ICLRW 2025
1771 papers
[Tiny] Parameterized Synthetic Text Generation with SimpleStories
Lennart Finke, Thomas Dooms, Mat Allen, Juan Diego Rodriguez, Noa Nabeshima, Dan Braun [Tiny] Understanding the Impact of Data Domain Extraction on Synthetic Data Privacy
Georgi Ganev, Meenatchi Sundaram Muthu Selva Annamalai, Sofiane Mahiou, Emiliano De Cristofaro $\text{CO}_2$-Net: A Physics-Informed Spatio-Temporal Model for Global $\text{CO}_2$ Reconstruction
Hao Zheng, Yuting Zheng, Hanbo Huang, Chaofan Sun, Lin Liu, Enhui Liao, Yi Han, Hao Zhou, Shiyu Liang 2DE: A Probabilistic Method for Differential Expression Across Niches in Spatial Transcriptomics Data
Nathan Levy, Florian Ingelfinger, Artemy Bakulin, Giacomo Cinnirella, Pierre Boyeau, Can Ergen, Nir Yosef 5d Neural Surrogates for Nonlinear Gyrokinetic Simulations of Plasma Turbulence
Gianluca Galletti, Fabian Paischer, Paul Setinek, William Hornsby, Lorenzo Zanisi, Naomi Carey, Stanislas Pamela, Johannes Brandstetter A Benchmark for Scalable Oversight Mechanisms
Abhimanyu Pallavi Sudhir, Jackson Kaunismaa, Arjun Panickssery A Biologically Plausible Associative Memory Network
Mohadeseh Shafiei Kafraj, Dmitry Krotov, Brendan A Bicknell, Peter E. Latham A Comprehensive Library for RNA Structure-Function Modeling
Luis Wyss, Vincent Mallet, Wissam Karroucha, Karsten Borgwardt, Carlos Oliver 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 Foundation Model for Simulation-Grade Molecular Electron Densities
Eduardo Soares, Dmitry Zubarev, Victor Yukio Shirasuna, Emilio Vital Brazil, Breno W S R Carvalho, Brandi Ransom, Holt Bui, Krystelle Lionti, Caio Rodrigues Gama, Daniel Djinishian de Briquez A Generalized Protein Design ML Model Enables Generation of Functional De Novo Proteins
Timothy P Riley, Oleg Matusovsky, Mohammad S. Parsa, Pourya Kalantari, Kooshiar Azimian, Kathy Y Wei A Generative Approach to LLM Harmfulness Detection with Red Flag Tokens
Sophie Xhonneux, David Dobre, Mehrnaz Mofakhami, Leo Schwinn, Gauthier Gidel A Guide to Misinformation Detection Data and Evaluation
Camille Thibault, Jacob-Junqi Tian, Gabrielle Péloquin-Skulski, Taylor Lynn Curtis, James Zhou, Florence Laflamme, Yuxiang Guan, Reihaneh Rabbany, Jean-François Godbout, Kellin Pelrine A Guided Design Framework for the Optimization of Therapeutic-like Antibodies
Amy Wang, Zhe Sang, Samuel Don Stanton, Jennifer L. Hofmann, Saeed Izadi, Eliott Park, Jan Ludwiczak, Matthieu Kirchmeyer, Darcy Davidson, Andrew Maier, Tom Pritsky, Nathan C. Frey, Andrew Martin Watkins, Franziska Seeger A Joint Space-Time Encoder for Geographic Time-Series Data
David Mickisch, Konstantin Klemmer, Mélisande Teng, David Rolnick A Large Language Model-Driven Heterogeneous Air-Ground Search Swarm
Jianzhuozhu, Xuran Pu, Jianjie Fang, Zhiyuan Deng, Xueqian Wang, Xinlei Chen A Model Zoo of Vision Transformers
Damian Falk, Léo Meynent, Florence Pfammatter, Konstantin Schürholt, Damian Borth A Model Zoo on Phase Transitions in Neural Networks
Konstantin Schürholt, Léo Meynent, Yefan Zhou, Yaoqing Yang, Damian Borth A Physics-Based Data-Driven Model for CO$_2$ Gas Diffusion Electrodes to Drive Automated Laboratories
Ivan Grega, Félix Therrien, Abhishek Soni, Karry Ocean, Kevan Dettelbach, Ribwar Ahmadi, Mehrdad Mokhtari, Curtis P. Berlinguette, Yoshua Bengio A Pilot Study on the Impact of LLMs on Virtual Tutoring for Low- to Middle-Income Countries
Nguyen Tien Dat, Phi Van Nguyen, Viet Anh Ngo, Long Tri Thai Son, Nguyen Nhat Minh, Long Q. Tran A Self-Improving Coding Agent
Maxime Robeyns, Martin Szummer, Laurence Aitchison A Sociotechnical Perspective on Aligning AI with Pluralistic Human Values
Dalia Ali, Aysenur Kocak, Dora Zhao, Allison Koenecke, Orestis Papakyriakopoulos A Taxonomy of Watermarking Methods for AI-Generated Content
Pierre Fernandez, Hady Elsahar, Sylvestre-Alvise Rebuffi, Tomas Soucek, Valeriu Lacatusu, Tuan Tran, Alexandre Mourachko A Unified Diffusion Bridge Framework via Stochastic Optimal Control
Kaizhen Zhu, Mokai Pan, Yuexin Ma, Yanwei Fu, Jingyi Yu, Jingya Wang, Ye Shi Abg-SciQA: A Dataset for Understanding and Resolving Ambiguity in Scientific Questions
Tiejin Chen, Kuan-Ru Liou, Mithun Shivakoti, Aaryan Gaur, Pragya Kumari, Meiqi Guo, Hua Wei Accelerating Goal-Conditioned RL Algorithms and Research
Michał Bortkiewicz, Władysław Pałucki, Vivek Myers, Tadeusz Dziarmaga, Tomasz Arczewski, Łukasz Kuciński, Benjamin Eysenbach Accelerating Transformer Inference and Training with 2:4 Activation Sparsity
Daniel Haziza, Timothy Chou, Dhruv Choudhary, Jesse Cai, Luca Wehrstedt, Francisco Massa, Jiecao Yu, Geonhwa Jeong, Supriya Rao, Patrick Labatut Accelerating Transformers in Online RL
Daniil Zelezetsky, Alexey Kovalev, Aleksandr Panov ACDiT: Interpolating Autoregressive Conditional Modeling and Diffusion Transformer
Jinyi Hu, Shengding Hu, Yuxuan Song, Yufei Huang, Mingxuan Wang, Hao Zhou, Zhiyuan Liu, Wei-Ying Ma, Maosong Sun Achieving Human Level Competitive Robot Table Tennis
David B D'Ambrosio, Saminda Wishwajith Abeyruwan, Laura Graesser, Atil Iscen, Heni Ben Amor, Alex Bewley, Barney Reed, Krista Reymann, Leila Takayama, Yuval Tassa, Krzysztof Marcin Choromanski, Erwin Coumans, Deepali Jain, Navdeep Jaitly, Natasha Jaques, Satoshi Kataoka, Yuheng Kuang, Nevena Lazic, Reza Mahjourian, Sherry Moore, Kenneth Oslund, Anish Shankar, Vikas Sindhwani, Vincent Vanhoucke, Grace Vesom, Peng Xu, Pannag R Sanketi Active Human Feedback Collection via Neural Contextual Dueling Bandits
Arun Verma, Xiaoqiang Lin, Zhongxiang Dai, Daniela Rus, Bryan Kian Hsiang Low Active Learning on Synthons for Molecular Design
Tom George Grigg, Mason Burlage, Oliver Brook Scott, Dominique Sydow, Liam Wilbraham Adapting a World Model for Trajectory Following in a 3D Game
Marko Tot, Shu Ishida, Abdelhak Lemkhenter, David Bignell, Pallavi Choudhury, Chris Lovett, Luis França, Matheus Ribeiro Furtado de Mendonça, Tarun Gupta, Darren Gehring, Sam Devlin, Sergio Valcarcel Macua, Raluca Georgescu Adaptive Length Image Tokenization via Recurrent Allocation
Shivam Duggal, Phillip Isola, Antonio Torralba, William T. Freeman Adaptive Local Training in Federated Learning
Donald Shenaj, Eugene Belilovsky, Pietro Zanuttigh Adaptively-Labeled Vision Datasets via Instance-Level Retrieval
Brandon Trabucco, Rishav Mukherji, Yutong Bai, Ruslan Salakhutdinov AdaPTS: Adapting Univariate Foundation Models to Probabilistic Multivariate Time Series Forecasting
Abdelhakim Benechehab, Vasilii Feofanov, Giuseppe Paolo, Albert Thomas, Maurizio Filippone, Balázs Kégl Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching
Aaron J Havens, Benjamin Kurt Miller, Bing Yan, Carles Domingo-Enrich, Anuroop Sriram, Daniel S. Levine, Brandon M Wood, Bin Hu, Brandon Amos, Brian Karrer, Xiang Fu, Guan-Horng Liu, Ricky T. Q. Chen AdS-GNN - A Conformally Equivariant Graph Neural Network
Maksim Zhdanov, Nabil Iqbal, Erik J Bekkers, Patrick Forré Adversarial Attacks on Data Attribution
Xinhe Wang, Pingbang Hu, Junwei Deng, Jiaqi W. Ma Adversarial Robustness in Parameter-Space Classifiers
Tamir Shor, Ethan Fetaya, Chaim Baskin, Alex M. Bronstein AegisLLM: Scaling Agentic Systems for Self-Reflective Defense in LLM Security
Zikui Cai, Shayan Shabihi, Bang An, Zora Che, Brian R. Bartoldson, Bhavya Kailkhura, Tom Goldstein, Furong Huang AffinityFlow: Guided Flows for Antibody Affinity Maturation
Can Chen, Karla-Luise Herpoldt, Chenchao Zhao, Zichen Wang, Marcus D. Collins, Shang Shang, Ron Benson 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 Agentic Knowledgeable Self-Awareness
Shuofei Qiao, Zhisong Qiu, Baochang Ren, Xiaobin Wang, Xiangyuan Ru, Ningyu Zhang, Xiang Chen, Yong Jiang, Pengjun Xie, Fei Huang, Huajun Chen Aguvis: Unified Pure Vision Agents for Autonomous GUI Interaction
Yiheng Xu, Zekun Wang, Junli Wang, Dunjie Lu, Tianbao Xie, Amrita Saha, Doyen Sahoo, Tao Yu, Caiming Xiong AI Systematically Rewires the Flow of Ideas
Zhonghao He, Tianyi Qiu, Tao Lin, Moshe Glickman, Atoosa Kasirzadeh, John Wihbey, Max Kleiman-Weiner AI-Enhanced Semantic Feature Norms for 786 Concepts
Siddharth Suresh, Kushin Mukherjee, Tyler Giallanza, Xizheng Yu, Mia Patil, Jonathan D. Cohen, Timothy T. Rogers AI-Guided Data-Scarce Engineering of RfxCas13d to Create a Cell Selection Tool
Aviv Spinner, Ayush Noori, Debora Susan Marks, George Church, Lisa Maria Riedmayr AI-Powered Virtual Tissues from Spatial Proteomics for Clinical Diagnostics and Biomedical Discovery
Johann Wenckstern, Eeshaan Jain, Kiril Vasilev, Matteo Pariset, Andreas Wicki, Gabriele Gut, Charlotte Bunne AIDE: Agentically Improve Visual Language Model with Domain Experts
Ming-Chang Chiu, Fuxiao Liu, Karan Sapra, Andrew Tao, Yaser Yacoob, Xuezhe Ma, Zhiding Yu, Guilin Liu Aioli: A Unified Optimization Framework for Language Model Data Mixing
Mayee F Chen, Michael Y. Hu, Nicholas Lourie, Kyunghyun Cho, Christopher Re AirExo-2: Scaling up Generalizable Robotic Imitation Learning with Low-Cost Exoskeletons
Hongjie Fang, Chenxi Wang, Yiming Wang, Jingjing Chen, Shangning Xia, Jun Lv, Zihao He, Xiyan Yi, Yunhan Guo, Xinyu Zhan, Lixin Yang, Weiming Wang, Cewu Lu, Hao-Shu Fang Algorithm Discovery with LLMs: Evolutionary Search Meets Reinforcement Learning
Anja Šurina, Amin Mansouri, Amal Seddas, Maryna Viazovska, Emmanuel Abbe, Caglar Gulcehre AlignVLM: Bridging Vision and Language Latent Spaces for Multimodal Understanding
Ahmed Masry, Juan A. Rodriguez, Tianyu Zhang, Suyuchen Wang, Chao Wang, Aarash Feizi, Akshay Kalkunte Suresh, Abhay Puri, Xiangru Jian, Pierre-Andre Noel, Sathwik Tejaswi Madhusudhan, Marco Pedersoli, Bang Liu, Nicolas Chapados, Yoshua Bengio, Enamul Hoque, Christopher Pal, Issam H. Laradji, David Vazquez, Perouz Taslakian, Spandana Gella, Sai Rajeswar All It Takes Is One Prompt: An Autonomous LLM-MA System
Qian Wang, Tianyu Wang, Zhenheng Tang, Qinbin Li, Nuo Chen, Jingsheng Liang, Bingsheng He All-Atom Diffusion Transformers: Unified Generative Modelling of Molecules and Materials
Chaitanya K. Joshi, Xiang Fu, Yi-Lun Liao, Vahe Gharakhanyan, Benjamin Kurt Miller, Anuroop Sriram, Zachary Ward Ulissi All-Atom Protein Generation with Latent Diffusion
Amy X. Lu, Wilson Yan, Sarah A Robinson, Simon Kelow, Kevin K Yang, Vladimir Gligorijevic, Kyunghyun Cho, Richard Bonneau, Pieter Abbeel, Nathan C. Frey AlphaGo or Beta-hCG: A Reinforcement Learning Framework for Assisted Conception
Simon Hanassab, Elizaveta Sheremetyeva, Sonali Parbhoo, Scott Nelson, Professor Waljit Dhillo, Thomas Heinis, Ali Abbara AlphaGo or Beta-hCG: A Reinforcement Learning Framework for Assisted Conception
Simon Hanassab, Elizaveta Sheremetyeva, Sonali Parbhoo, Scott M. Nelson, Waljit S. Dhillo, Ali Abbara, Thomas Heinis AMPO: Active Multi Preference Optimization for Self-Play Preference Selection
Taneesh Gupta, Rahul Madhavan, Xuchao Zhang, Chetan Bansal, Saravan Rajmohan An Architecture Search Framework for Inference-Time Techniques
Jon Saad-Falcon, Adrian Gamarra Lafuente, Shlok Natarajan, Nahum Maru, Hristo Todorov, Etash Kumar Guha, E. Kelly Buchanan, Mayee F Chen, Neel Guha, Christopher Re, Azalia Mirhoseini An Evaluation of Unconditional 3D Molecular Generation Methods
Martin Buttenschoen, Yael Ziv, Garrett M Morris, Charlotte Deane Antibody Design Using Preference Optimization and Structural Inference
Archit Vasan, Gautham Dharuman, Ozan Gokdemir, Heng Ma, Arvind Ramanathan APPA : Agentic Preformulation Pathway Assistant
Julius Lange, Leonid Komissarov, Nicole Wyttenbach, Andrea Anelli Approximate Posteriors in Neural Networks: A Sampling Perspective
Julius Kobialka, Emanuel Sommer, Juntae Kwon, Daniel Dold, David Rügamer Approximations to Worst-Case Data Dropping: Unmasking Failure Modes
Jenny Y. Huang, David R. Burt, Yunyi Shen, Tin D. Nguyen, Tamara Broderick AppVLM: A Lightweight Vision Language Model for Online App Control
Georgios Papoudakis, Thomas Coste, Zhihao Wu, Jianye Hao, Jun Wang, Kun Shao Are Semantic Watermarks for Diffusion Models Resilient to Layout Control?
Denis Lukovnikov, Andreas Müller, Jonas Thietke, Erwin Quiring, Asja Fischer Are Watermarks for Diffusion Models Radioactive?
Jan Dubiński, Michel Meintz, Franziska Boenisch, Adam Dziedzic Are We Done with Object-Centric Learning?
Alexander Rubinstein, Ameya Prabhu, Matthias Bethge, Seong Joon Oh Aria-UI: Visual Grounding for GUI Instructions
Yuhao Yang, Yue Wang, Dongxu Li, Ziyang Luo, Bei Chen, Chao Huang, Junnan Li ASIDE: Architectural Separation of Instructions and Data in Language Models
Egor Zverev, Evgenii Kortukov, Alexander Panfilov, Soroush Tabesh, Sebastian Lapuschkin, Wojciech Samek, Christoph H. Lampert Assessing Dialect Fairness and Robustness of Large Language Models in Reasoning Tasks
Fangru Lin, Shaoguang Mao, Emanuele La Malfa, Valentin Hofmann, Adrian de Wynter, Xun Wang, Si-Qing Chen, Michael J. Wooldridge, Janet B. Pierrehumbert, Furu Wei Assessing Diversity Collapse in Reasoning
Xingyu Dang, Christina Baek, J Zico Kolter, Aditi Raghunathan Assessing Quantization and Efficient Fine-Tuning for Protein Language Models
Sebastian Clancy, Ilan Yaniv Zeisler, Pouriya Bayat, Matthew Xie, Vivian White, Spencer Perkins, Sepehr Bayat, Keith Pardee Assessing Robustness to Spurious Correlations in Post-Training Language Models
Julia Shuieh, Prasann Singhal, Apaar Shanker, John Heyer, George Pu, Samuel Marc Denton Assessing the Capabilities of Large Brainwave Foundation Models
Na Lee, Stylianos Bakas, Konstantinos Barmpas, Yannis Panagakis, Dimitrios Adamos, Nikolaos Laskaris, Stefanos Zafeiriou Associative Memory Learning Through Redundancy Maximization
Mark Blümel, Andreas Christian Schneider, David Alexander Ehrlich, Valentin Neuhaus, Marcel Graetz, Michael Wibral, Abdullah Makkeh, Viola Priesemann Attacking Multimodal OS Agents with Malicious Image Patches
Lukas Aichberger, Alasdair Paren, Philip Torr, Yarin Gal, Adel Bibi Attention Is All You Need for Mixture-of-Depths Routing
Advait Gadhikar, Souptik Kumar Majumdar, Niclas Popp, Piyapat Saranrittichai, Martin Rapp, Lukas Schott Attention Scheme Inspired SoftMax Regression
Zhihang Li, Zhizhou Sha, Zhao Song, Mingda Wan Augmenting X-Ray Astronomical Representations with Scientific Knowledge Through Contrastive Learning
Juan Rafael Martínez-Galarza, Nicolò Oreste Pinciroli Vago, Shivam Raval, Carolina Cuesta-Lazaro, Melanie Weber, David Alvarez-Melis, Alberto Accomazzi, Cecilia Garraffo, Joshua Knutson, Ryan Thill, Christopher B. Green, Imantha Ahangama AutoKaggle: A Multi-Agent Framework for Autonomous Data Science Competitions
Ziming Li, Qianbo Zang, David Ma, Jiawei Guo, Tianyu Zheng, Minghao Liu, Xinyao Niu, Yue Wang, Jian Yang, Jiaheng Liu, Wanjun Zhong, Wangchunshu Zhou, Stephen Huang, Ge Zhang Automated Red Teaming with GOAT: The Generative Offensive Agent Tester
Maya Pavlova, Erik Brinkman, Krithika Iyer, Vítor Albiero, Joanna Bitton, Hailey Nguyen, Cristian Canton Ferrer, Ivan Evtimov, Aaron Grattafiori Automating Evaluation of Creativity in LLMs with Semantic Entropy and Efficient Multi-Agent Judge
Tan Min Sen, Zachary Choy Kit Chun, Swaagat Bikash Saikia, Syed Ali Redha Alsagoff, Banerjee Mohor, Nadya Yuki Wangsajaya, Alvin Chan Aviary: Training Language Agents on Challenging Scientific Tasks
Siddharth Narayanan, James D. Braza, Ryan-Rhys Griffiths, Manvitha Ponnapati, Albert Bou, Jon M Laurent, Ori Kabeli, Geemi Wellawatte, Sam Cox, Samuel G Rodriques, Andrew White BaxBench: Can LLMs Generate Correct and Secure Backends?
Mark Vero, Niels Mündler, Victor Chibotaru, Veselin Raychev, Maximilian Baader, Nikola Jovanović, Jingxuan He, Martin Vechev Bayesian Approximation of RNA Folding Times
Dominik Scheuer, Frederic Runge, Jörg K.H. Franke, Michael T. Wolfinger, Christoph Flamm, Frank Hutter Bayesian Concept Bottleneck Models with LLM Priors
Jean Feng, Avni Kothari, Lucas Zier, Chandan Singh, Yan Shuo Tan Bayesian Invariance Modeling of Multi-Environment Data
Luhuan Wu, Mingzhang Yin, Yixin Wang, John Patrick Cunningham, David Blei Be like a Goldfish, Don't Memorize! Mitigating Memorization in Generative LLMs
Abhimanyu Hans, Yuxin Wen, Neel Jain, John Kirchenbauer, Hamid Kazemi, Prajwal Singhania, Siddharth Singh, Gowthami Somepalli, Jonas Geiping, Abhinav Bhatele, Tom Goldstein BenchAgents: Automated Benchmark Creation with Agent Interaction
Natasha Butt, Varun Chandrasekaran, Neel Joshi, Besmira Nushi, Vidhisha Balachandran Benchmarking Agentic Workflow Generation
Shuofei Qiao, Runnan Fang, Zhisong Qiu, Xiaobin Wang, Ningyu Zhang, Yong Jiang, Pengjun Xie, Fei Huang, Huajun Chen Benchmarking and Optimizing Organism Wide Single-Cell RNA Alignment Methods
Juan Javier Díaz-Mejía, Elias Williams, Octavian Focsa, Dylan Mendonca, Swechha Singh, Brendan Innes, Samuel Cooper Benchmarking Fine-Tuned RNA Language Models for Intronic Branch Point Prediction
Pablo Rodenas Ruiz, Ali Saadat, Timothy T. Tran, Oliver Müller Smedt, Peng Zhang, Jacques Fellay Beyond Adversarial Robustness: Breaking the Robustness-Alignment Trade-Off in Object Recognition
Pinyuan Feng, Drew Linsley, Thibaut Boissin, Alekh Karkada Ashok, Thomas Fel, Stephanie Olaiya, Thomas Serre Beyond Disorder: Unveiling Cooperativeness in Multidirectional Associative Memories
Andrea Alessandrelli, Adriano Barra, Federico Ricci-Tersenghi, Andrea Ladiana, Andrea Lepre Beyond ID Bias: PCA-Guided Dropout for Robust Fine-Tuning
Bo Fei, Xiaocheng Li, ZhangZhiqi, Youchen Qing, Yancong Deng Beyond Scalars: Concept-Based Alignment Analysis in Vision Transformers
Johanna Vielhaben, Dilyara Bareeva, Jim Berend, Wojciech Samek, Nils Strodthoff Beyond Top-K: Structured Sparsification for Compression in Pipeline Parallel
Sameera Ramasinghe, Thalaiyasingam Ajanthan, Gil Avraham, Yan Zuo, Alexander Long BiD: Behavioral Agents in Dynamic Auctions
Weitong Zhang, Chengqi Zang, Mark Schmidt, Richard Blythman Black-Box Adversarial Attacks on LLM-Based Code Completion
Slobodan Jenko, Niels Mündler, Jingxuan He, Mark Vero, Martin Vechev BOLT: Bootstrap Long Chain-of-Thought in Language Models Without Distillation
Bo Pang, Hanze Dong, Jiacheng Xu, Silvio Savarese, Yingbo Zhou, Caiming Xiong Boss LLM: Adaptation via No-Regret Learning
Yu Feng, Avishree Khare, Nghia Nguyen, Sikata Bela Sengupta Brain-Inspired Sparse Training Enables Transformers and LLMs to Perform as Fully Connected
Yingtao Zhang, Jialin Zhao, Wenjing Wu, Ziheng Liao, Umberto Michieli, Carlo Vittorio Cannistraci Breaking Focus: Contextual Distraction Curse in Large Language Models
Yanbo Wang, Zixiang Xu, Yue Huang, Chujie Gao, Siyuan Wu, Jiayi Ye, Xiuying Chen, Pin-Yu Chen, Xiangliang Zhang BridgeVoC: Insights into Using Schrödinger Bridge for Neural Vocoders
Tong Lei, Andong Li, Rilin Chen, Dong Yu, Meng Yu, Jing Lu, Chengshi Zheng Bridging Scales Between Chemical Space and Behavioral Phenotype
Adrien Jouary, J. Miguel Mata, Dean Rance, Gonzalo G. de Polavieja, Christian K. Machens, Michael Orger Bridging the Sim-to-Real Gap for Athletic Loco-Manipulation
Nolan Fey, Gabriel B. Margolis, Martin Peticco, Pulkit Agrawal Bridging the Training-Inference Gap in LLMs by Leveraging Self-Generated Tokens
Zhepeng Cen, Yao Liu, Siliang Zeng, Pratik Chaudhari, Huzefa Rangwala, George Karypis, Rasool Fakoor Bridging Vision Language Model (VLM) Evaluation Gaps with a Framework for Scalable and Cost-Effective Benchmark Generation
Tim Rädsch, Leon Mayer, Simon Pavicic, Ali Emre Kavur, Marcel Knopp, Barış Öztürk, Klaus Maier-Hein, Paul F Jaeger, Fabian Isensee, Annika Reinke, Lena Maier-hein CAMEx: Curvature-Aware Merging of Experts
Dung Viet Nguyen, Minh Hoang Nguyen, Luc Nguyen, Rachel S.Y. Teo, Tan Minh Nguyen, Linh Duy Tran Camp: Combinatorial Engineering of Proteins
Manvitha Ponnapati, Sapna Sinha, Brian Lynch, Edward Boyden, Joseph Jacobson Can 1b LLM Surpass 405b LLM? Rethinking Compute-Optimal Test-Time Scaling
Runze Liu, Junqi Gao, Jian Zhao, Kaiyan Zhang, Xiu Li, Biqing Qi, Wanli Ouyang, Bowen Zhou Can Language Models Falsify? the Need for Inverse Benchmarking
Shiven Sinha, Shashwat Goel, Ponnurangam Kumaraguru, Jonas Geiping, Matthias Bethge, Ameya Prabhu Can Large Language Models Reason? a Characterization via 3-SAT
Rishi Hazra, Gabriele Venturato, Pedro Zuidberg Dos Martires, Luc De Raedt Can LLM Watermarking Robustly Prevent Unauthorized Knowledge Distillation?
Leyi Pan, Aiwei Liu, Shiyu Huang, Yijian Lu, Xuming Hu, Lijie Wen, Irwin King, Philip S. Yu Can Transformers Learn Full Bayesian Inference in Context?
Arik Reuter, Tim G. J. Rudner, Vincent Fortuin, David Rügamer Can Transformers Learn Tasks of Varying Complexity In-Context?
Puneesh Deora, Bhavya Vasudeva, Tina Behnia, Christos Thrampoulidis Can Your Uncertainty Scores Detect Hallucinated Entity?
Min-Hsuan Yeh, Max Kamachee, Seongheon Park, Yixuan Li Captured by Captions: On Memorization and Its Mitigation in CLIP Models
Wenhao Wang, Adam Dziedzic, Grace C. Kim, Michael Backes, Franziska Boenisch Capturing Global Features of Crystals from Their Bond Networks
Qianxiang Ai, Sartaaj Takrim Khan, Senja Barthel, Seyed Mohamad Moosavi CARROT: A Cost Aware Rate Optimal Router
Seamus Somerstep, Felipe Maia Polo, Allysson Flavio Melo de Oliveira, Prattyush Mangal, Mírian Silva, Onkar Bhardwaj, Mikhail Yurochkin, Subha Maity Causal Concept Graph Models: Beyond Causal Opacity in Deep Learning
Gabriele Dominici, Pietro Barbiero, Mateo Espinosa Zarlenga, Alberto Termine, Martin Gjoreski, Giuseppe Marra, Marc Langheinrich Causal Lifting of Neural Representations: Zero-Shot Generalization for Causal Inferences
Riccardo Cadei, Ilker Demirel, Piersilvio De Bartolomeis, Lukas Lindorfer, Sylvia Cremer, Cordelia Schmid, Francesco Locatello Causal Representation Learning and Inference via Mixture-Based Priors
Avinash Kori, Carles Balsells-Rodas, Ben Glocker, Yingzhen Li, Francesco Locatello Causally Reliable Concept Bottleneck Models
Giovanni De Felice, Arianna Casanova, Francesco De Santis, Silvia Santini, Johannes Schneider, Pietro Barbiero, Alberto Termine Chain-of-Thought Reasoning in the Wild Is Not Always Faithful
Iván Arcuschin, Jett Janiak, Robert Krzyzanowski, Senthooran Rajamanoharan, Neel Nanda, Arthur Conmy Challenges of Decomposing Tools in Surgical Scenes Through Disentangling the Latent Representations
Sai Lokesh Gorantla, Raviteja Sista, Apoorva Srivastava, Utpal De, Partha Pratim Chakrabarti, Debdoot Sheet Character-Level Tokenizations as Powerful Inductive Biases for RNA Foundational Models
Adrian Morales-Pastor, Raquel Vázquez-Reza, Miłosz Wieczór, Clàudia Valverde, Manel Gil-Sorribes, Bertran Miquel-Oliver, Alvaro Ciudad Serrano, Alexis Molina Cheap and Effective Personalization of Foundation Language Models for Imitating a User's Writing Style
Armand Mihai Nicolicioiu, Eugenia Iofinova, Andrej Jovanovic, Eldar Kurtic, Mahdi Nikdan, Andrei Panferov, Ilia Markov, Nir N Shavit, Dan Alistarh Chimera: State Space Models Beyond Sequences
Aakash Lahoti, Tanya Marwah, Ratish Puduppully, Albert Gu CleanGen: Mitigating Backdoor Attacks for Generation Tasks in Large Language Models
Yuetai Li, Zhangchen Xu, Fengqing Jiang, Luyao Niu, Dinuka Sahabandu, Bhaskar Ramasubramanian, Radha Poovendran Clifford Group Equivariant Diffusion Models for 3D Molecular Generation
Cong Liu, Sharvaree Vadgama, David Ruhe, Erik J Bekkers, Patrick Forré CMAT: A Multi-Agent Collaboration Tuning Framework for Enhancing Small Language Models
梁学辰, Yangfan He, Meiling Tao, Yinghui Xia, Yijin Wang, Jianhui Wang, Kun Li, Jiayi Su, Tianyu Shi, Jun Wang, Yang Jingsong Co-Optimizing Recommendation and Evaluation for LLM Selection
Tarun Kumar, Cong Xu, Arpit Shah, Baradji Diallo, Martin Foltin, Suparna Bhattacharya CoDe: Blockwise Control for Denoising Diffusion Models
Anuj Singh, Sayak Mukherjee, Ahmad Beirami, Hadi J. Rad Code2JSON: Can a Zero-Shot LLM Extract Code Features for Code RAG?
Aryan Singhal, Rajat Ghosh, Ria Mundra, Harshil Dadlani, Debojyoti Dutta CodeEditorBench: Evaluating Code Editing Capability of LLMs
Jiawei Guo, Ziming Li, Xueling Liu, Kaijing Ma, Tianyu Zheng, Zhouliang Yu, Ding Pan, Yizhi Li, Ruibo Liu, Yue Wang, Shuyue Guo, Xingwei Qu, Xiang Yue, Ge Zhang, Wenhu Chen, Jie Fu CoheMark: A Novel Sentence-Level Watermark for Enhanced Text Quality
Junyan Zhang, Shuliang Liu, Aiwei Liu, Yubo Gao, Jungang Li, Xiaojie Gu, Xuming Hu ComfyGen: Prompt-Adaptive Workflows for Text-to-Image Generation
Rinon Gal, Adi Haviv, Yuval Alaluf, Amit Haim Bermano, Daniel Cohen-Or, Gal Chechik Compositional Flows for 3D Molecule and Synthesis Pathway Co-Design
Tony Shen, Seonghwan Seo, Ross Irwin, Kieran Didi, Simon Olsson, Woo Youn Kim, Martin Ester Compressive Meta-Learning
Daniel Mas Montserrat, David Bonet, Maria Perera, Xavier Giró-i-Nieto, Alexander G. Ioannidis Conformal Structured Prediction
Botong Zhang, Shuo Li, Osbert Bastani Conformal Transformations for Symmetric Power Transformers
Saurabh Kumar, Jacob Buckman, Carles Gelada, Xiaowen Zhang Consistency Training with Physical Constraints
Che-Chia Chang, Chen-Yang Dai, Te-Sheng Lin, Ming-Chih Lai, Chieh-Hsin Lai Continuously Tempered Diffusion Samplers
Ezra Erives, Bowen Jing, Peter Holderrieth, Tommi Jaakkola Contrastive Private Data Synthesis via Weighted Multi-PLM Fusion
Tianyuan Zou, Yang Liu, Peng Li, Yufei Xiong, Jianqing Zhang, Jingjing Liu, Ye Ouyang, Xiaozhou Ye, Yaqin Zhang Contrastive Representations for Combinatorial Reasoning
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Yang Zhang, Er Jin, Yanfei Dong, Ashkan Khakzar, Philip Torr, Johannes Stegmaier, Kenji Kawaguchi Emergence of Computational Structure in a Neural Network Physics Simulator
Rohan Hitchcock, Gary W Delaney, Jonathan H. Manton, Richard Scalzo, Jingge Zhu Emergent Misalignment: Narrow Finetuning Can Produce Broadly Misaligned LLMs
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Abhay Gupta, Jacob Cheung, Philip Meng, Shayan Sayyed, Austen Liao, Kevin Zhu, Sean O'Brien Enhanced Continual Learning of Vision-Language Models with Model Fusion
Haoyuan Gao, Zicong Zhang, Yuqi Wei, Linglan Zhao, Guilin Li, Yexin Li, Linghe Kong, Weiran Huang Enhancing DNA Foundation Models to Address Masking Inefficiencies
Monireh Safari, Pablo Andres Millan Arias, Scott C. Lowe, Lila Kari, Angel X Chang, Graham W. Taylor Ensemble Kalman Sampling and Diffusion Prior in Tandem: A Split Gibbs Framework
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Aleksandra Eliseeva, Alexander Kovrigin, Ilia Kholkin, Egor Bogomolov, Yaroslav Zharov Eqm-Mpd: Equivariant On-Manifold Motion Planning Diffusion
Evangelos Chatzipantazis, Nishanth Rao, Kostas Daniilidis EquiJump: Protein Dynamics Simulation via SO(3)-Equivariant Stochastic Interpolants
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Hoang V. Tran, Thieu Vo, An Nguyen The, Tho Tran Huu, Minh-Khoi Nguyen-Nhat, Thanh Tran, Duy-Tung Pham, Tan Minh Nguyen ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models via Error Detection
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Yijiang Li, Bingyang Wang, Tianwei Zhao, Qingying Gao, Hokin Deng, Dezhi Luo Evaluating Speech to Text for Children with Speech Impairment
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Alexander Shypula, Shuo Li, Botong Zhang, Vishakh Padmakumar, Kayo Yin, Osbert Bastani Evaluating Universal Interatomic Potentials for Molecular Dynamics of Real-World Minerals
Sajid Mannan, Carmelo Gonzales, Vaibhav Bihani, Kin Long Kelvin Lee, Nitya Nand Gosvami, Santiago Miret, N M Anoop Krishnan Evaluation of Large Language Models via Coupled Token Generation
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Sawan Patel, Fred Zhangzhi Peng, Keith Fraser, Adam David Friedman, Pranam Chatterjee, Sherwood Yao Evolving RL: Discovering New Activation Functions Using LLMs
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Mahalakshmi Sabanayagam, Lukas Gosch, Stephan Günnemann, Debarghya Ghoshdastidar Exact Unlearning of Finetuning Data via Model Merging at Scale
Kevin Kuo, Amrith Setlur, Kartik Srinivas, Aditi Raghunathan, Virginia Smith Explaining Length Bias in LLM-Based Preference Evaluations
Zhengyu Hu, Linxin Song, Jieyu Zhang, Zheyuan Xiao, Zhengyu Chen, Hui Xiong Exploiting What Trained Models Learn for Making Them Robust to Spurious Correlations Without Group Annotations
Mahdi Ghaznavi, Hesam Asadollahzadeh, Fahimeh Hosseini Noohdani, Soroush Vafaie Tabar, Hosein Hasani, Taha Akbari Alvanagh, Mohammad Hossein Rohban, Mahdieh Soleymani Baghshah Exploring Asynchronism in SWARM Parallelism
Yan Zuo, Gil Avraham, Thalaiyasingam Ajanthan, Sameera Ramasinghe, Alexander Long Exploring Query-to-Reference Mapping Challenges for Automated Single-Cell Atlas-Based Diagnostics
Francesco Craighero, Davide Maspero, Laura Jiménez-Gracia, Sergio Aguilar-Fernández, Maria Boulougouri, Juan C. Nieto, Holger Heyn Exploring Sparse Adapters for Scalable Merging of Parameter Efficient Experts
Samin Yeasar Arnob, Zhan Su, Minseon Kim, Oleksiy Ostapenko, Doina Precup, Lucas Caccia, Alessandro Sordoni Exploring the Pre-Conditions for Memory-Learning Agents
Vishwa Shah, Vishruth Veerendranath, Graham Neubig, Daniel Fried, Zora Zhiruo Wang Extending Prot2Token: Aligning Protein Language Models for Unified and Diverse Protein Prediction Tasks
Mahdi Pourmirzaei, Ye Han, Farzaneh Esmaili, Mohammadreza Pourmirzaeioliaei, Salhuldin Alqarghuli, Kai Chen, Dong Xu Fast and Accurate Antibody Sequence Design via Structure Retrieval
Xingyi Zhang, Kun Xie, Ningqiao Huang, Wei Liu, Peilin Zhao, Sibo Wang, Kangfei Zhao, Biaobin Jiang Fast Gradient Computation for RoPE Attention in Almost Linear Time
Yifang Chen, Jiayan Huo, Xiaoyu Li, Yingyu Liang, Zhenmei Shi, Zhao Song Fast Proxies for LLM Robustness Evaluation
Tim Beyer, Jan Schuchardt, Leo Schwinn, Stephan Günnemann Fast Solvers for Discrete Diffusion Models: Theory and Applications of High-Order Algorithms
Yinuo Ren, Haoxuan Chen, Yuchen Zhu, Wei Guo, Yongxin Chen, Grant M. Rotskoff, Molei Tao, Lexing Ying FastRM: An Efficient and Automatic Explainability Framework for Multimodal Generative Models
Gabriela Ben-Melech Stan, Estelle Aflalo, Man Luo, Shachar Rosenman, Tiep Le, Sayak Paul, Shao-Yen Tseng, Vasudev Lal Federated Circuits: A Unified Framework for Scalable and Efficient Federated Learning
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Cécile Trottet, Michael Krauthammer, Mary-Anne Hartley FetalCSR: Multi-Input Attention Fusion Network for Neural ODE-Based Fetal Cortical Surface Reconstruction
Haoxiang Li, Mingxuan Liu, Xuguang Bai, Yi Liao, Jialan Zheng, Hongjia Yang, Zihan Li, Haibo Qu, Qiyuan Tian Few-Shot Whole Slide Pathology Classification with Multi-Granular Vision-Language Models
Anh-Tien Nguyen, Duy Minh Ho Nguyen, Nghiem Tuong Diep, Trung Quoc Nguyen, Nhat Ho, Jacqueline Michelle Metsch, Miriam Cindy Maurer, Daniel Sonntag, Hanibal Bohnenberger, Anne-Christin Hauschild Feynman-Kac Correctors in Diffusion: Annealing, Guidance, and Product of Experts
Marta Skreta, Tara Akhound-Sadegh, Viktor Ohanesian, Roberto Bondesan, Alan Aspuru-Guzik, Arnaud Doucet, Rob Brekelmans, Alexander Tong, Kirill Neklyudov Finding Sparse Autoencoder Representations of Errors in CoT Prompting
Justin Theodorus, V Swaytha, Shivani Gautam, Adam Ward, Mahir Shah, Cole Blondin, Kevin Zhu Fine-Tuning Pretrained Models with NVIB for Improved Generalisation
Fabio James Fehr, Alina Elena Baia, Xiaoguang Chang, Andrei Catalin Coman, Karl El Hajal, Dina El Zein, Shashi Kumar, Juan Pablo Zuluaga Gomez, Andrea Cavallaro, Damien Teney, James Henderson First-Place Solution to NeurIPS 2024 Invisible Watermark Removal Challenge
Fahad Shamshad, Tameem Bakr, Yahia Salaheldin Shaaban, Noor Hazim Hussein, Karthik Nandakumar, Nils Lukas Fixed-Point RNNs: From Diagonal to Dense in a Few Iterations
Sajad Movahedi, Felix Sarnthein, Nicola Muca Cirone, Antonio Orvieto Flat Posterior for Bayesian Model Averaging
Sungjun Lim, Jeyoon Yeom, Sooyon Kim, Hoyoon Byun, Jinho Kang, Yohan Jung, Jiyoung Jung, Kyungwoo Song FlipAttack: Jailbreak LLMs via Flipping
Yue Liu, Xiaoxin He, Miao Xiong, Jinlan Fu, Shumin Deng, Yingwei Ma, Jiaheng Zhang, Bryan Hooi Flow Along the K-Amplitude for Generative Modeling
Weitao Du, Shuning Chang, Jiasheng Tang, Yu Rong, Fan Wang, Shengchao Liu Flow Matching Neural Processes
Hussen Abu Hamad, Dan Rosenbaum Flow-Based Fragment Identification via Contrastive Learning of Binding Site-Specific Latent Representations
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Julian Cremer, Ross Irwin, Alessandro Tibo, Jon Paul Janet, Simon Olsson, Djork-Arné Clevert Flows Don't Cross in High Dimension
Teodora Reu, Sixtine Dromigny, Michael M. Bronstein, Francisco Vargas FocalLens: Instruction Tuning Enables Zero-Shot Conditional Image Representations
Cheng-Yu Hsieh, Pavan Kumar Anasosalu Vasu, Fartash Faghri, Raviteja Vemulapalli, Chun-Liang Li, Ranjay Krishna, Oncel Tuzel, Hadi Pouransari Foundation Model-Based Data Selection for Dense Prediction Tasks
Niclas Popp, Dan Zhang, Jan Hendrik Metzen, Matthias Hein, Lukas Schott Fractional Brownian Bridges for Aligned Data
Gabriel Nobis, Arina Belova, Maximilian Springenberg, Rembert Daems, Christoph Knochenhauer, Manfred Opper, Tolga Birdal, Wojciech Samek FreeFlow: Latent Flow Matching for Free Energy Difference Estimation
Ege Erdogan, Radoslav Ralev, Mika Rebensburg, Céline Marquet, Leon Klein, Hannes Stark From Dense to Dynamic: Token-Difficulty Driven MoEfication of Pre-Trained LLMs
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Ruben Weijers, Denton Wu, Hannah Betts, Tamara Jacod, Yuxiang Guan, Vidya Sujaya, Kushal Dev, Toshali Goel, William Delooze, Reihaneh Rabbany, Ying Wu, Jean-François Godbout, Kellin Pelrine From Intuition to Understanding: Using AI Peers to Overcome Physics Misconceptions
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Pouriya Bayat, Spencer Perkins, Sebastian Clancy, Sahil Swapnesh Patel, Richard Fei Yin, Krištof Bozovičar, Idorenyin Iwe, Mohammad Simchi, Ilan Yaniv Zeisler, Serena Singh, Vivian White, Matthew Xie, Sean Palter, Keith Pardee From Pseudo-Code to Source Code: A Self-Supervised Search Approach
Adithya Kulkarni, Mohna Chakraborty, Yonas Afewerki Sium, Sai Charishma Valluri, Wei Le, Qi Li FullDiffusion: Diffusion Models Without Time Truncation
Shohei Taniguchi, Masahiro Suzuki, Yusuke Iwasawa, Yutaka Matsuo Fusion of Graph Neural Networks via Optimal Transport
Weronika Ormaniec, Michael Vollenweider, Elisa Hoskovec G-Designer: Architecting Multi-Agent Communication Topologies via Graph Neural Networks
Guibin Zhang, Yanwei Yue, Xiangguo Sun, Guancheng Wan, Miao Yu, Junfeng Fang, Kun Wang, Tianlong Chen, Dawei Cheng Game-Theoretic Regularized Self-Play Alignment of Large Language Models
Xiaohang Tang, Sangwoong Yoon, Seongho Son, Huizhuo Yuan, Quanquan Gu, Ilija Bogunovic GENATATOR: De Novo Gene Annotation with DNA Language Model
Aleksei Shmelev, Artem Shadskiy, Yuri Kuratov, Mikhail Burtsev, Olga Kardymon, Veniamin Fishman Gene Set Function Discovery with LLM-Based Agents and Knowledge Retrieval
Daniela Pinto Veizaga, Aécio Santos, Juliana Freire, Wenke Liu, Sarah Keegan, David Fenyo Generalised Parallel Tempering: Flexible Replica Exchange via Flows and Diffusions
Leo Zhang, Peter Potaptchik, George Deligiannidis, Arnaud Doucet, Hai-Dang Dau, Saifuddin Syed Generalist World Model Pre-Training for Efficient Reinforcement Learning
Yi Zhao, Aidan Scannell, Yuxin Hou, Tianyu Cui, Le Chen, Dieter Büchler, Arno Solin, Juho Kannala, Joni Pajarinen Generalizing to Any Diverse Distribution: Uniformity & Rebalancing
Andreas Loukas, Karolis Martinkus, Edward Wagstaff, Kyunghyun Cho Generating $\pi$-Functional Molecules Using STGG+ with Active Learning
Alexia Jolicoeur-Martineau, Yan Zhang, Boris Knyazev, Aristide Baratin, Cheng-Hao Liu Generating Symbolic World Models via Test-Time Scaling of Large Language Models
Zhouliang Yu, Yuhuan Yuan, Tim Z. Xiao, Fuxiang Frank Xia, Jie Fu, Ge Zhang, Ge Lin, Weiyang Liu Generative Protein Design for Overlapping Genes
Chenling Xu, Jennifer Lynn Chlebek, Jonathan E Allen, Hunter Nisonoff, Dan Mcfarland Park Generative Subgrid-Scale Modeling
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Metod Jazbec, Eliot Wong-Toi, Guoxuan Xia, Dan Zhang, Eric Nalisnick, Stephan Mandt Geneshift: Impact of Different Scenario Shift on Jailbreaking LLM
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Guy Lutsker, Gal Sapir, Smadar Shilo, Jordi Merino, Anastasia Godneva, Jerry R Greenfield, Dorit Samocha-Bonet, Raja Dhir, Francisco Gude, Shie Mannor, Eli Meirom, Gal Chechik, Hagai Rossman, Eran Segal Gradient GA: Gradient Genetic Algorithm for Drug Molecular Design
Chris Zhuang, Debadyuti Mukherjee, Yingzhou Lu, Tianfan Fu, Ruqi Zhang GradMetaNet: An Equivariant Architecture for Learning on Gradients
Yoav Gelberg, Yam Eitan, Aviv Navon, Aviv Shamsian, Theo Putterman, Haggai Maron GRAPE: Generalizing Robot Policy via Preference Alignment
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Shashwat Goel, Joschka Strüber, Ilze Amanda Auzina, Karuna K Chandra, Ponnurangam Kumaraguru, Douwe Kiela, Ameya Prabhu, Matthias Bethge, Jonas Geiping GROQ-Seq: A Collaborative, Open Data Approach to Addressing Protein Function Prediction
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Yue Liu, Hongcheng Gao, Shengfang Zhai, Jun Xia, Tianyi Wu, Zhiwei Xue, Yulin Chen, Kenji Kawaguchi, Jiaheng Zhang, Bryan Hooi Guided Generation of B-Cell Receptors with Conditional Walk-Jump Sampling
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Roman Levin, Valeriia Cherepanova, Abhimanyu Hans, Avi Schwarzschild, Tom Goldstein HDEE: Heterogeneous Domain Expert Ensemble
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Manish Bhattarai, Ryan Barron, Maksim E. Eren, Minh N. Vu, Vesselin Grantcharov, Ismael Boureima, Valentin Stanev, Cynthia Matuszek, Vladimir I Valtchinov, Kim Rasmussen, Boian S. Alexandrov Hebbian Sparse Autoencoder
Nikita Kurdiukov, Anton Razzhigaev HEP-JEPA: A Foundation Model for Collider Physics
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Bo Chen, Chengyue Gong, Xiaoyu Li, Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song, Mingda Wan Higher-Order Molecular Learning: The Cellular Transformer
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Junhao Shi, Qingyuan Chen, Zhaoye Fei, Yining Zheng, Qipeng Guo, Xuanjing Huang, Xipeng Qiu How to Steer LLM Latents for Hallucination Detection?
Seongheon Park, Xuefeng Du, Min-Hsuan Yeh, Haobo Wang, Yixuan Li Human Alignment: How Much We Adapt to LLMs?
Cazalets Tanguy, Ruben Janssens, Tony Belpaeme, Joni Dambre HybriDNA: A Hybird Transformer-Mamba2 Long-Range DNA Language Model
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Jaisidh Singh, Diganta Misra, Boris Knyazev, Antonio Orvieto I-SHEEP: Self-Alignment of LLM from Scratch Through an Iterative Self-Enhancement Paradigm
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Stas Syrota, Yevgen Zainchkovskyy, Johnny Xi, Benjamin Bloem-Reddy, Søren Hauberg Implicit Language Models Are RNNs: Balancing Parallelization and Expressivity
Mark Schöne, Babak Rahmani, Heiner Kremer, Fabian Falck, Hitesh Ballani, Jannes Gladrow Improving Test-Time Search for LLMs with Backtracking Against In-Context Value Verifiers
Anikait Singh, Kushal Arora, Sedrick Keh, Jean Mercat, Tatsunori Hashimoto, Chelsea Finn, Aviral Kumar Improving Transformer World Models for Data-Efficient RL
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Bac Nguyen, Chieh-Hsin Lai, Yuhta Takida, Naoki Murata, Toshimitsu Uesaka, Stefano Ermon, Yuki Mitsufuji Improving Your Model Ranking on Chatbot Arena by Vote Rigging
Rui Min, Tianyu Pang, Chao Du, Qian Liu, Minhao Cheng, Min Lin In Search of Forgotten Domain Generalization
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Gouki Minegishi, Hiroki Furuta, Shohei Taniguchi, Yusuke Iwasawa, Yutaka Matsuo Inducing Group Fairness in Prompt-Based Language Model Decisions
James Atwood, Nino Scherrer, Preethi Lahoti, Ananth Balashankar, Flavien Prost, Ahmad Beirami InductionBench: LLMs Fail in the Simplest Complexity Class
Wenyue Hua, Fei Sun, Liangming Pan, Adam Jardine, William Yang Wang Inference-Time Alignment in Continuous Space
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Fatemeh S. Hashemi Golpayegani, Till Richter, Alejandro Tejada Lapuerta, Lennard Halle, Mohammad Lotfollahi, Fabian J Theis Inverse Problems with Experiment-Guided AlphaFold
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Chen Chen, Enhuai Liu, Daochang Liu, Mubarak Shah, Chang Xu Is Confidence All You Need? Exploring Human-Ai Joint Decision-Making in Spatiotemporal Robotic Tasks
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Alexander Denker, Shreyas Padhy, Francisco Vargas, Johannes Hertrich Joint MoE Scaling Laws: Mixture of Experts Can Be Memory Efficient
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Anne Ouyang, Simon Guo, Simran Arora, Alex L Zhang, William Hu, Christopher Re, Azalia Mirhoseini KGGen: Text to Knowledge Graph
Belinda Mo, Kyssen Yu, Joshua Kazdan, Proud Mpala, Lisa Yu, Chris Cundy, Charilaos Kanatsoulis, Sanmi Koyejo Kinetic Langevin Diffusion for Crystalline Materials Generation
François R J Cornet, Federico Bergamin, Arghya Bhowmik, Juan Maria Garcia-Lastra, Jes Frellsen, Mikkel N. Schmidt Kun: Answer Polishment for Chinese Self-Alignment with Instruction Back-Translation
Tianyu Zheng, Shuyue Guo, Xingwei Qu, Jiawei Guo, Xeron Du, Chenghua Lin, Stephen Huang, Jie Fu, Ge Zhang Kurtail : Kurtosis-Based LLM Quantization
Mohammad Sadegh Akhondzadeh, Aleksandar Bojchevski, Evangelos Eleftheriou, Martino Dazzi KV Prediction for Improved Time to First Token
Maxwell Horton, Qingqing Cao, Chenfan Sun, Yanzi Jin, Sachin Mehta, Mohammad Rastegari, Moin Nabi LAION-C: An Out-of-Distribution Benchmark for Web-Scale Vision Models
Fanfei Li, Thomas Klein, Wieland Brendel, Robert Geirhos, Roland S. Zimmermann LaM-SLidE: Latent Space Modeling of Spatial Dynamical Systems via Linked Entities
Florian Sestak, Artur P. Toshev, Andreas Fürst, Günter Klambauer, Andreas Mayr, Johannes Brandstetter LaMsS: When Large Language Models Meet Self-Skepticism
Yetao Wu, Yihong Wang, Teng Chen, Ningyuan Xi, Qingqing Gu, Hongyang Lei, Luo Ji Landscape of Thoughts: Visualizing the Reasoning Process of Large Language Models
Zhanke Zhou, Xuan Li, Zhaocheng Zhu, Mikhail Galkin, Xiao Feng, Sanmi Koyejo, Jian Tang, Bo Han LangPert: LLM-Driven Contextual Synthesis for Unseen Perturbation Prediction
Kaspar Märtens, Marc Boubnovski Martell, Cesar A. Prada-Medina, Rory Donovan-Maiye Language Model Preference Evaluation with Multiple Weak Evaluators
Zhengyu Hu, Jieyu Zhang, Zhihan Xiong, Alexander Ratner, Hui Xiong, Ranjay Krishna Large Drug Discovery Model
Ilia Igashov, Arne Schneuing, Adrian W. Dobbelstein, Irina Morozova, Rebecca Manuela Neeser, Evgenia Elizarova, Philippe Schwaller, Michael M. Bronstein, Bruno Correia Large Language Diffusion Models
Shen Nie, Fengqi Zhu, Zebin You, Xiaolu Zhang, Jingyang Ou, Jun Hu, Jun Zhou, Yankai Lin, Ji-Rong Wen, Chongxuan Li Large Language Model Is Secretly a Protein Sequence Optimizer
Yinkai Wang, Jiaxing He, Yuanqi Du, Xiaohui Chen, Jianan Canal Li, Liping Liu, Xiaolin Xu, Soha Hassoun Large Language Model-Enhanced Multi-Armed Bandits
Jiahang Sun, Zhiyong Wang, Runhan Yang, Chenjun Xiao, John C.S. Lui, Zhongxiang Dai Large Language Models Are Innate Crystal Structure Generators
Jingru Gan, Peichen Zhong, Yuanqi Du, Yanqiao Zhu, Chenru Duan, Haorui Wang, Daniel Schwalbe-Koda, Carla P Gomes, Kristin Persson, Wei Wang Large Language Models for Zero-Shot Inference of Causal Structures in Biology
Izzy Newsham, Luka Kovačević, Richard Moulange, Nan Rosemary Ke, Sach Mukherjee Last Layer Empirical Bayes
Valentin Villecroze, Yixin Wang, Gabriel Loaiza-Ganem Latent Action Learning Requires Supervision in the Presence of Distractors
Alexander Nikulin, Ilya Zisman, Denis Tarasov, Lyubaykin Nikita, Andrei Polubarov, Igor Kiselev, Vladislav Kurenkov Latent Adversarial Training Improves the Representation of Refusal
Alexandra Abbas, Nora Petrova, Hélios Lyons, Natalia Perez-Campanero LayerDAG: A Layerwise Autoregressive Diffusion Model for Directed Acyclic Graph Generation
Mufei Li, Viraj Shitole, Eli Chien, Changhai Man, Zhaodong Wang, Srinivas, Ying Zhang, Tushar Krishna, Pan Li Learning a Thousand Tasks in a Day
Kamil Dreczkowski, Pietro Vitiello, Vitalis Vosylius, Edward Johns Learning Automata from Demonstrations, Examples, and Natural Language
Marcell Vazquez-Chanlatte, Karim Elmaaroufi, Stefan Witwicki, Matei Zaharia, Sanjit A. Seshia Learning Decision Trees as Amortized Structure Inference
Mohammed Mahfoud, Ghait Boukachab, Michał Koziarski, Alex Hernández-García, Stefan Bauer, Yoshua Bengio, Nikolay Malkin Learning from Less: Sindy Surrogates in Rl
Aniket Dixit, Muhammad Ibrahim Khan, Faizan Ahmed, James Brusey Learning Long-Context Robot Policies via Past-Token Prediction
Marcel Torne Villasevil, Andy Tang, Yuejiang Liu, Chelsea Finn Learning Multiphase and Multiphysics System with Decoupled State Space Model
Yun Young Choi, Seunghwan Lee, Minho Lee, Lee JinHaeng, Joohwan Ko, Chanwoong Moon Learning on LLM Output Signatures for Gray Box LLM Behavior Analysis
Guy Bar-Shalom, Fabrizio Frasca, Derek Lim, Yoav Gelberg, Yftah Ziser, Ran El-Yaniv, Gal Chechik, Haggai Maron Learning on Model Weights Using Tree Experts
Eliahu Horwitz, Bar Cavia, Jonathan Kahana, Yedid Hoshen Learning Representations of Instruments for Partial Identification of Treatment Effects
Jonas Schweisthal, Dennis Frauen, Maresa Schröder, Konstantin Hess, Niki Kilbertus, Stefan Feuerriegel Learning the RoPEs: Better 2D and 3D Position Encodings with STRING
Connor Schenck, Isaac Reid, Mithun George Jacob, Alex Bewley, Joshua Ainslie, David Rendleman, Deepali Jain, Mohit Sharma, Kumar Avinava Dubey, Ayzaan Wahid, Sumeet Singh, René Wagner, Tianli Ding, Chuyuan Fu, Arunkumar Byravan, Jake Varley, Alexey A. Gritsenko, Matthias Minderer, Dmitry Kalashnikov, Jonathan Tompson, Vikas Sindhwani, Krzysztof Marcin Choromanski Learning to Defer for Causal Discovery with Imperfect Experts
Oscar Clivio, Divyat Mahajan, Perouz Taslakian, Sara Magliacane, Ioannis Mitliagkas, Valentina Zantedeschi, Alexandre Drouin Learning to Lie: Reinforcement Learning Attacks Damage Human-AI Teams and Teams of LLMs
Abed K. Musaffar, Anand Gokhale, Sirui Zeng, Rasta Tadayon, Xifeng Yan, Ambuj Singh, Francesco Bullo Learning to Navigate in Open Urban Environments Using a Simple Sim2Real Strategy
Lixuan He, Haoyu Dong, Yangcheng Yu, Zhenxing Chen, Jie Feng, Xin Wang, Yong Li Learning to Predict Ensembles of Protein Conformations from Molecular Dynamics Simulation Trajectories
Bongjin Koo, Patrick Jiang, Soumya Dutta, I. Can Kazan, S. Banu Ozkan, Paul T Kim, Abhishek Singharoy, Tristan Bepler LeMat-Bulk: Aggregating, and De-Duplicating Quantum Chemistry Materials Databases
Martin Siron, Inel Djafar, Etienne du Fayet, Amandine Rossello, Ali Ramlaoui, Alexandre Duval Leveraging State Space Models in Long Range Genomics
Matvei Popov, Aymen Kallala, Anirudha Ramesh, Narimane Hennouni, Shivesh Khaitan, Rick Gentry, Alain-Sam Cohen Leveraging the True Depth of LLMs
Ramón Calvo González, Daniele Paliotta, Matteo Pagliardini, Martin Jaggi, François Fleuret Lifting the Benchmark Iceberg with Item-Response Theory
Mara Schilling-Wilhelmi, Nawaf Alampara, Kevin Maik Jablonka Ligand-Conditioned Binding Site Prediction Using Contrastive Geometric Learning
Lisa Schneckenreiter, Sohvi Luukkonen, Lukas Friedrich, Daniel Kuhn, Günter Klambauer Lightweight Latent Verifiers for Efficient Meta-Generation Strategies
Bartosz Piotrowski, Witold Drzewakowski, Konrad Staniszewski, Piotr Miłoś Linking Neural Representations to Adaptive Behavior with Cognitive Modeling
Christina Maher, Salman Qasim, Lizbeth Nunez Martinez, Angela Radulescu, Ignacio Saez LLM Neurosurgeon: Targeted Knowledge Removal in LLMs Using Sparse Autoencoders
Kunal Patil, Dylan Zhou, Yifan Sun, Karthik Lakshmanan, Senthooran Rajamanoharan, Arthur Conmy LLM-Augmented Chemical Synthesis and Design Decision Programs
Haorui Wang, Jeff Guo, Lingkai Kong, Rampi Ramprasad, Philippe Schwaller, Yuanqi Du, Chao Zhang LLM4GRN: Discovering Causal Gene Regulatory Networks with LLMs – Evaluation Through Synthetic Data Generation
Tejumade Afonja, Ivaxi Sheth, Ruta Binkyte, Waqar Hanif, Shubhi Ambast, Charles Mwangi Kaumbutha, Matthias Becker, Mario Fritz LLMs Know What to Drop: Self-Attention Guided KV Cache Eviction for Efficient Long-Context Inference
Guangtao Wang, Shubhangi Upasani, Chen Wu, Darshan Gandhi, Jonathan Lingjie Li, Changran Hu, Bo Li, Urmish Thakker LLMs Lost in Translation: M-Alert Uncovers Cross-Linguistic Safety Gaps
Felix Friedrich, Simone Tedeschi, Patrick Schramowski, Manuel Brack, Roberto Navigli, Huu Nguyen, Bo Li, Kristian Kersting LLMs on the Line: Data Determines Loss-to-Loss Scaling Laws
Prasanna Mayilvahanan, Thaddäus Wiedemer, Sayak Mallick, Matthias Bethge, Wieland Brendel LLMV-AgE: Verifying LLM-Guided Planning for Agentic Exploration in Open-World RL
Haotian Chi, Songwei Zhao, Ivor Tsang, Yew-Soon Ong, Hechang Chen, Yi Chang, Haiyan Yin LM Agents May Fail to Act on Their Own Risk Knowledge
Yuzhi Tang, Tianxiao Li, Elizabeth Li, Chris J. Maddison, Honghua Dong, Yangjun Ruan LM2: Large Memory Models for Long Context Reasoning
Jikun Kang, Wenqi Wu, Filippos Christianos, Alex James Chan, Fraser David Greenlee, George Thomas, Marvin Purtorab, Andrew Toulis LoBAM: LoRA-Based Backdoor Attack on Model Merging
Ming Yin, Jingyang Zhang, Jingwei Sun, Minghong Fang, Hai Helen Li, Yiran Chen LoRACode: LoRA Adapters for Code Embeddings
Saumya Chaturvedi, Aman Chadha, Laurent Bindschaedler Low Stein Discrepancy via Message-Passing Monte Carlo
Nathan Kirk, T. Konstantin Rusch, Jakob Zech, Daniela Rus Lurie Networks with K-Contracting Dynamics
Carl R Richardson, Matthew C. Turner, Steve R. Gunn MALIBU Benchmark: Multi-Agent LLM Implicit Bias Uncovered
Ishwara Vasista, Imran Mirza, Cole Huang, Rohan Rajasekhara Patil, Aslihan Akalin, Kevin Zhu, Sean O'Brien MALT: Improving Reasoning with Multi-Agent LLM Training
Sumeet Ramesh Motwani, Chandler Smith, Rocktim Jyoti Das, Rafael Rafailov, Ivan Laptev, Philip Torr, Fabio Pizzati, Ronald Clark, Christian Schroeder de Witt Mamba State-Space Models Are Lyapunov-Stable Learners
John Timothy Halloran, Manbir S Gulati, Paul F Roysdon ManiSkill3: GPU Parallelized Robot Simulation and Rendering for Generalizable Embodied AI
Stone Tao, Fanbo Xiang, Arth Shukla, Yuzhe Qin, Xander Hinrichsen, Xiaodi Yuan, Chen Bao, Xinsong Lin, Yulin Liu, Tse-Kai Chan, Yuan Gao, Xuanlin Li, Tongzhou Mu, Nan Xiao, Arnav Gurha, Viswesh N, Yong Woo Choi, Yen-Ru Chen, Zhiao Huang, Roberto Calandra, Rui Chen, Shan Luo, Hao Su MAS-GPT: Training LLMs to Build LLM-Based Multi-Agent Systems
Rui Ye, Shuo Tang, Rui Ge, Yaxin Du, Zhenfei Yin, Jing Shao, Siheng Chen Masked Generative Nested Transformers with Decode Time Scaling
Sahil Goyal, Debapriya Tula, Gagan Jain, Pradeep Shenoy, Prateek Jain, Sujoy Paul Masked Generative Priors Improve World Models Sequence Modelling Capabilities
Cristian Meo, Mircea Tudor Lică, Zarif Ikram, Akihiro Nakano, Vedant Shah, Aniket Rajiv Didolkar, Dianbo Liu, Anirudh Goyal, Justin Dauwels MatBind: Probing the Multimodality of Materials Science with Contrastive Learning
Adrian Mirza, Le Yang, Anoop K. Chandran, Jona Östreicher, Sebastien Bompas, Bashir Kazimi, Stefan Kesselheim, Pascal Friederich, Stefan Sandfeld, Kevin Maik Jablonka MatDock: Multi-Molecule Docking in Porous Materials with Flow Matching
Malte Franke, Mingrou Xie, Akshay Subramanian, Juno Nam, Rafael Gomez-Bombarelli MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities Against Hard Perturbations
Kaixuan Huang, Jiacheng Guo, Zihao Li, Xiang Ji, Jiawei Ge, Wenzhe Li, Yingqing Guo, Tianle Cai, Hui Yuan, Runzhe Wang, Yue Wu, Ming Yin, Shange Tang, Yangsibo Huang, Chi Jin, Xinyun Chen, Chiyuan Zhang, Mengdi Wang MathConstruct: Challenging LLM Reasoning with Constructive Proofs
Jasper Dekoninck, Mislav Balunovic, Nikola Jovanović, Ivo Petrov, Martin Vechev Matryoshka Quantization
Pranav Ajit Nair, Puranjay Datta, Jeff Dean, Prateek Jain, Aditya Kusupati Mdcrow: Automating Molecular Dynamics Workflows with Large Language Models
Sam Cox, Quintina L. Campbell, Jorge Medina, Brittany Watterson, Andrew White MeMDLM: De Novo Membrane Protein Design with Property-Guided Discrete Diffusion
Shrey Goel, Vishrut Thoutam, Edgar Mariano Marroquin, Aaron Gokaslan, Arash Firouzbakht, Sophia Vincoff, Volodymyr Kuleshov, Huong T. Kratochvil, Pranam Chatterjee MemLLM: Finetuning LLMs to Use Explicit Read-Write Memory
Ali Modarressi, Abdullatif Köksal, Ayyoob Imani, Mohsen Fayyaz, Hinrich Schuetze Mimetic Initialization Helps State Space Models Learn to Recall
Asher Trockman, Hrayr Harutyunyan, J Zico Kolter, Sanjiv Kumar, Srinadh Bhojanapalli Mimetic Initialization of MLPs
Asher Trockman, J Zico Kolter Mind the Gap: A Practical Attack on GGUF Quantization
Kazuki Egashira, Robin Staab, Mark Vero, Jingxuan He, Martin Vechev MixER: Better Mixture of Experts Routing for Hierarchical Meta-Learning
Roussel Desmond Nzoyem, Grant Stevens, Amarpal Sahota, David A.W. Barton, Tom Deakin Mixture-of-Transformers: A Sparse and Scalable Architecture for Multi-Modal Foundation Models
Weixin Liang, Lili Yu, Liang Luo, Srini Iyer, Ning Dong, Chunting Zhou, Gargi Ghosh, Mike Lewis, Luke Zettlemoyer, Xi Victoria Lin Mixture-of-Transformers: A Sparse and Scalable Architecture for Multi-Modal Foundation Models
Weixin Liang, Lili Yu, Liang Luo, Srini Iyer, Ning Dong, Chunting Zhou, Gargi Ghosh, Mike Lewis, Wen-tau Yih, Luke Zettlemoyer, Xi Victoria Lin ML-Bench: Evaluating Large Language Models and Agents for Machine Learning Tasks on Repository-Level Code
Xiangru Tang, Yuliang Liu, Zefan Cai, Daniel Shao, Junjie Lu, Yichi Zhang, Zexuan Deng, Helan Hu, Kaikai An, Ruijun Huang, Shuzheng Si, Chen Sheng, Haozhe Zhao, Liang Chen, Tianyu Liu, Yujia Qin, Wangchunshu Zhou, Yilun Zhao, Zhiwei Jiang, Baobao Chang, Arman Cohan, Mark Gerstein MLIP Arena: Advancing Fairness and Transparency in Machine Learning Interatomic Potentials Through an Open and Accessible Benchmark Platform
Yuan Chiang, Tobias Kreiman, Elizabeth Weaver, Ishan Amin, Matthew Kuner, Christine Zhang, Aaron Kaplan, Daryl Chrzan, Samuel M Blau, Aditi S. Krishnapriyan, Mark Asta Mllm Can See? Dynamic Correction Decoding for Hallucination Mitigation
Chenxi Wang, Xiang Chen, Ningyu Zhang, Bozhong Tian, Haoming Xu, Shumin Deng, Huajun Chen MMA: Benchmarking Multi-Modal Large Language Model in Ambiguity Contexts
Ru Wang, Selena Song, Liang Ding, Mingming Gong, Yusuke Iwasawa, Yutaka Matsuo, Jiaxian Guo MMInference: Accelerating Pre-Filling for Long-Context Visual Language Models via Modality-Aware Permutation Sparse Attention
Yucheng Li, Huiqiang Jiang, Chengruidong Zhang, Qianhui Wu, Xufang Luo, Surin Ahn, Amir H. Abdi, Dongsheng Li, Jianfeng Gao, Yuqing Yang, Lili Qiu MMKE-Bench: A Multimodal Editing Benchmark for Diverse Visual Knowledge
Yuntao Du, Kailin Jiang, Zhi Gao, Chenrui Shi, Zilong Zheng, Siyuan Qi, Qing Li MoA: Mixture of Sparse Attention for Automatic Large Language Model Compression
Tianyu Fu, Haofeng Huang, Xuefei Ning, Genghan Zhang, Boju Chen, Tianqi Wu, Hongyi Wang, Zixiao Huang, Shiyao Li, Shengen Yan, Guohao Dai, Huazhong Yang, Yu Wang MobiLlama: Towards Accurate & Lightweight Fully Transparent GPT
Omkar Chakradhar Thawakar, Ashmal Vayani, Salman Khan, Hisham Cholakkal, Rao Muhammad Anwer, Michael Felsberg, Timothy Baldwin, Eric P. Xing, Fahad Shahbaz Khan Model Assembly Learning with Heterogeneous Layer Weight Merging
Yi-Kai Zhang, Jin Wang, Xu-Xiang Zhong, De-Chuan Zhan, Han-Jia Ye Model Diffusion for Certifiable Few-Shot Transfer Learning
Fady Rezk, Royson Lee, Henry Gouk, Timothy Hospedales, Minyoung Kim Model Evaluations Need Rigorous and Transparent Human Baselines
Kevin Wei, Patricia Paskov, Sunishchal Dev, Michael J Byun, Anka Reuel, Xavier Roberts-Gaal, Rachel Calcott, Evie Coxon, Chinmay Deshpande Modern Hopfield Networks with Continuous-Time Memories
Saul Santos, António Farinhas, Daniel C McNamee, Andre Martins MODIS: Multi-Omics Data Integration for Small and Unpaired Datasets
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Keyue Qiu, Yuxuan Song, Zhehuan Fan, Peidong Liu, Zhe Zhang, Mingyue Zheng, Hao Zhou, Wei-Ying Ma Place Field Representation Learning During Policy Learning
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Haoran He, Yang Zhang, Liang Lin, Zhongwen Xu, Ling Pan Predicting Pulmonary Hypertension in Newborns: A Multi-View VAE Approach
Lucas Erlacher, Samuel Ruiperez-Campillo, Holger Michel, Sven Wellmann, Thomas M. Sutter, Ece Ozkan, Julia E Vogt Predictive Inference Is Really Free with In-Context Learning
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Emiliano Penaloza, Tianyue H. Zhang, Laurent Charlin, Mateo Espinosa Zarlenga Preference-Based Alignment of Discrete Diffusion Models
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Tai Dang, Long-Hung Pham, Sang T. Truong, Ari Glenn, Wendy Nguyen, Edward A Pham, Jeffrey S. Glenn, Sanmi Koyejo, Thang Luong Preserving Product Fidelity in Large Scale Image Recontextualization with Diffusion Models
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Antoni Kowalczuk, Jan Dubiński, Franziska Boenisch, Adam Dziedzic Privacy Auditing for Large Language Models with Natural Identifiers
Lorenzo Rossi, Bartłomiej Marek, Franziska Boenisch, Adam Dziedzic Probing Mechanical Reasoning in Large Vision Language Models
Haoran Sun, Yijiang Li, Qingying Gao, Haiyun Lyu, Dezhi Luo, Hokin Deng ProDiF: Protecting Domain-Invariant Features to Secure Pre-Trained Models Against Extraction
Tong Zhou, Shijin Duan, Gaowen Liu, Charles Fleming, Ramana Rao Kompella, Shaolei Ren, Xiaolin Xu Programmable Protein Stabilization with Language Model-Derived Peptide Guides
Lauren Hong, Tian Zi Wang, Divya Srijay, Howard Liu, Rio Watson, Lin Zhao, Sophia Vincoff, Leo Chen, Kseniia Kholina, Shrey Goel, Matthew DeLisa, Pranam Chatterjee Programmatic Video Prediction Using Large Language Models
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Peng Cheng, Zhihao Wu, Jianxiong Li, Ziteng He, Haoran Xu, Wei Sun, Youfang Lin, Xianyuan Zhan Q-Filters: Leveraging Query-Key Geometry for Efficient Key-Value Cache Compression
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Zongyu Lin, Yao Tang, Xingcheng Yao, Da Yin, Ziniu Hu, Yizhou Sun, Kai-Wei Chang Quasi-Random Multi-Sample Inference for Large Language Models
Avinash Amballa, Aditya Parashar, Aditya Vikram Singh, Jinlin Lai, Benjamin Rozonoyer Query-Dependent Prompt Optimization via Multi-Loop Offline Reinforcement Learning
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Andrei Panferov, Jiale Chen, Soroush Tabesh, Roberto L. Castro, Mahdi Nikdan, Dan Alistarh R-Llava: Improving Med-Vqa Understanding Through Visual Region of Interest
Xupeng Chen, Zhixin Lai, Kangrui Ruan, Shichu Chen, Jiaxiang Liu, Zuozhu Liu RAG-Enhanced Collaborative LLM Agents for Drug Discovery
Namkyeong Lee, Edward De Brouwer, Ehsan Hajiramezanali, Tommaso Biancalani, Chanyoung Park, Gabriele Scalia Rationalization Models for Text-to-SQL
Gaetano Rossiello, Nhan H Pham, Michael Glass, Junkyu Lee, Dharmashankar Subramanian Re-Imagine: Symbolic Benchmark Synthesis for Reasoning Evaluation
Xinnuo Xu, Rachel Lawrence, Kshitij Dubey, Atharva Pandey, Fabian Falck, Risa Ueno, Aditya V. Nori, Rahul Sharma, Amit Sharma, Javier Gonzalez Re:Frame - Retrieving Experience from Associative Memory
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Shashata Sawmya, Shuvom Sadhuka, Ragulan Sivakumar, Nir N Shavit, Dan Alistarh, Bonnie Berger RecurFormer: Not All Transformer Heads Need Self-Attention
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Wenlong Chen, Naoki Kiyohara, Harrison Bo Hua Zhu, Yingzhen Li Reference-Free Cell-Type Annotation with LLM Agents
Yidi Huang, Ivan Cohen, Van Quynh-Thi Truong, Pedram B Bayat, Sameer A Bhatti, Luca Paruzzo, Mark M. Painter, Shirong Zheng, Derek Alan Oldridge, Joost Wagenaar, Allison R Greenplate, Dokyoon Kim ReFocus: Visual Editing as a Chain of Thought for Structured Image Understanding
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Guanghan Wang, Yair Schiff, Subham Sekhar Sahoo, Volodymyr Kuleshov Representation Learning for Distributional Perturbation Extrapolation
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Eduardo Soares, Zeynep Sumer, Emilio Vital Brazil, Dave Braines, Richard L Anderson Residue-Level Text Conditioning for Protein Language Model Mutation Effect Prediction
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Xuerui Su, Yue Wang, Jinhua Zhu, Mingyang Yi, Feng Xu, Zhi-Ming Ma, Yuting Liu Revealing Chemical Reasoning in LLMs Through Search on Complex Planning Tasks
Andres M Bran, Théo A. Neukomm, Daniel P Armstrong, Zlatko Jončev, Philippe Schwaller Revisiting Multi-Modal LLM Evaluation
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Shenao Zhang, Zhihan Liu, Boyi Liu, Yufeng Zhang, Yingxiang Yang, Yongfei Liu, Liyu Chen, Tao Sun, Zhaoran Wang Rich Feature Learning via Diversification
Xi Leng, Yongqiang Chen, Xiaoying Tang, Yatao Bian RichSpace: Enriching Text-to-Video Prompt Space via Text Embedding Interpolation
Yuefan Cao, Chengyue Gong, Xiaoyu Li, Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song RILe: Reinforced Imitation Learning
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Liancheng Fang, Aiwei Liu, Henry Peng Zou, Hengrui Zhang, Philip S. Yu RL Zero: Zero-Shot Language to Behaviors Without Any Supervision
Harshit Sikchi, Siddhant Agarwal, Pranaya Jajoo, Samyak Parajuli, Caleb Chuck, Max Rudolph, Peter Stone, Amy Zhang, Scott Niekum RMBoost: Reward Model Training with Preference-Conditional Multi-Aspect Synthetic Data Generation
Jiaming Shen, Ran Xu, Yennie Jun, Zhen Qin, Tianqi Liu, Carl Yang, Yi Liang, Simon Baumgartner, Michael Bendersky RNAGym: Benchmarks for RNA Fitness and Structure Prediction
Rohit Arora, Murphy Angelo, Christian Andrew Choe, Aaron W Kollasch, Fiona Qu, Courtney A. Shearer, Ruben Weitzman, Artem Gazizov, Sarah Gurev, Erik Xie, Debora Susan Marks, Pascal Notin RoboMorph: Evolving Robot Morphology Using Large Language Models
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Aayush Mishra, Daniel Habermann, Marvin Schmitt, Stefan T. Radev, Paul-Christian Bürkner Robust Online Inference Using Adaptive Model Switching
Kalpan Mukherjee, Vikramank Singh, Abishek Sankararaman, Balakrishnan Murali Narayanaswamy, Tim Kraska Rule-Based Rating and Selection of LLM Training Data
Xiaomin Li, Mingye Gao, Zhiwei Zhang, Chang Yue, Hong Hu RuleArena: A Benchmark for LLM Rule-Guided Reasoning in Real-World Scenarios
Ruiwen Zhou, Wenyue Hua, Liangming Pan, Sitao Cheng, Xiaobao Wu, En Yu, William Yang Wang RxRx3-Core: Benchmarking Drug-Target Interactions in High-Content Microscopy
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Xihui Lin, Yunan Zhang, Suyu Ge, Liliang Ren, Barun Patra, Vishrav Chaudhary, Hao Peng, Xia Song SafeChain: Safety of Language Models with Long Chain-of-Thought Reasoning Capabilities
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Rajat Vadiraj Dwaraknath, Lexing Ying Sampling Through Algorithmic Diffusion in Non-Convex Perceptron Problems
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Charlie B. Tan, Joey Bose, Chen Lin, Leon Klein, Michael M. Bronstein, Alexander Tong Scalable Fingerprinting of Large Language Models
Anshul Nasery, Jonathan Hayase, Creston Brooks, Peiyao Sheng, Himanshu Tyagi, Pramod Viswanath, Sewoong Oh Scalable Thompson Sampling via Ensemble++
Yingru Li, Jiawei Xu, Baoxiang Wang, Zhi-Quan Luo Scalably Solving Assistance Games
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Jungyoon Lee, Michael Plainer, Yuanqi Du, Lars Holdijk, Rob Brekelmans, Carla P Gomes, Dominique Beaini, Kirill Neklyudov Scaling Deep Learning Solutions for Transition Path Sampling
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Xiyao Wang, Zhengyuan Yang, Linjie Li, Hongjin Lu, Yuancheng Xu, Chung-Ching Lin, Kevin Lin, Furong Huang, Lijuan Wang Scaling Laws and Efficient Inference for Ternary Language Models
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Tim Pearce, Tabish Rashid, David Bignell, Raluca Georgescu, Sam Devlin, Katja Hofmann Scaling up Parameter Generation: A Recurrent Diffusion Approach
Kai Wang, Dongwen Tang, Wangbo Zhao, Konstantin Schürholt, Zhangyang Wang, Yang You Score-Debiased Kernel Density Estimation
Elliot L Epstein, Rajat Vadiraj Dwaraknath, Thanawat Sornwanee, John Winnicki, Jerry Weihong Liu ScreenSpot-Pro: GUI Grounding for Professional High-Resolution Computer Use
Kaixin Li, Meng Ziyang, Hongzhan Lin, Ziyang Luo, Yuchen Tian, Jing Ma, Zhiyong Huang, Tat-Seng Chua Self-Ablating Transformers: More Interpretability, Less Sparsity
Jeremias Lino Ferrao, Luhan Mikaelson, Keenan Pepper, Natalia Perez-Campanero Self-Correcting Self-Consuming Loops for Generative Model Training
Nate Gillman, Michael Freeman, Daksh Aggarwal, Chia-Hong Hsu, Calvin Luo, Yonglong Tian, Chen Sun Self-Correction for OOD Generalization
Vanya Bannihatti Kumar, Abhinav Sukumar Rao, Aditi Raghunathan Self-Improving Diffusion Models with Synthetic Data
Sina Alemohammad, Ahmed Imtiaz Humayun, Shruti Agarwal, John Collomosse, Richard Baraniuk Self-Steering Language Models
Gabriel Grand, Joshua B. Tenenbaum, Vikash Mansinghka, Alexander K. Lew, Jacob Andreas Self-Supervised Learning Encodes Uncertainty
Miguel De Llanza Varona, Ryan Singh, Christopher Buckley Self-Taught Self-Correction for Small Language Models
Viktor Moskvoretskii, Chris Biemann, Irina Nikishina Semantic Device Graphs for Perovskite Solar Cell Design
Anagha Aneesh, Nawaf Alampara, José~A.~Márque, Kevin Maik Jablonka Sesame: Opening the Door to Protein Pockets
Raúl Miñán, Carles Perez-Lopez, Javier Iglesias-Fernández, Alvaro Ciudad Serrano, Alexis Molina Shape Generation via Weight Space Learning
Maximilian Plattner, Arturs Berzins, Johannes Brandstetter Shaping Inductive Bias in Diffusion Models Through Frequency-Based Noise Control
Thomas Jiralerspong, Berton Earnshaw, Jason Hartford, Yoshua Bengio, Luca Scimeca Shh, Don't Say That! Domain Certification in LLMs
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Yuxuan Song, Zhe Zhang, Yu Pei, Jingjing Gong, Mingxuan Wang, Hao Zhou, Jingjing Liu, Wei-Ying Ma Simulation-Free Structure Learning for Stochastic Dynamics
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Pascal Jutras Dube, Patrick Pynadath, Ruqi Zhang SMI-TED: A Large-Scale Foundation Model for Materials and Chemistry
Emilio Vital Brazil, Eduardo Soares, Victor Yukio Shirasuna, Renato Cerqueira, Dmitry Zubarev, Kristin Schmidt Societal Alignment Frameworks Can Improve LLM Alignment
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Tianjin Huang, Ziquan Zhu, Gaojie Jin, Lu Liu, Zhangyang Wang, Shiwei Liu SpargeAttn: Training-Free Sparse Attention Accelerating Any Model Inference
Jintao Zhang, Chendong Xiang, Haofeng Huang, Jia Wei, Haocheng Xi, Jun Zhu, Jianfei Chen SpARK: An Embarrassingly Simple Sparse Watermarking in LLMs with Enhanced Text Quality
Duy Cao Hoang, Thanh Quoc Hung Le, Rui Chu, Ping Li, Weijie Zhao, Yingjie Lao, Khoa D Doan Sparse and Wide Linear RNNs Are at the Efficiency-Performance Pareto Front
Alessandro Pierro, Steven Abreu, Jonathan Timcheck, Philipp Stratmann, Sumit Bam Shrestha Sparse Gradient Compression for Fine-Tuning Large Language Models
David H. Yang, Mohammad Mohammadi Amiri, Tejaswini Pedapati, Subhajit Chaudhury, Pin-Yu Chen Spawrious: A Benchmark for Fine Control of Spurious Correlation Biases
Aengus Lynch, Gbetondji Jean-Sebastien Dovonon, Jean Kaddour, Ricardo Silva SPELL: Spatial Prompting with Chain-of-Thought for Zero-Shot Learning in Spatial Transcriptomics
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Justin Singh Kang, Landon Butler, Abhineet Agarwal, Yigit Efe Erginbas, Ramtin Pedarsani, Bin Yu, Kannan Ramchandran Spherical Tree-Sliced Wasserstein Distance
Hoang V. Tran, Thanh Chu, Minh-Khoi Nguyen-Nhat, Huyen Trang Pham, Tam Le, Tan Minh Nguyen SpurLens: Finding Spurious Correlations in Multimodal LLMs
Parsa Hosseini, Sumit Nawathe, Mazda Moayeri, Sriram Balasubramanian, Soheil Feizi Stable-SPAM: How to Train in 4-Bit More Stably than 16-Bit Adam
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Helena Casademunt, Caden Juang, Samuel Marks, Senthooran Rajamanoharan, Neel Nanda Steering Generative Models with Experimental Data for Protein Fitness Optimization
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Alex Jihun Lee, Ava P Amini, Kevin K Yang, Sarah Alamdari, Chentong Wang, Reza Abbasi-Asl Student-Informed Teacher Training
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Joël Mathys, Andreas Plesner, Jorel Elmiger, Roger Wattenhofer Synthetic Data Pruning in High Dimensions: A Random Matrix Perspective
Aymane El Firdoussi, Mohamed El Amine Seddik, Soufiane Hayou, Reda Alami, Ahmed Alzubaidi, Hakim Hacid Synthetic Poisoning Attacks: The Impact of Poisoned MRI Image on U-Net Brain Tumor Segmentation
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Alex Gu, Naman Jain, Wen-Ding Li, Manish Shetty, Kevin Ellis, Koushik Sen, Armando Solar-Lezama TDRI: Two-Phase Dialogue Refinement and Co-Adaptation for Interactive Image Generation
Yangfan He, Yuheng Feng, Jianhui Wang, Kun Li, Yijin Wang, Haoyuan Li, Sida Li, Yinghui Xia, Tianyu Shi, Miao Zhang Teaching Language Models to Critique via Reinforcement Learning
Zhihui Xie, Jie Chen, Liyu Chen, Weichao Mao, Jingjing Xu, Lingpeng Kong Teaching Transformers Causal Reasoning Through Axiomatic Training
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Hadi Salloum, Kamil Sabbagh, Osama Orabi, Amine Trabelsi, Ruslan Lukin, Yaroslav Kholodov Test-Time View Selection for Multi-Modal Decision Making
Eeshaan Jain, Johann Wenckstern, Benedikt von Querfurth, Charlotte Bunne Text to 3D Object Generation for Scalable Room Assembly
Sonia Laguna, Alberto Garcia-Garcia, Marie-Julie Rakotosaona, Stylianos Moschoglou, Leonhard Helminger, Sergio Orts-Escolano Text2World: Benchmarking Large Language Models for Symbolic World Model Generation
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Scott Geng, Hamish Ivison, Chun-Liang Li, Maarten Sap, Jerry Li, Ranjay Krishna, Pang Wei Koh The Differences Between Direct Alignment Algorithms Are a Blur
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Subham Sekhar Sahoo, Justin Deschenaux, Aaron Gokaslan, Guanghan Wang, Justin T Chiu, Volodymyr Kuleshov The Landscape of Causal Discovery Data: Grounding Causal Discovery in Real-World Applications
Philippe Brouillard, Chandler Squires, Jonas Wahl, Konrad Kording, Karen Sachs, Alexandre Drouin, Dhanya Sridhar The Lock-in Hypothesis: Stagnation by Algorithm
Tianyi Qiu, Zhonghao He, Tejasveer Chugh, Max Kleiman-Weiner The Space Between: On Folding, Symmetries and Sampling
Michal Lewandowski, Bernhard Heinzl, Raphael Pisoni, Bernhard A. Moser The Steganographic Potentials of Language Models
Artem Karpov, Tinuade Adeleke, Seong Hah Cho, Natalia Perez-Campanero The Surprising Effectiveness of Randomness in LLM Pruning
Shuyao Xu, Liu Jiayao, Zhenfeng He, Cheng Peng, Weidi Xu Think Smarter Not Harder: Adaptive Reasoning with Inference Aware Optimization
Zishun Yu, Tengyu Xu, Di Jin, Karthik Abinav Sankararaman, Yun He, Wenxuan Zhou, Zhouhao Zeng, Eryk Helenowski, Chen Zhu, Sinong Wang, Hao Ma, Han Fang Thinking Slow, Fast: Scaling Inference Compute with Distilled Reasoners
Daniele Paliotta, Junxiong Wang, Matteo Pagliardini, Kevin Li, Aviv Bick, Albert Gu, François Fleuret, Tri Dao Tight Clusters Make Specialized Experts
Stefan Nielsen, Rachel S.Y. Teo, Laziz Abdullaev, Tan Minh Nguyen TIMER: Temporal Instruction Modeling and Evaluation for Longitudinal Clinical Records
Hejie Cui, Alyssa Unell, Bowen Chen, Jason Alan Fries, Emily Alsentzer, Sanmi Koyejo, Nigam Shah Token-Level Adversarial Prompt Detection Based on Perplexity Measures and Contextual Information
Zhengmian Hu, Gang Wu, Saayan Mitra, Ruiyi Zhang, Tong Sun, Heng Huang, Viswanathan Swaminathan ToolScan: A Benchmark for Characterizing Errors in Tool-Use LLMs
Shirley Kokane, Ming Zhu, Tulika Manoj Awalgaonkar, Jianguo Zhang, Akshara Prabhakar, Thai Quoc Hoang, Zuxin Liu, R N Rithesh, Liangwei Yang, Weiran Yao, Juntao Tan, Zhiwei Liu, Huan Wang, Juan Carlos Niebles, Shelby Heinecke, Caiming Xiong, Silvio Savarese TOP-ERL: Transformer-Based Off-Policy Episodic Reinforcement Learning
Ge Li, Dong Tian, Hongyi Zhou, Xinkai Jiang, Rudolf Lioutikov, Gerhard Neumann Towards Comprehensive Preference Data Collection for Reward Modeling
Yulan Hu, Qingyang Li, Sheng Ouyang, Ge Chen, Jinman Zhao, Yong Liu Towards Effective Discrimination Testing for Generative AI
Thomas P Zollo, Nikita Rajaneesh, Richard Zemel, Talia B. Gillis, Emily Black Towards Extrapolation in Deep Material Property Regression
Mianzhi Pan, JianFei Li, Yawen Ouyang, Wei-Ying Ma, Jianbing Zhang, Hao Zhou Towards Faster and More Compact Foundation Models for Molecular Property Prediction
Yasir M. Ghunaim, Andrés Villa, Gergo Ignacz, Gyorgy Szekely, Motasem Alfarra, Bernard Ghanem Towards Fusing Point Cloud and Visual Representations for Imitation Learning
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Yingyu Liang, Zhenmei Shi, Zhao Song, Chiwun Yang Towards Internet-Scale Training for Agents
Brandon Trabucco, Gunnar A Sigurdsson, Robinson Piramuthu, Ruslan Salakhutdinov Towards LVLM-Aided Alignment of Task-Specific Vision Models
Alexander Koebler, Christian Greisinger, Jan Paulus, Ingo Thon, Florian Buettner Towards More Accurate Full-Atom Antibody Co-Design
Jiayang Wu, Xingyi Zhang, Xiangyu Dong, Kun Xie, Ziqi Liu, Wensheng Gan, Sibo Wang, Le Song Towards Personalized Healthcare Without Harm via Bias Modulation
Frank Ngaha, Patrik Kenfack, Ulrich Aïvodji, Samira Ebrahimi Kahou Towards Representation Learning for Phenotyping Beyond Animal Pose Estimation
Takatomi Kubo, Nina Nakajima, Nanako Miyai, Midori Osaki, Suzuka Higashitsutsumi Towards Scalable Newborn Screening: Automated General Movement Assessment in Uncontrolled Settings
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Mingtian Zhang, Jiajun He, Wenlin Chen, Zijing Ou, José Miguel Hernández-Lobato, Bernhard Schölkopf, David Barber Towards Variational Flow Matching on General Geometries
Olga Zaghen, Floor Eijkelboom, Alison Pouplin, Erik J Bekkers Towards Watermarking of Open-Source LLMs
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Weitao Feng, Jiyan He, Jie Zhang, Tianyi Wei, Wenbo Zhou, Qing Guo, Weiming Zhang, Tianwei Zhang, Nenghai Yu Tradeoffs Between Alignment and Helpfulness in Language Models with Steering Methods
Yotam Wolf, Noam Wies, Dorin Shteyman, Binyamin Rothberg, Yoav Levine, Amnon Shashua Training a Generally Curious Agent
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Gianluigi Silvestri, Luca Ambrogioni, Chieh-Hsin Lai, Yuhta Takida, Yuki Mitsufuji Training Deep Predictive Coding Networks
Chang Qi, Thomas Lukasiewicz, Tommaso Salvatori Training Domain Draft Models for Speculative Decoding: Best Practices and Insights
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Lucas Caccia, Alan Ansell, Ivan Vulić, Edoardo Ponti, Alessandro Sordoni Training Software Engineering Agents and Verifiers with SWE-Gym
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Alexander F Spies, William Edwards, Michael Ivanitskiy, Adrians Skapars, Tilman Räuker, Katsumi Inoue, Alessandra Russo, Murray Shanahan Traveling Waves Integrate Spatial Information into Spectral Representations
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Andreas Floros, Seyed-Mohsen Moosavi-Dezfooli, Pier Luigi Dragotti TwinMarket: A Scalable Behavioral and Social Simulation for Financial Markets
Yuzhe Yang, Yifei Zhang, Minghao Wu, Kaidi Zhang, Yunmiao Zhang, Honghai Yu, Yan Hu, Benyou Wang Type-Constrained Code Generation with Language Models
Niels Mündler, Jingxuan He, Hao Wang, Koushik Sen, Dawn Song, Martin Vechev TypyBench: Evaluating LLM Type Inference for Untyped Python Repositories
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Gregory Kang Ruey Lau, Hieu Dao, Bryan Kian Hsiang Low Uncertainty-Aware PPG-2-ECG for Enhanced Cardiovascular Diagnosis Using Diffusion Models
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Meng Ding, Mingxi Lei, Shaopeng Fu, Di Wang, Jinhui Xu Understanding Reasoning in Thinking Language Models via Steering Vectors
Constantin Venhoff, Iván Arcuschin, Philip Torr, Arthur Conmy, Neel Nanda Understanding School Attendance Through Multimodal Modelling of Student Narratives
Tingrui Qiao, Caroline Walker, Chris W Cunningham, Adam Jang-Jones, Susan Mary Bennett Morton, Kane Meissel, Yun Sing Koh Understanding Task Representations in Neural Networks via Bayesian Ablation
Andrew Joohun Nam, Declan Iain Campbell, Thomas L. Griffiths, Jonathan D. Cohen, Sarah-Jane Leslie Universal Actions for Enhanced Embodied Foundation Models
Jinliang Zheng, Jianxiong Li, Dongxiu Liu, Yinan Zheng, Zhihao Wang, Zhonghong Ou, Yu Liu, Jingjing Liu, Ya-Qin Zhang, Xianyuan Zhan Universal LLM Routing with Correctness-Based Representation
Wittawat Jitkrittum, Harikrishna Narasimhan, Ankit Singh Rawat, Jeevesh Juneja, Zifeng Wang, Chen-Yu Lee, Pradeep Shenoy, Rina Panigrahy, Aditya Krishna Menon, Sanjiv Kumar Universally Applicable and Tunable Graph-Based Coarse-Graining for Machine Learning Force Fields
Christoph Brunken, Sebastien Boyer, Mustafa Omar, Martin Maarand, Olivier Peltre, Solal Attias, Bakary N'tji Diallo, Anastasia Markina, Olaf Othersen, Oliver Bent Unlearning Geo-Cultural Stereotypes in Multilingual LLMs
Alireza Dehghanpour Farashah, Aditi Khandelwal, Negar Rostamzadeh, Golnoosh Farnadi Unlocking Post-Hoc Dataset Inference with Synthetic Data
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Jeffrey Yang Fan Chiang, Seungjae Lee, Jia-Bin Huang, Furong Huang, Yizheng Chen Why Do Multiagent Systems Fail?
Melissa Z Pan, Mert Cemri, Lakshya A Agrawal, Shuyi Yang, Bhavya Chopra, Rishabh Tiwari, Kurt Keutzer, Aditya Parameswaran, Kannan Ramchandran, Dan Klein, Joseph E. Gonzalez, Matei Zaharia, Ion Stoica Wild Posteriors in the Wild
Yunyi Shen, Tamara Broderick WorkflowAgent: Towards Specialized Web Agents Using Production-Scale Workflow Data
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Bibek Upadhayay, Vahid Behzadan, Amin Karbasi X-IL: Exploring the Design Space of Imitation Learning Policies
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