, Siwei Han, Shi Qiu, Yiyang Zhou, Zhaoyang Wang, Wenhao Zheng, Zhaorun Chen, Chenhang Cui, Mingyu Ding, Linjie Li, Lijuan Wang, Huaxiu Yao MMWorld: Towards Multi-Discipline Multi-Faceted World Model Evaluation in Videos
Xuehai He, Weixi Feng, Kaizhi Zheng, Yujie Lu, Wanrong Zhu, Jiachen Li, Yue Fan, Jianfeng Wang, Linjie Li, Zhengyuan Yang, Kevin Lin, William Yang Wang, Lijuan Wang, Xin Eric Wang MNIST-Nd: A Set of Naturalistic Datasets to Benchmark Clustering Across Dimensions
Polina Turishcheva, Laura Hansel, Martin Ritzert, Marissa A. Weis, Alexander S Ecker Mobile OS Task Procedure Extraction from YouTube
Yunseok Jang, Yeda Song, Sungryull Sohn, Lajanugen Logeswaran, Tiange Luo, Honglak Lee MobileFlow: A Multimodal LLM for Mobile GUI Agent
Songqin Nong, Jiali Zhu, Rui Wu, Jiongchao Jin, Shuo Shan, Xiutian Huang, Wenhao Xu Mode Collapse in Variational Deep Gaussian Processes
Francisco Javier Sáez-Maldonado, Juan Maroñas, Daniel Hernández-Lobato Model Exploration Through Marginal Likelihood Entropy Maximisation
Daniel Jarne Ornia, Joel Dyer, Nicholas George Bishop, Ani Calinescu, Michael J. Wooldridge Model Manipulation Attacks Enable More Rigorous Evaluations of LLM Capabilities
Zora Che, Stephen Casper, Anirudh Satheesh, Rohit Gandikota, Domenic Rosati, Stewart Slocum, Lev E McKinney, Zichu Wu, Zikui Cai, Bilal Chughtai, Daniel Filan, Furong Huang, Dylan Hadfield-Menell Model Recycling: Model Component Reuse to Promote In-Context Learning
Lindsay M. Smith, Chase Goddard, Vudtiwat Ngampruetikorn, David J. Schwab Model Soup for Better RLHF: Weight Space Averaging to Improve Alignment in LLMs
Atoosa Chegini, Hamid Kazemi, Seyed Iman Mirzadeh, Dong Yin, Maxwell Horton, Moin Nabi, Mehrdad Farajtabar, Keivan Alizadeh Modeling CAR Response at the Single-Cell Level Using Conditional OT
Alice Driessen, Jannis Born, Rocío Castellanos Rueda, Sai T. Reddy, Marianna Rapsomaniki Modeling Cognitive Strategies in Teaching
Sevan K Harootonian, Yael Niv, Thomas L. Griffiths, Mark K Ho Modeling Complex System Dynamics with Flow Matching Across Time and Conditions
Martin Rohbeck, Charlotte Bunne, Edward De Brouwer, Jan-Christian Huetter, Anne Biton, Kelvin Y. Chen, Aviv Regev, Romain Lopez Modelling Variation in the Forward EMG Model.
Dimitrios Halatsis, Alexander Kenneth Clarke, Dario Farina Modern Hopfield Networks Meet Encoded Neural Representations - Addressing Practical Considerations
Satyananda Kashyap, Niharika S. D'Souza, Luyao Shi, Ken C. L. Wong, Hongzhi Wang, Tanveer Syeda-mahmood Modulating Language Model Experiences Through Frictions
Katherine M. Collins, Valerie Chen, Ilia Sucholutsky, Hannah Rose Kirk, Malak Sadek, Holli Sargeant, Ameet Talwalkar, Adrian Weller, Umang Bhatt Molecular Generation with State Space Sequence Models
Anri Lombard, Shane Acton, Ulrich Armel Mbou Sob, Jan Buys MolGen-Transformer: An Open-Source Self-Supervised Model for Molecular Generation and Latent Space Exploration
Chih-Hsuan Yang, Rebekah Duke, Parker Delaney Sornberger, Moses Ogbaje, Chad Risko, Baskar Ganapathysubramanian Molphenix: A Multimodal Foundation Model for PhenoMolecular Retrieval
Philip Fradkin, Puria Azadi Moghadam, Karush Suri, Frederik Wenkel, Maciej Sypetkowski, Dominique Beaini Molphenix: A Multimodal Foundation Model for PhenoMolecular Retrieval
Philip Fradkin, Puria Azadi Moghadam, Karush Suri, Frederik Wenkel, Maciej Sypetkowski, Dominique Beaini Monkey See, Model Knew: Large Language Models Accurately Predict Human and Macaque Visual Brain Activity
Colin Conwell, Emalie McMahon, Akshay Vivek Jagadeesh, Kasper Vinken, Saloni Sharma, Jacob S. Prince, George A. Alvarez, Talia Konkle, Leyla Isik, Margaret Livingstone Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning
Yuxi Xie, Anirudh Goyal, Wenyue Zheng, Min-Yen Kan, Timothy P Lillicrap, Kenji Kawaguchi, Michael Shieh MovieCORE: COgnitive REasoning in Movies
Gueter Josmy Faure, Min-Hung Chen, Jia-Fong Yeh, Ying Cheng, Hung-Ting Su, Shang-Hong Lai, Winston H. Hsu MSc-SQL: Multi-Sample Critiquing Small Language Models for Text-to-SQL Translation
Satya Krishna Gorti, Ilan Gofman, Zhaoyan Liu, Jiapeng Wu, Noël Vouitsis, Guangwei Yu, Jesse C. Cresswell, Rasa Hosseinzadeh Multi-Modal Cascade Feature Transfer for Polymer Property Prediction
Kiichi Obuchi, Yuta Yahagi, Kota Matsui, Kiyohiko Toyama, Shukichi Tanaka Multi-Objective Reinforcement Learning: A Tool for Pluralistic Alignment
Peter Vamplew, Conor F. Hayes, Cameron Foale, Richard Dazeley, Hadassah Harland Multi-Source Music Generation with Latent Diffusion
Zhongweiyang Xu, Debottam Dutta, Yu-Lin Wei, Romit Roy Choudhury Multi-Step Preference Optimization via Two-Player Markov Games
Yongtao Wu, Luca Viano, Yihang Chen, Zhenyu Zhu, Quanquan Gu, Volkan Cevher Multi-Task Neural Network Mapping onto Analog-Digital Heterogeneous Accelerators
Hadjer Benmeziane, Corey Lammie, Athanasios Vasilopoulos, Irem Boybat, Manuel Le Gallo, Hsinyu Tsai, Kaoutar El Maghraoui, Abu Sebastian Multilingual Trolley Problems for Language Models
Zhijing Jin, Max Kleiman-Weiner, Giorgio Piatti, Sydney Levine, Jiarui Liu, Fernando Gonzalez Adauto, Francesco Ortu, András Strausz, Mrinmaya Sachan, Rada Mihalcea, Yejin Choi, Bernhard Schölkopf Multimodal Auto Validation for Self-Refinement in Web Agents
Ruhana Azam, Tamer Abuelsaad, Aditya Vempaty, Ashish Jagmohan Multimodal Self-Instruct: Synthetic Abstract Image and Visual Reasoning Instruction Using Language Model
Wenqi Zhang, Zhenglin Cheng, Yuanyu He, Mengna Wang, Yongliang Shen, Zeqi Tan, Guiyang Hou, Mingqian He, Yanna Ma, Weiming Lu, Yueting Zhuang Multimodal Situational Safety
Kaiwen Zhou, Chengzhi Liu, Xuandong Zhao, Anderson Compalas, Xin Eric Wang Multivariate Prediction of Human Behavior in Task fMRI
Alessandra Camassa, Joseph Park, Margot Wagner, Terrence Sejnowski, Gerald M Pao MultiVerse: Exposing Large Language Model Alignment Problems in Diverse Worlds
Xiaolong Jin, Zhuo Zhang, Guangyu Shen, Hanxi Guo, Kaiyuan Zhang, Siyuan Cheng, Xiangyu Zhang MuMA-ToM: Multi-Modal Multi-Agent Theory of Mind
Haojun Shi, Suyu Ye, Xinyu Fang, Chuanyang Jin, Leyla Isik, Yen-Ling Kuo, Tianmin Shu MuMA-ToM: Multi-Modal Multi-Agent Theory of Mind
Haojun Shi, Suyu Ye, Xinyu Fang, Chuanyang Jin, Leyla Isik, Yen-Ling Kuo, Tianmin Shu N Multipliers for N Bits: Learning Bit Multipliers for Non-Uniform Quantization
Raghav Singhal, Anmol Biswas, Sivakumar Elangovan, Shreyas Sabnis, Udayan Ganguly N-Gram Induction Heads for In-Context RL: Improving Stability and Reducing Data Needs
Ilya Zisman, Alexander Nikulin, Andrei Polubarov, Lyubaykin Nikita, Vladislav Kurenkov Nanowire Neural Networks for Time-Series Processing
Veronica Pistolesi, Andrea Ceni, Claudio Gallicchio, Gianluca Milano, Carlo Ricciardi NARAIM: Native Aspect Ratio Autoregressive Image Models
Daniel Gallo Fernández, Robert van der Klis, Răzvan-Andrei Matișan, Janusz Partyka, Samuele Papa, Efstratios Gavves, Phillip Lippe Narrow Transformer: Mono-Lingual Code SLM for Desktop
Kamalkumar Rathinasamy, A J Balaji, Ankush Kumar, Gagan Gayari, Harshini K, Rajab Ali Mondal, K S Sreenivasa Raghavan, Swayam Singh, Mohammed Rafee Tarafdar Natural Language Prompts Guide the Design of Novel Functional Protein Sequences
Niksa Praljak, Hugh Yeh, Miranda Moore, Michael Socolich, Rama Ranganathan, Andrew Ferguson Neural Audio Codec for Latent Music Representations
Luca A Lanzendörfer, Florian Grötschla, Amir Dellali, Roger Wattenhofer Neural Compression for Multispectral Satellite Images
Woojin Cho, Steve Andreas Immanuel, Junhyuk Heo, Darongsae Kwon Neural Entropic Multimarginal Optimal Transport
Dor Tsur, Ziv Goldfeld, Kristjan Greenewald, Haim H. Permuter Neuron-Astrocyte Associative Memory
Leo Kozachkov, Jean-Jacques Slotine, Dmitry Krotov NLIR: Natural Language Intermediate Representation for Mechanized Theorem Proving
Laetitia Teodorescu, Guillaume Baudart, Emilio Jesús Gallego Arias, Marc Lelarge Noise Aware Finetuning for Analog Non-Linear Dot Product Engine
Lei Zhao, Luca Buonanno, Aishwarya Natarajan, Jim Ignowski, Giacomo Pedretti Non-Interactive Remote Coordination
Yassine Hamdi, Xueyan Niu, Bo Bai, Deniz Gunduz Normalization Matters for Optimization Performance on Graph Neural Networks
Alan Milligan, Frederik Kunstner, Hamed Shirzad, Mark Schmidt, Danica J. Sutherland Not All LLM Reasoners Are Created Equal
Arian Hosseini, Alessandro Sordoni, Daniel Kenji Toyama, Aaron Courville, Rishabh Agarwal Not All LLM Reasoners Are Created Equal
Arian Hosseini, Alessandro Sordoni, Daniel Kenji Toyama, Aaron Courville, Rishabh Agarwal OASIS: Open Agents Social Interaction Simulations on One Million Agents
Ziyi Yang, Zaibin Zhang, Zirui Zheng, Yuxian Jiang, Ziyue Gan, Zhiyu Wang, Zijian Ling, Konisberg, Martz Ma, Bowen Dong, Prateek Gupta, Shuyue Hu, Zhenfei Yin, Guohao Li, Xu Jia, Lijun Wang, Bernard Ghanem, Huchuan Lu, Wanli Ouyang, Yu Qiao, Philip Torr, Jing Shao Object-Centric Temporal Consistency via Conditional Autoregressive Inductive Biases
Cristian Meo, Akihiro Nakano, Mircea Tudor Lică, Aniket Rajiv Didolkar, Masahiro Suzuki, Anirudh Goyal, Mengmi Zhang, Justin Dauwels, Yutaka Matsuo, Yoshua Bengio OC-CLIP : Object-Centric Binding in Contrastive Language-Image Pretraining
Rim Assouel, Pietro Astolfi, Florian Bordes, Michal Drozdzal, Adriana Romero-Soriano OmniPredict: GPT-4o Enhanced Multi-Modal Pedestrian Crossing Intention Prediction
Je-Seok Ham, Jia Huang, Peng Jiang, Jinyoung Moon, Yongjin Kwon, Srikanth Saripalli, Changick Kim On a Spurious Interaction Between Uncertainty Scores and Answer Evaluation Metrics in Generative QA Tasks
Andrea Santilli, Miao Xiong, Michael Kirchhof, Pau Rodriguez, Federico Danieli, Xavier Suau, Luca Zappella, Sinead Williamson, Adam Golinski On Demonstration Selection for Improving Fairness in Language Models
Song Wang, Peng Wang, Yushun Dong, Tong Zhou, Lu Cheng, Yangfeng Ji, Jundong Li On Divergence Measures for Training GFlowNets
Tiago Silva, Eliezer de Souza da Silva, Diego Mesquita On Efficient Distillation from LLMs to SLMs
Metod Jazbec, Menglin Xia, Ankur Mallick, Daniel Madrigal, Dongge Han, Samuel Kessler, Victor Rühle On Incorporating Prior Knowledge Extracted from Pre-Trained Language Models into Causal Discovery
Chanhui Lee, Juhyeon Kim, YongJun Jeong, Yoonseok Yeom, Juhyun Lyu, Jung-Hee Kim, Sangmin Lee, Sangjun Han, Hyeokjun Choe, Soyeon Park, Woohyung Lim, Kyunghoon Bae, Sungbin Lim, Sanghack Lee On Interpretability and Overreliance
Julian Skirzynski, Elena Glassman, Berk Ustun On LLM Augmented AB Experimentation
Shiv Shankar, Ritwik Sinha, Madalina Fiterau On Memorization of Large Language Models in Logical Reasoning
Chulin Xie, Yangsibo Huang, Chiyuan Zhang, Da Yu, Xinyun Chen, Bill Yuchen Lin, Bo Li, Badih Ghazi, Ravi Kumar On the Cognitive Alignment Between Humans and Machines
Marco Rothermel, Sayed Soroush Daftarian, Tahmineh A. Koosha, Mohammad-Ali Nikouei Mahani, Hamidreza Jamalabadi On the Ricci Curvature of Attention Maps and Transformers Training and Robustness
Amirhossein Farzam, Oded Schlesinger, Joshua M. Susskind, Juan Matias Di Martino, Guillermo Sapiro On Your Mark, Get Set, Warmup!
Dayal Singh Kalra, Maissam Barkeshli One Initialization to Rule Them All: Fine-Tuning via Explained Variance Adaptation
Fabian Paischer, Lukas Hauzenberger, Thomas Schmied, Benedikt Alkin, Marc Peter Deisenroth, Sepp Hochreiter One Initialization to Rule Them All: Fine-Tuning via Explained Variance Adaptation
Fabian Paischer, Lukas Hauzenberger, Thomas Schmied, Benedikt Alkin, Marc Peter Deisenroth, Sepp Hochreiter One-Shot World Models Using a Transformer Trained on a Synthetic Prior
Fabio Ferreira, Moreno Schlageter, Raghu Rajan, André Biedenkapp, Frank Hutter OpenMathInstruct-2: Accelerating AI for Math with Massive Open-Source Instruction Data
Shubham Toshniwal, Wei Du, Ivan Moshkov, Branislav Kisacanin, Alexan Ayrapetyan, Igor Gitman Optimizing Attention
Hanno Ackermann, Hong Cai, Markus Nagel, Leyla Mirvakhabova, Farhad G. Zanjani, Fatih Porikli Optimizing Small Language Models for In-Vehicle Function-Calling
Yahya Sowti Khiabani, Farris Atif, Chieh Hsu, Sven Stahlmann, Tobias Michels, Sebastian Kramer, Benedikt Heidrich, M. Saquib Sarfraz, Julian Merten, Faezeh Tafazzoli Optimizing the Gabriel Graph Construction Algorithm
Jose Geraldo Fernandes, Vitor Mourao Hanriot, Antonio de Padua Braga Optimizing the IFMIF-DONES Particle Accelerator with Differentiable Deep Learning Surrogate Models
Galo Gallardo Romero, Guillermo Rodríguez-Llorente, Lucas Magariños Rodríguez, Rodrigo Morant Navascués, Nikita Khvatkin Petrovsky, Roberto Gómez-Espinosa Martín Orthrus: Towards Evolutionary and Functional RNA Foundation Models
Philip Fradkin, Ruian Shi, Keren Isaev, Brendan Frey, Quaid Morris, Leo J Lee, Bo Wang Out-of-Distribution Detection & Applications with Ablated Learned Temperature Energy
Will LeVine, Benjamin Pikus, Jacob Phillips, Berk Norman, Fernando Amat Gil, Sean M. Hendryx PabLO: Improving Semi-Supervised Learning with Pseudolabeling Optimization
Harit Vishwakarma, Yi Chen, Satya Sai Srinath Namburi Gnvv, Sui Jiet Tay, Ramya Korlakai Vinayak, Frederic Sala PACE: Procedural Abstractions for Communicating Efficiently
Jonathan David Thomas, Andrea Silvi, Devdatt Dubhashi, Vikas Garg, Moa Johansson PaPaGei: Open Foundation Models for Optical Physiological Signals
Arvind Pillai, Dimitris Spathis, Fahim Kawsar, Mohammad Malekzadeh Parameter-Efficient Fine-Tuning of State Space Models
Kevin Galim, Wonjun Kang, Yuchen Zeng, Hyung Il Koo, Kangwook Lee Parrot: Autoregressive Spoken Dialogue Language Modeling with Decoder-Only Transformers
Ziqiao Meng, Qichao Wang, Wenqian Cui, Yifei Zhang, Bingzhe Wu, Irwin King, Liang Chen, Peilin Zhao Partially Frozen Random Networks Contain Compact Strong Lottery Tickets
Hikari Otsuka, Daiki Chijiwa, Ángel López García-Arias, Yasuyuki Okoshi, Kazushi Kawamura, Thiem Van Chu, Daichi Fujiki, Susumu Takeuchi, Masato Motomura PATIENT-Ψ: Using Large Language Models to Simulate Patients for Training Mental Health Professionals
Ruiyi Wang, Stephanie Milani, Jamie C. Chiu, Jiayin Zhi, Shaun M. Eack, Travis Labrum, Samuel M Murphy, Nev Jones, Kate V Hardy, Hong Shen, Fei Fang, Zhiyu Chen PATIENT-Ψ: Using Large Language Models to Simulate Patients for Training Mental Health Professionals
Ruiyi Wang, Stephanie Milani, Jamie C. Chiu, Jiayin Zhi, Shaun M. Eack, Travis Labrum, Samuel M Murphy, Nev Jones, Kate V Hardy, Hong Shen, Fei Fang, Zhiyu Chen Pay Attention to What Matters
Pedro Luiz Silva, Fadhel Ayed, Antonio De Domenico, Ali Maatouk Pearls from Pebbles: Improved Confidence Functions for Auto-Labeling
Harit Vishwakarma, Yi Chen, Sui Jiet Tay, Satya Sai Srinath Namburi Gnvv, Frederic Sala, Ramya Korlakai Vinayak PepDoRA: A Unified Peptide Language Model via Weight-Decomposed Low-Rank Adaptation
Leyao Wang, Rishab Pulugurta, Pranay Vure, Yinuo Zhang, Aastha Pal, Pranam Chatterjee Perception Loss Function Adaptive to Rate for Learned Video Compression
Sadaf Salehkalaibar, Buu Phan, João Atz Dick, Ashish J Khisti, Jun Chen, Wei Yu Personalized Adaptation via In-Context Preference Learning
Allison Lau, Younwoo Choi, Vahid Balazadeh, Keertana Chidambaram, Vasilis Syrgkanis, Rahul Krishnan Personalized Soups: Personalized Large Language Model Alignment via Post-Hoc Parameter Merging
Joel Jang, Seungone Kim, Bill Yuchen Lin, Yizhong Wang, Jack Hessel, Luke Zettlemoyer, Hannaneh Hajishirzi, Yejin Choi, Prithviraj Ammanabrolu PersonalLLM: Tailoring LLMs to Individual Preferences
Thomas P Zollo, Andrew Wei Tung Siah, Naimeng Ye, Ang Li, Hongseok Namkoong PertEval-scFM: Benchmarking Single-Cell Foundation Models for Perturbation Effect Prediction
Aaron Wenteler, Martina Occhetta, Nikhil Branson, Magdalena Huebner, William Dee, Victor Curean, William Connell, Siu Pui Chung, Yasha Ektefaie, Amaya Gallagher-Syed, César Miguel Valdez Córdova PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis
Yan Wu, Esther Wershof, Sebastian M Schmon, Marcel Nassar, Błażej Osiński, Ridvan Eksi, Kun Zhang, Thore Graepel Pharmacophore-Based Design by Learning on Voxel Grids
Omar Mahmood, Pedro O. Pinheiro, Richard Bonneau, Saeed Saremi, Vishnu Sresht Photonic KAN: A Kolmogorov-Arnold Network Inspired Efficient Photonic Neuromorphic Architecture
Yiwei Peng, Sean Hooten, Thomas Van Vaerenbergh, Xian Xiao, Marco Fiorentino, Raymond G Beausoleil PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making
Jonathan Light, Sixue Xing, Yuanzhe Liu, Weiqin Chen, Min Cai, Xiusi Chen, Guanzhi Wang, Wei Cheng, Yisong Yue, Ziniu Hu Planning in Natural Language Improves LLM Search for Code Generation
Evan Z Wang, Federico Cassano, Catherine Wu, Yunfeng Bai, William Song, Vaskar Nath, Ziwen Han, Sean M. Hendryx, Summer Yue, Hugh Zhang Pluralistic Alignment over Time
Toryn Q. Klassen, Parand A. Alamdari, Sheila A. McIlraith PoisonedParrot: Subtle Data Poisoning Attacks to Elicit Copyright-Infringing Content from Large Language Models
Michael-Andrei Panaitescu-Liess, Pankayaraj Pathmanathan, Yigitcan Kaya, Zora Che, Bang An, Sicheng Zhu, Aakriti Agrawal, Furong Huang Polar Codes for Channel Simulation
Sharang M. Sriramu, Rochelle Barsz, Elizabeth Polito, Aaron B. Wagner Policy Aggregation
Parand A. Alamdari, Soroush Ebadian, Ariel D. Procaccia Policy Dreamer: Diverse Public Policy Generation via Elicitation and Simulation of Human Preferences
Arjun Karanam, José Ramón Enríquez, Udari Madhushani Sehwag, Michael Elabd, Kanishk Gandhi, Noah Goodman, Sanmi Koyejo Policy Optimization for Strictly Batch Imitation Learning
Rishabh Agrawal, Nathan Dahlin, Rahul Jain, Ashutosh Nayyar Population Transformer: Learning Population-Level Representations of Intracranial Activity
Geeling Chau, Christopher Wang, Sabera J Talukder, Vighnesh Subramaniam, Saraswati Soedarmadji, Yisong Yue, Boris Katz, Andrei Barbu PORTAL: Scalable Tabular Foundation Models via Content-Specific Tokenization
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Yanjun Gao, Skatje Myers, Shan Chen, Dmitriy Dligach, Timothy A Miller, Danielle Bitterman, Guanhua Chen, Anoop Mayampurath, Matthew Churpek, Majid Afshar Position: Addressing Ethical Challenges and Safety Risks in GenAI-Powered Brain-Computer Interfaces
Konstantinos Barmpas, Georgios Zoumpourlis, Yannis Panagakis, Dimitrios Adamos, Nikolaos Laskaris, Stefanos Zafeiriou Position: Maximizing Neural Regression Scores May Not Identify Good Models of the Brain
Rylan Schaeffer, Mikail Khona, Sarthak Chandra, Mitchell Ostrow, Brando Miranda, Sanmi Koyejo Position: Participatory Assessment of Large Language Model Applications in an Academic Medical Center
Giorgia Carra, Bogdan Kulynych, François Bastardot, Daniel E. Kaufmann, Noémie Boillat-Blanco, Jean Louis Raisaro Position: XAI Needs Formal Notions of Explanation Correctness
Stefan Haufe, Rick Wilming, Benedict Clark, Rustam Zhumagambetov, Danny Panknin, Ahcene Boubekki Post-Calibration Techniques: Balancing Calibration and Score Distribution Alignment
Agathe Fernandes Machado, Arthur Charpentier, Emmanuel Flachaire, Ewen Gallic, Francois Hu Posterior Sampling via Autoregressive Generation
Kelly W. Zhang, Tiffany Cai, Hongseok Namkoong, Daniel Russo Predicting Human Decisions with Behavioral Theories and Machine Learning
Ori Plonsky, Reut Apel, Eyal Ert, Moshe Tennenholtz, David Bourgin, Joshua Peterson, Daniel Reichman, Thomas L. Griffiths, Stuart Russell, Evan Carter, James F. Cavanagh, Ido Erev Preference-Based Multi-Objective Bayesian Optimization with Gradients
Joshua Hang Sai Ip, Ankush Chakrabarty, Hideyuki Masui, Ali Mesbah, Diego Romeres PRIMUS: Pretraining IMU Encoders with Multimodal Self-Supervision
Arnav Mohanty Das, Chi Ian Tang, Fahim Kawsar, Mohammad Malekzadeh Principled Probing of Foundation Models in the Auditory Modality
Etienne Bost, Mitsuko Aramaki, Richard Kronland-Martinet, Sølvi Ystad, Thierry Artières, Thomas Schatz Principles of Animal Cognition for LLM Evaluations: A Case Study on Transitive Inference
Sunayana Rane, Cyrus Kirkman, Amanda Royka, Graham Todd, Ryan Law, Jacob Gates Foster, Erica Cartmill Probabilistic Active Few-Shot Learning in Vision-Language Models
Anton Baumann, Marcus Klasson, Rui Li, Arno Solin, Martin Trapp Probabilistic Active Few-Shot Learning in Vision-Language Models
Anton Baumann, Marcus Klasson, Rui Li, Arno Solin, Martin Trapp Probabilistic Forecasting for Building Energy Systems: Are Time-Series Foundation Models the Answer?
Young-Jin Park, François Germain, Jing Liu, Ye Wang, Gordon Wichern, Toshiaki Koike-Akino, Navid Azizan, Christopher R. Laughman, Ankush Chakrabarty Probabilistic Fusion Approach for Robust Battery Prognostics
Jokin Alcibar, Ekhi Zugasti, Aitor Aguirre-Ortuzar, Jose I. Aizpurua Probing LLM World Models: Enhancing Guesstimation with Wisdom of Crowds Decoding
Yun-Shiuan Chuang, Nikunj Harlalka, Sameer Narendran, Alexander Cheung, Sizhe Gao, Siddharth Suresh, Junjie Hu, Timothy T. Rogers Progressive Distillation Induces an Implicit Curriculum
Abhishek Panigrahi, Bingbin Liu, Sadhika Malladi, Andrej Risteski, Surbhi Goel Projected Neural Differential Equations for Power Grid Modeling with Constraints
Alistair White, Anna Büttner, Maximilian Gelbrecht, Niki Kilbertus, Frank Hellmann, Niklas Boers Proliferation of Cosine-Tuning in Both Artificial Spiking and Cortical Neural Networks During Learning
Tengjun Liu, Yansong Chua, Yiwei Zhang, Yuxiao Ning, Guihua Wan, Zijun Wan, Shaomin Zhang, Weidong Chen ProMISe: Promptable Medical Image Segmentation Using SAM
Jinfeng Wang, Sifan Song, Xinkun Wang, Yiyi Wang, Yiyi Miao, Jionglong Su, S Kevin Zhou Promoting Cross-Modal Representations to Improve Multimodal Foundation Models for Physiological Signals
Ching Fang, Christopher Michael Sandino, Behrooz Mahasseni, Juri Minxha, Hadi Pouransari, Erdrin Azemi, Ali Moin, Ellen L. Zippi Prospective Learning: Learning for a Dynamic Future
Ashwin De Silva, Rahul Ramesh, Rubing Yang, Siyu Yu, Joshua T Vogelstein, Pratik Chaudhari Protecting Users from Themselves: Safeguarding Contextual Privacy in Interactions with Conversational Agents
Ivoline C. Ngong, Swanand Kadhe, Hao Wang, Keerthiram Murugesan, Justin D. Weisz, Amit Dhurandhar, Karthikeyan Natesan Ramamurthy Provable Unlearning in Topic Modeling and Downstream Tasks
Stanley Wei, Sadhika Malladi, Sanjeev Arora, Amartya Sanyal Pseudo-Asynchronous Local SGD: Robust and Efficient Data-Parallel Training
Hiroki Naganuma, Xinzhi Zhang, Man-Chung Yue, Ioannis Mitliagkas, Russell J. Hewett, Philipp Andre Witte, Yin Tat Lee Public Procurement for Responsible AI? Understanding U.S. Cities' Practices and Needs
Nari Johnson, Elise Silva, Harrison Leon, Motahhare Eslami, Beth Schwanke, Ravit Dotan, Hoda Heidari Pulsar Candidate Classification with Multimodal Large Language Models
Fuyong Zhao, Yuyang Li, Yanhao Wang, Hui Li, Mei Chen, Panfeng Chen, Ningchen Sun, Cunshi Wang, Jifeng Liu Putnam-AXIOM: A Functional and Static Benchmark for Measuring Higher Level Mathematical Reasoning
Aryan Gulati, Brando Miranda, Eric Chen, Emily Xia, Kai Fronsdal, Bruno de Moraes Dumont, Sanmi Koyejo PyTorch Frame: A Modular Framework for Multi-Modal Tabular Learning
Weihua Hu, Yiwen Yuan, Zecheng Zhang, Akihiro Nitta, Kaidi Cao, Vid Kocijan, Jinu Sunil, Jure Leskovec, Matthias Fey Quantifying Variance in Evaluation Benchmarks
Lovish Madaan, Aaditya K Singh, Rylan Schaeffer, Andrew Poulton, Sanmi Koyejo, Pontus Stenetorp, Sharan Narang, Dieuwke Hupkes Quantum Diffusion Model for Quark and Gluon Jet Generation
Mariia Baidachna, Sergei Gleyzer, Konstantin Matchev, Katia Matcheva, Kyoungchul Kong, Gopal Ramesh Dahale, Isabel Pedraza, Tom Magorsch, Rey Guadarrama Quantum Generative Adversarial Networks for High Energy Physics Simulations
Rey Guadarrama, Sergei Gleyzer, Konstantin Matchev, Katia Matcheva, Kyoungchul Kong, Gopal Ramesh Dahale, Mariia Baidachna, Haydee Hernández-Arellano, Isabel Pedraza Quo Vadis, Video Understanding with Vision-Language Foundation Models?
Mahmoud Ali, Di Yang, Arkaprava Sinha, Dominick Reilly, Srijan Das, Gianpiero Francesca, Francois Bremond Random Propagations in GNNs
Thu Bui, Anugunj Naman, Carola-Bibiane Schönlieb, Bruno Ribeiro, Beatrice Bevilacqua, Moshe Eliasof Random Token Fusion for Multi-View Medical Diagnosis
Jingyu Guo, Christos Matsoukas, Fredrik Strand, Kevin Smith RAP: Retrieval-Augmented Planning with Contextual Memory for Multimodal LLM Agents
Tomoyuki Kagaya, Thong Jing Yuan, Yuxuan Lou, Jayashree Karlekar, Sugiri Pranata, Akira Kinose, Koki Oguri, Felix Wick, Yang You Rational Metareasoning for Large Language Models
C. Nicolò De Sabbata, Theodore Sumers, Thomas L. Griffiths Rational Metareasoning for Large Language Models
C. Nicolò De Sabbata, Theodore Sumers, Thomas L. Griffiths Reaction Graph Networks for Inorganic Synthesis Condition Prediction of Solid State Materials
Thorben Prein, Fuzhan Rahmanian, Kesava Prasad Arul, Jasmin El-Wafi, Menelaos Panagiotis Fotiadis, Jan Heimann, Paul Weinmann, Yifei Duan, Elton Pan, Elsa Olivetti, Jennifer L.M. Rupp Reasoning and Tools for Forecasting
Elvis Hsieh, Preston Fu, Jonathan Chen Reasoning in Reasoning: A Hierarchical Framework for Better and Faster Neural Theorem Proving
Ziyu Ye, Jiacheng Chen, Jonathan Light, Yifei Wang, Jiankai Sun, Mac Schwager, Philip Torr, Guohao Li, Yuxin Chen, Kaiyu Yang, Yisong Yue, Ziniu Hu Recurrent Interpolants for Probabilistic Time Series Prediction
Yu Chen, Marin Biloš, Sarthak Mittal, Wei Deng, Kashif Rasul, Anderson Schneider Recursive Decomposition with Dependencies for Generic Divide-and-Conquer Reasoning
Sergio Hernández-Gutiérrez, Minttu Alakuijala, Alexander V Nikitin, Pekka Marttinen Recursive Nested Filtering for Efficient Amortized Bayesian Experimental Design
Sahel Iqbal, Hany Abdulsamad, Sara Perez-Vieites, Simo Särkkä, Adrien Corenflos Red Teaming Language-Conditioned Robot Models via Vision Language Models
Sathwik Karnik, Zhang-Wei Hong, Nishant Abhangi, Yen-Chen Lin, Tsun-Hsuan Wang, Pulkit Agrawal RefactorBench: Evaluating Stateful Reasoning in Language Agents Through Code
Dhruv Gautam, Spandan Garg, Jinu Jang, Neel Sundaresan, Roshanak Zilouchian Moghaddam ReFeR: A Hierarchical Framework of Models as Evaluative and Reasoning Agents
Yaswanth Narsupalli, Abhranil Chandra, Sreevatsa Muppirala, Manish Gupta, Pawan Goyal Refusal Tokens: A Simple Way to Calibrate Refusals in Large Language Models
Neel Jain, Aditya Shrivastava, Chenyang Zhu, Daben Liu, Alfy Samuel, Ashwinee Panda, Anoop Kumar, Micah Goldblum, Tom Goldstein Regress, Don’t Guess – A Regression-like Loss on Number Tokens for Language Models
Jonas Zausinger, Lars Pennig, Kacper Chlodny, Vincent Limbach, Anna Ketteler, Thorben Prein, Vishwa Mohan Singh, Michael Danziger, Jannis Born Regularizing the Infinite: Improved Generalization Performance with Deep Equilibrium Models
Babak Rahmani, Jannes Gladrow, Kirill Kalinin, Heiner Kremer, Christos Gkantsidis, Hitesh Ballani Reimagining Time Series Foundation Models: Metadata and State-Space Model Perspectives
Pengrui Quan, Ozan Baris Mulayim, Liying Han, Dezhi Hong, Mario Berges, Mani Srivastava Reinforcement Learning from Multi-Role Debates as Feedback for Bias Mitigation in LLMs
Ruoxi Cheng, Hao-Xuan Ma, Shuirong Cao, Jiaqi Li, Aihua Pei, Zhiqiang Wang, Pengliang Ji, Haoyu Wang, Jiaqi Huo Relational Deep Learning: Graph Representation Learning on Relational Databases
Joshua Robinson, Rishabh Ranjan, Weihua Hu, Kexin Huang, Jiaqi Han, Alejandro Dobles, Matthias Fey, Jan Eric Lenssen, Yiwen Yuan, Zecheng Zhang, Xinwei He, Jure Leskovec Relative Representations: Topological and Geometric Perspectives
Alejandro García-Castellanos, Giovanni Luca Marchetti, Danica Kragic, Martina Scolamiero RelWire: Metric Based Rewiring
Rishi Sonthalia, Anna Gilbert, Matthew Durham RenderAttack: Hundreds of Adversarial Attacks Through Differentiable Texture Generation
Dron Hazra, Alex Bie, Mantas Mazeika, Xuwang Yin, Andy Zou, Dan Hendrycks, Maximilian Kaufmann Report Cards: Qualitative Evaluation of LLMs Using Natural Language Summaries
Blair Yang, Fuyang Cui, Keiran Paster, Jimmy Ba, Pashootan Vaezipoor, Silviu Pitis, Michael R. Zhang Representation Learning Based Target Discovery from UKBB MRI Data
Sivaramakrishnan Sankarapandian, Ramprakash Srinivasan, Matt Sooknah, Elena Sorokin, Jun Xu Representation Learning of Structured Data for Medical Foundation Models
Vijay Prakash Dwivedi, Viktor Schlegel, Andy T. Liu, Thanh-Tung Nguyen, Abhinav Ramesh Kashyap, Jeng Wei, Wei-Hsian Yin, Stefan Winkler, Robby T. Tan Representation Tuning
Christopher Ackerman Research Journey of Generative Protein Modeling
Xinhui Chen, Yiwen Yuan, Joseph Liu, Chak Tou Leong, Zhen Xie, Xiaoye Zhu, Ying Chen, Songyue Chen, Chenyi Wang, Kun Li, Jie Zhang, Zuchao Li, Jiaqi Chen Residual Stream Analysis with Multi-Layer SAEs
Tim Lawson, Lucy Farnik, Conor Houghton, Laurence Aitchison Rethinking Aleatoric and Epistemic Uncertainty
Freddie Bickford Smith, Jannik Kossen, Eleanor Trollope, Mark van der Wilk, Adam Foster, Tom Rainforth Rethinking Artistic Copyright Infringements in the Era of Text-to-Image Generative Models
Mazda Moayeri, Samyadeep Basu, Sriram Balasubramanian, Priyatham Kattakinda, Atoosa Chegini, Robert Brauneis, Soheil Feizi Rethinking Fine-Tuning Through Geometric Perspective
Krishna Sri Ipsit Mantri, Moshe Eliasof, Carola-Bibiane Schönlieb, Bruno Ribeiro Rethinking Knowledge Transfer in Learning Using Privileged Information
Danil Provodin, Bram van den Akker, Christina Katsimerou, Maurits Clemens Kaptein, Mykola Pechenizkiy Rethinking LLM Memorization Through the Lens of Adversarial Compression
Avi Schwarzschild, Zhili Feng, Pratyush Maini, Zachary Chase Lipton, J Zico Kolter Rethinking Message Passing for Algorithmic Alignment
Joël Mathys, Florian Grötschla, Kalyan Varma Nadimpalli, Roger Wattenhofer Rethinking Patch Dependence for Masked Autoencoders
Letian Fu, Long Lian, Renhao Wang, Baifeng Shi, XuDong Wang, Adam Yala, Trevor Darrell, Alexei A Efros, Ken Goldberg RH20T-P: A Primitive-Level Robotic Manipulation Dataset Towards Composable Generalization Agents in Real-World Scenarios
Zeren Chen, Zhelun Shi, Xiaoya Lu, Lehan He, Sucheng Qian, Zhenfei Yin, Wanli Ouyang, Jing Shao, Yu Qiao, Cewu Lu, Lu Sheng RHAAPsody: RHEED Heuristic Adaptive Automation Platform Framework for Molecular Beam Epitaxy Synthesis
Sarah Akers, Henry W. Sprueill, Jenna Pope, Arman Ter-Petrosyan, Derek Hopkins, Ajay Harilal, Jijo Christudasjustus, Vinyay Amatya, Patrick Gemperline, Ryan Comes, Tiffany Kaspar Riemannian Black Box Variational Inference
Mykola Lukashchuk, Wouter W. L. Nuijten, Dmitry Bagaev, Ismail Senoz, Bert de Vries Right on Time: Revising Time Series Models by Constraining Their Explanations
Maurice Kraus, David Steinmann, Antonia Wüst, Andre Kokozinski, Kristian Kersting RLHS: Mitigating Misalignment in RLHF with Hindsight Simulation
Kaiqu Liang, Haimin Hu, Ryan Liu, Thomas L. Griffiths, Jaime Fernández Fisac Robo-MUTUAL: Robotic Multimodal Task Specification via Unimodal Learning
Jianxiong Li, Zhihao Wang, Jinliang Zheng, Xiaoai Zhou, Guanming Wang, Guanglu Song, Yu Liu, Jingjing Liu, Ya-Qin Zhang, Junzhi Yu, Xianyuan Zhan Robust Multi-View Co-Expression Network Inference
Teodora Pandeva, Martijs Johannes Jonker, Leendert Hamoen, Joris Mooij, Patrick Forré Robust Offline Learning via Adversarial World Models
Uljad Berdica, Kelvin Li, Michael Beukman, Alexander David Goldie, Perla Maiolino, Jakob Nicolaus Foerster ROCKET-1: Master Open-World Interaction with Visual-Temporal Context Prompting
Shaofei Cai, Zihao Wang, Kewei Lian, Zhancun Mu, Xiaojian Ma, Anji Liu, Yitao Liang RoCoFT: Efficient Finetuning of Large Language Models with Row-Column Updates
Md Kowsher, Tara Esmaeilbeig, Chun-Nam Yu, Mojtaba Soltanalian, Niloofar Yousefi Rule-Guided Language Model Alignment for Text Generation Management in Industrial Use Cases
Shunichi Akatsuka, Aman Kumar, Xian Yeow Lee, Lasitha Vidyaratne, Dipanjan Dipak Ghosh, Ahmed K. Farahat S2L-RM: Short-to-Long Reward Modeling
Changyu Chen, Zichen Liu, Haonan Wang, Chao Du, Tianyu Pang, Qian Liu, Arunesh Sinha, Pradeep Varakantham, Min Lin SAC-GLAM: Improving Online RL for LLM Agents with Soft Actor-Critic and Hindsight Relabeling
Loris Gaven, Thomas Carta, Clément Romac, Olivier Sigaud, Sylvain Lamprier, Pierre-Yves Oudeyer SafetyAnalyst: Interpretable, Transparent, and Steerable LLM Safety Moderation
Jing-Jing Li, Valentina Pyatkin, Max Kleiman-Weiner, Liwei Jiang, Nouha Dziri, Anne Collins, Jana Schaich Borg, Maarten Sap, Yejin Choi, Sydney Levine SAGE-RT: Synthetic Alignment Data Generation for Safety Evaluation and Red Teaming
Anurakt Kumar, Divyanshu Kumar, Jatan Loya, Nitin Aravind Birur, Tanay Baswa, Sahil Agarwal, Prashanth Harshangi SALT: Sales Autocompletion Linked Business Tables Dataset
Tassilo Klein, Clemens Biehl, Margarida Costa, Andre Sres, Jonas Kolk, Johannes Hoffart Sample Compression Hypernetworks: From Generalization Bounds to Meta-Learning
Benjamin Leblanc, Mathieu Bazinet, Nathaniel D'Amours, Alexandre Drouin, Pascal Germain Sample-Efficient Alignment for LLMs
Zichen Liu, Changyu Chen, Chao Du, Wee Sun Lee, Min Lin Sampling Language from Latent System 2 Reasoning
Celine Lee, Md Arafat Sultan, Tahira Naseem, Alexander M Rush, Ramón Fernandez Astudillo Sandbag Detection Through Model Impairment
Cameron Tice, Philipp Alexander Kreer, Nathan Helm-Burger, Prithviraj Singh Shahani, Fedor Ryzhenkov, Teun van der Weij, Felix Hofstätter, Jacob Haimes Scalable and Interpretable Quantum Natural Language Processing: An Implementation on Trapped Ions
Tiffany Duneau, Saskia Bruhn, Gabriel Matos, Tuomas Laakkonen, Katerina Saiti, Anna Pearson, Konstantinos Meichanetzidis, Bob Coecke Scalable Universal T-Cell Receptor Embeddings from Adaptive Immune Repertoires
Paidamoyo Chapfuwa, Ilker Demirel, Lorenzo Pisani, Javier Zazo, Elon Portugaly, Jabran Zahid, Julia Greissl Scale-Consistent Learning with Neural Operators
Zongyi Li, Samuel Lanthaler, Catherine Deng, Yixuan Wang, Kamyar Azizzadenesheli, Anima Anandkumar Scaling Dense Representations for Single Cell Gene Expression with Transcriptome-Scale Context
Nicholas Ho, Caleb Ellington, Jinyu Hou, Sohan Addagudi, Shentong Mo, Tianhua Tao, Dian Li, Yonghao Zhuang, Hongyi Wang, Xingyi Cheng, Le Song, Eric P. Xing Scaling-Laws for Large Time-Series Models
Justin Alsing, Thomas Edwards, Benjamin Dan Wandelt, James Alvey, Nam H Nguyen SCAR: Sparse Conditioned Autoencoders for Concept Detection and Steering in LLMs
Ruben Härle, Felix Friedrich, Manuel Brack, Björn Deiseroth, Patrick Schramowski, Kristian Kersting SciDFM: A Large Language Model with Mixture-of-Experts for Science
Liangtai Sun, Danyu Luo, Da Ma, Zihan Zhao, Baocai Chen, Zhennan Shen, Su Zhu, Lu Chen, Xin Chen, Kai Yu Scientific Knowledge Graph and Ontology Generation Using Open Large Language Models
Alexandru Oarga, Matthew Hart, Andres M Bran, Magdalena Lederbauer, Philippe Schwaller Scientific Knowledge Graph and Ontology Generation Using Open Large Language Models
Alexandru Oarga, Matthew Hart, Andres M Bran, Magdalena Lederbauer, Philippe Schwaller SciLitLLM: How to Adapt LLMs for Scientific Literature Understanding
Sihang Li, Jin Huang, Jiaxi Zhuang, Yaorui Shi, Xiaochen Cai, Mingjun Xu, Xiang Wang, Linfeng Zhang, Guolin Ke, Hengxing Cai SciRIFF: A Resource to Enhance Language Model Instruction-Following over Scientific Literature
David Wadden, Kejian Shi, Jacob Morrison, Aakanksha Naik, Shruti Singh, Nitzan Barzilay, Kyle Lo, Tom Hope, Luca Soldaini, Zejiang Shen, Doug Downey, Hannaneh Hajishirzi, Arman Cohan SEAL: Suite for Evaluating API-Use of LLMs
Woojeong Kim, Ashish Jagmohan, Aditya Vempaty SeCom: On Memory Construction and Retrieval for Personalized Conversational Agents
Zhuoshi Pan, Qianhui Wu, Huiqiang Jiang, Xufang Luo, Hao Cheng, Dongsheng Li, Yuqing Yang, Chin-Yew Lin, H. Vicky Zhao, Lili Qiu, Jianfeng Gao Second-Order Forward-Mode Automatic Differentiation for Optimization
Adam D. Cobb, Atilim Gunes Baydin, Barak A. Pearlmutter, Susmit Jha SeisLM: A Foundation Model for Seismic Waveforms
Tianlin Liu, Jannes Münchmeyer, Laura Laurenti, Chris Marone, Maarten V. de Hoop, Ivan Dokmanić Selective Preference Aggregation
Shreyas Kadekodi, Hayden McTavish, Berk Ustun Selective Preference Aggregation
Shreyas Kadekodi, Hayden McTavish, Berk Ustun Self Supervised Learning Using Controlled Diffusion Image Augmentation
Judah A Goldfeder, Patrick Minwan Puma, Gabriel Guo, Gabriel Guerra Trigo, Hod Lipson SELF-BART : A Transformer-Based Molecular Representation Model Using SELFIES
Indra Priyadarsini, Seiji Takeda, Lisa Hamada, Emilio Vital Brazil, Eduardo Soares, Hajime Shinohara Self-Improvement in Language Models: The Sharpening Mechanism
Audrey Huang, Adam Block, Dylan J Foster, Dhruv Rohatgi, Cyril Zhang, Max Simchowitz, Jordan T. Ash, Akshay Krishnamurthy Self-Play Preference Optimization for Language Model Alignment
Yue Wu, Zhiqing Sun, Huizhuo Yuan, Kaixuan Ji, Yiming Yang, Quanquan Gu Self-Preference Bias in LLM-as-a-Judge
Koki Wataoka, Tsubasa Takahashi, Ryokan Ri SELFGOAL: Your Language Agents Already Know How to Achieve High-Level Goals
Ruihan Yang, Jiangjie Chen, Yikai Zhang, Siyu Yuan, Aili Chen, Kyle Richardson, Yanghua Xiao, Deqing Yang Semantically Safe Robot Manipulation: From Semantic Scene Understanding to Motion Safeguards
Lukas Brunke, Yanni Zhang, Ralf Römer, Jack Naimer, Nikola Staykov, SiQi Zhou, Angela P. Schoellig Sentiment Reasoning for Healthcare
Khai-Nguyen Nguyen, Khai Le-Duc, Bach Phan Tat, Le Duy, Jerry Ngo, Long Vo-Dang, Anh Totti Nguyen, Hy Truong Son SepONet: Efficient Large-Scale Physics-Informed Operator Learning
Xinling Yu, Sean Hooten, Ziyue Liu, Yequan Zhao, Marco Fiorentino, Thomas Van Vaerenbergh, Zheng Zhang Shh, Don't Say That! Domain Certification in LLMs
Cornelius Emde, Preetham Arvind, Alasdair Paren, Maxime Kayser, Tom Rainforth, Thomas Lukasiewicz, Philip Torr, Adel Bibi ShowUI: One Vision-Language-Action Model for Generalist GUI Agent
Kevin Qinghong Lin, Linjie Li, Difei Gao, Zhengyuan Yang, Zechen Bai, Weixian Lei, Lijuan Wang, Mike Zheng Shou Shrinking the Size of Deep Extreme Multi-Label Classification
Marco Bornstein, Tahseen Rabbani, Brian Joseph Gravelle, Furong Huang Signals in the Cells: Multimodal and Contextualized Machine Learning Foundations for Therapeutics
Alejandro Velez-Arce, Kexin Huang, Michelle M Li, Xiang Lin, Wenhao Gao, Bradley Pentelute, Tianfan Fu, Manolis Kellis, Marinka Zitnik SignAttention: On the Interpretability of Transformer Models for Sign Language Translation
Pedro Alejandro Dal Bianco, Oscar Agustín Stanchi, Facundo Manuel Quiroga, Franco Ronchetti, Enzo Ferrante SignAttention: On the Interpretability of Transformer Models for Sign Language Translation
Oscar Agustín Stanchi, Pedro Alejandro Dal Bianco, Facundo Manuel Quiroga, Franco Ronchetti, Enzo Ferrante Sim2Real Transfer for Catalyst Activity Prediction
Yuta Yahagi, Kiichi Obuchi, Fumihiko Kosaka, Kota Matsui Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction
Karina Zadorozhny, Kangway V. Chuang, Bharath Sathappan, Ewan Wallace, Vishnu Sresht, Colin A Grambow Simple and Effective Masked Diffusion Language Models
Subham Sekhar Sahoo, Marianne Arriola, Aaron Gokaslan, Yair Schiff, Edgar Mariano Marroquin, Justin T Chiu, Alexander M Rush, Volodymyr Kuleshov Simplicity Prevails: Rethinking Negative Preference Optimization for LLM Unlearning
Chongyu Fan, Jiancheng Liu, Licong Lin, Jinghan Jia, Ruiqi Zhang, Song Mei, Sijia Liu Simulating User Agents for Embodied Conversational AI
Daniel Philipov, Vardhan Dongre, Gokhan Tur, Dilek Hakkani Tur Simulation System Towards Solving Societal-Scale Manipulation
Maximilian Puelma Touzel, Sneheel Sarangi, Austin Welch, Gayatri K, Dan Zhao, Zachary Yang, Hao Yu, Tom Gibbs, Ethan Kosak-Hine, Andreea Musulan, Camille Thibault, Reihaneh Rabbany, Jean-François Godbout, Kellin Pelrine Simulation System Towards Solving Societal-Scale Manipulation
Maximilian Puelma Touzel, Sneheel Sarangi, Austin Welch, Gayatri K, Dan Zhao, Zachary Yang, Hao Yu, Tom Gibbs, Ethan Kosak-Hine, Andreea Musulan, Camille Thibault, Busra Tugce Gurbuz, Reihaneh Rabbany, Jean-François Godbout, Kellin Pelrine Since Faithfulness Fails: The Performance Limits of Neural Causal Discovery
Mateusz Olko, Mateusz Gajewski, Joanna Wojciechowska, Łukasz Kuciński, Mikołaj Morzy, Piotr Sankowski, Piotr Miłoś Sirius: Contextual Sparsity with Correction for Efficient LLM
Yang Zhou, Zhuoming Chen, Zhaozhuo Xu, Xi Victoria Lin, Beidi Chen Situated Instruction Following Under Ambiguous Human Intent
So Yeon Min, Xavier Puig, Devendra Singh Chaplot, Tsung-Yen Yang, Akshara Rai, Priyam Parashar, Russ Salakhutdinov, Yonatan Bisk, Roozbeh Mottaghi Situated Instruction Following Under Ambiguous Human Intent
So Yeon Min, Xavier Puig, Devendra Singh Chaplot, Tsung-Yen Yang, Akshara Rai, Priyam Parashar, Russ Salakhutdinov, Yonatan Bisk, Roozbeh Mottaghi SkewAct: Red Teaming Large Language Models via Activation-Skewed Adversarial Prompt Optimization
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Yaozhong Shi, Angela F Gao, Zachary E Ross, Kamyar Azizzadenesheli Unlearning In- vs. Out-of-Distribution Data in LLMs Under Gradient-Based Methods
Teodora Baluta, Pascal Lamblin, Daniel Tarlow, Fabian Pedregosa, Gintare Karolina Dziugaite Unlearning Tabular Data Without a "Forget Set''
Aviraj Newatia, Michael Cooper, Rahul Krishnan Unlocking State-Tracking in Linear RNNs Through Negative Eigenvalues
Riccardo Grazzi, Julien Siems, Jörg K.H. Franke, Arber Zela, Frank Hutter, Massimiliano Pontil UnoLoRA: Single Low-Rank Adaptation for Efficient Multitask Fine-Tuning
Akash Kamalesh, Anirudh Lakhotia, H S Nischal, Prerana Sanjay Kulkarni, Gowri Srinivasa Unsupervised Causal Abstraction
Yuchen Zhu, Sergio Hernan Garrido Mejia, Bernhard Schölkopf, Michel Besserve Unveiling and Manipulating Concepts in Time Series Foundation Models
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Kai Jappe Sandbrink, Brian Christian, Linas Nasvytis, Christian Schroeder de Witt, Patrick Butlin Using LLMs to Model the Beliefs and Preferences of Targeted Populations
Keiichi Namikoshi, Alexandre Filipowicz, David Ayman Shamma, Rumen I Iliev, Candice L Hogan, Nikos Arechiga Using Rashomon Sets for Robust Active Learning
Simon Dovan Nguyen, Tyler McCormick, Kentaro Hoffman VALL-E R: Robust and Efficient Zero-Shot Text-to-Speech Synthesis via Monotonic Alignment
Bing Han, Long Zhou, Shujie Liu, Sanyuan Chen, Lingwei Meng, Yanmin Qian, Eric Liu, Sheng Zhao, Jinyu Li, Furu Wei Value Alignment from Unstructured Text
Inkit Padhi, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Manish Nagireddy, Pierre Dognin, Kush R. Varshney Value-Aligned Imitation via Focused Satisficing
Rushit N. Shah, Nikolaos Agadakos, Synthia Sasulski, Ali Farajzadeh, Sanjiban Choudhury, Brian D Ziebart Variational Bayes Gaussian Splatting
Toon Van de Maele, Ozan Catal, Alexander Tschantz, Christopher Buckley, Tim Verbelen Variational Best-of-N Alignment
Afra Amini, Tim Vieira, Elliott Ash, Ryan Cotterell Variational Last Layers for Bayesian Optimization
Paul Brunzema, Mikkel Jordahn, John Willes, Sebastian Trimpe, Jasper Snoek, James Harrison Variational Low-Rank Adaptation Using IVON
Bai Cong, Nico Daheim, Yuesong Shen, Daniel Cremers, Rio Yokota, Mohammad Emtiyaz Khan, Thomas Möllenhoff Variational Search Distributions
Daniel M. Steinberg, Rafael Oliveira, Cheng Soon Ong, Edwin V. Bonilla VCR: Visual Caption Restoration
Tianyu Zhang, Suyuchen Wang, Lu Li, Ge Zhang, Perouz Taslakian, Sai Rajeswar, Jie Fu, Bang Liu, Yoshua Bengio Verification Methods for International AI Agreements
Akash Wasil, Thomas David Reed, Jack William Miller, Peter Barnett VerMCTS: Synthesizing Multi-Step Programs Using a Verifier, a Large Language Model, and Tree Search
David Brandfonbrener, Simon Henniger, Sibi Raja, Tarun Prasad, Chloe R Loughridge, Federico Cassano, Sabrina Ruixin Hu, Jianang Yang, William E. Byrd, Robert Zinkov, Nada Amin VIA: A Spatiotemporal Video Adaptation Framework for Global and Local Video Editing
Jing Gu, Yuwei Fang, Ivan Skorokhodov, Peter Wonka, Xinya Du, Sergey Tulyakov, Xin Eric Wang Video Representation Learning of Cardiac MRI for Genetic Discovery
Matt Sooknah, Sivaramakrishnan Sankarapandian, Ramprakash Srinivasan, Johannes Riegler, Jun Xu VideoPhy: Evaluating Physical Commonsense for Video Generation
Hritik Bansal, Zongyu Lin, Tianyi Xie, Zeshun Zong, Michal Yarom, Yonatan Bitton, Chenfanfu Jiang, Yizhou Sun, Kai-Wei Chang, Aditya Grover VideoWebArena: Evaluating Long Context Multimodal Agents with Video Understanding Web Tasks
Lawrence Keunho Jang, Yinheng Li, Charles Ding, Justin Lin, Paul Pu Liang, Dan Zhao, Rogerio Bonatti, Kazuhito Koishida VinePPO: Accurate Credit Assignment in RL for LLM Mathematical Reasoning
Amirhossein Kazemnejad, Milad Aghajohari, Eva Portelance, Alessandro Sordoni, Siva Reddy, Aaron Courville, Nicolas Le Roux Virtual Personas for Language Models via an Anthology of Backstories
Suhong Moon, Marwa Abdulhai, Minwoo Kang, Joseph Suh, Widyadewi Soedarmadji, Eran Kohen Behar, David Chan Virtual Personas for Language Models via an Anthology of Backstories
Suhong Moon, Marwa Abdulhai, Minwoo Kang, Joseph Suh, Widyadewi Soedarmadji, Eran Kohen Behar, David Chan Vision Foundation Models: Can They Be Applied to Astrophysics Data?
Erica Lastufka, Mariia Drozdova, Vitaliy Kinakh, Slava Voloshynovskiy Visual Language Alignment Tuning
Le Zhang, Qian Yang, Aishwarya Agrawal Visual Sketchpad: Sketching as a Visual Chain of Thought for Multimodal Language Models
Yushi Hu, Weijia Shi, Xingyu Fu, Dan Roth, Mari Ostendorf, Luke Zettlemoyer, Noah A. Smith, Ranjay Krishna Visualizing Linear RNNs Through Unrolling
Josue Casco-Rodriguez, Tyler Burley, Cj Barberan, Ahmed Imtiaz Humayun, Randall Balestriero, Richard Baraniuk Visualizing Loss Functions as Topological Landscape Profiles
Caleb Geniesse, Jiaqing Chen, Tiankai Xie, Ge Shi, Yaoqing Yang, Dmitriy Morozov, Talita Perciano, Michael W. Mahoney, Ross Maciejewski, Gunther H. Weber ViTally Consistent: Scaling Biological Representation Learning for Cell Microscopy
Kian Kenyon-Dean, Zitong Jerry Wang, John Urbanik, Konstantin Donhauser, Jason Hartford, Saber Saberian, Nil Sahin, Ihab Bendidi, Safiye Celik, Marta Fay, Juan Sebastián Rodríguez Vera, Imran S Haque, Oren Kraus VRVQ: Variable Bitrate Residual Vector Quantization for Audio Compression
Yunkee Chae, Woosung Choi, Yuhta Takida, Junghyun Koo, Yukara Ikemiya, Zhi Zhong, Kin Wai Cheuk, Marco A. Martínez-Ramírez, Kyogu Lee, Wei-Hsiang Liao, Yuki Mitsufuji Warmstarting for Scaling Language Models
Neeratyoy Mallik, Maciej Janowski, Johannes Hog, Herilalaina Rakotoarison, Aaron Klein, Josif Grabocka, Frank Hutter WASH: Train Your Ensemble with Communication-Efficient Weight Shuffling, Then Average
Louis Fournier, Adel Nabli, Masih Aminbeidokhti, Marco Pedersoli, Eugene Belilovsky, Edouard Oyallon Ways Forward for Global AI Benefit Sharing
Sam Manning, Claire Dennis, Stephen Clare We Need Far Fewer Unique Filters than We Thought
Zahra Babaiee, Peyman Kiasari, Daniela Rus, Radu Grosu Weak-to-Strong Confidence Prediction
Yukai Yang, Tracy Yixin Zhu, Marco Morucci, Tim G. J. Rudner Weak-to-Strong Confidence Prediction
Tracy Yixin Zhu, Yukai Yang, Marco Morucci, Tim G. J. Rudner Weighted Diversified Sampling for Efficient Data-Driven Single-Cell Gene-Gene Interaction Discovery
Yifan Wu, Yuntao Yang, Zirui Liu, Zhao Li, Khushbu Pahwa, Rongbin Li, Wenjin Zheng, Xia Hu, Zhaozhuo Xu Weighted Diversified Sampling for Efficient Data-Driven Single-Cell Gene-Gene Interaction Discovery
Yifan Wu, Yuntao Yang, Zirui Liu, Zhao Li, Khushbu Pahwa, Rongbin Li, Wenjin Zheng, Xia Hu, Zhaozhuo Xu What Do We Learn from Inverting CLIP Models?
Hamid Kazemi, Atoosa Chegini, Jonas Geiping, Soheil Feizi, Tom Goldstein What Makes for Good Image Captions?
Delong Chen, Samuel Cahyawijaya, Etsuko Ishii, Ho Shu Chan, Yejin Bang, Pascale Fung What Should a Neuron Aim for? Designing Local Objective Functions Based on Information Theory
Andreas Christian Schneider, Valentin Neuhaus, David Alexander Ehrlich, Alexander S Ecker, Abdullah Makkeh, Viola Priesemann, Michael Wibral What You See Is What You Get: Entity-Aware Summarization for Reliable Sponsored Search
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Rylan Schaeffer, Dan Valentine, Luke Bailey, James Chua, Cristobal Eyzaguirre, Zane Durante, Joe Benton, Brando Miranda, Henry Sleight, Tony Tong Wang, John Hughes, Rajashree Agrawal, Mrinank Sharma, Scott Emmons, Sanmi Koyejo, Ethan Perez When Do Universal Image Jailbreaks Transfer Between Vision-Language Models?
Rylan Schaeffer, Dan Valentine, Luke Bailey, James Chua, Cristobal Eyzaguirre, Zane Durante, Joe Benton, Brando Miranda, Henry Sleight, Tony Tong Wang, John Hughes, Rajashree Agrawal, Mrinank Sharma, Scott Emmons, Sanmi Koyejo, Ethan Perez When Do We Not Need Larger Vision Models?
Baifeng Shi, Ziyang Wu, Maolin Mao, Xin Wang, Trevor Darrell WikiDO: A New Benchmark Evaluating Cross-Modal Retrieval for Vision-Language Models
Pavan Kalyan Tankala, Piyush Singh Pasi, Sahil Dharod, Azeem Motiwala, Preethi Jyothi, Aditi Chaudhary, Krishna Srinivasan WildFeedback: Aligning LLMs with In-Situ User Interactions and Feedback
Taiwei Shi, Zhuoer Wang, Longqi Yang, Ying-Chun Lin, Zexue He, Mengting Wan, Pei Zhou, Sujay Kumar Jauhar, Xiaofeng Xu, Xia Song, Jennifer Neville Windows Agent Arena: Evaluating Multi-Modal OS Agents at Scale
Rogerio Bonatti, Dan Zhao, Dillon Dupont, Sara Abdali, Yinheng Li, Yadong Lu, Justin Wagle, Kazuhito Koishida, Arthur Bucker, Lawrence Keunho Jang, Zheng Hui WISE: Rethinking the Knowledge Memory for Lifelong Model Editing of Large Language Models
Peng Wang, Zexi Li, Ningyu Zhang, Ziwen Xu, Yunzhi Yao, Yong Jiang, Pengjun Xie, Fei Huang, Huajun Chen Wolf: Captioning Everything with a World Summarization Framework
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Vighnesh Subramaniam, Tomaso A Poggio, Boris Katz, Brian Cheung, Andrei Barbu World Models for Web Agents
Hyungjoo Chae, Namyoung Kim, Minju Gwak, Gwanwoo Song, Jihoon Kim, Kai Tzu-iunn Ong, Sunghwan Kim, Dongha Lee, Jinyoung Yeo Worldwide Federated Training of Language Models
Alex Iacob, Lorenzo Sani, Bill Marino, Preslav Aleksandrov, William F. Shen, Nicholas Donald Lane WyckoffTransformer: Generation of Symmetric Crystals
Nikita Kazeev, Ruiming Zhu, Ignat Romanov, Andrey E Ustyuzhanin, Shuya Yamazaki, Wei Nong, Kedar Hippalgaonkar XoRA: Expander Adapted LoRA Finetuning
Amaljith Ev, Arindam Biswas, Suryam Arnav Kalra, Pabitra Mitra, Biswajit Basu xTED: Cross-Domain Adaptation via Diffusion-Based Trajectory Editing
Haoyi Niu, Qimao Chen, Tenglong Liu, Jianxiong Li, Guyue Zhou, Yi Zhang, Jianming Hu, Xianyuan Zhan Zero-Shot Learning of Causal Models
Divyat Mahajan, Jannes Gladrow, Agrin Hilmkil, Cheng Zhang, Meyer Scetbon Zero-Shot Whole-Body Humanoid Control via Behavioral Foundation Models
Andrea Tirinzoni, Ahmed Touati, Jesse Farebrother, Mateusz Guzek, Anssi Kanervisto, Yingchen Xu, Alessandro Lazaric, Matteo Pirotta ZOOPFL: Exploring Black-Box Foundation Models for Personalized Federated Learning
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