TMLR 2025
1432 papers
(Accelerated) Noise-Adaptive Stochastic Heavy-Ball Momentum
Anh Quang Dang, Reza Babanezhad Harikandeh, Sharan Vaswani [Re] Benchmarking LLM Capabilities in Negotiation Through Scoreable Games
Jorge Carrasco Pollo, Ioannis Kapetangeorgis, Joshua Rosenthal, John Hua Yao [RE] GNNBoundary: Finding Boundaries and Going Beyond Them
Jan Henrik Bertrand, Lukas Bierling, Ina Klaric, Aron Wezenberg ∇QDARTS: Quantization as an Elastic Dimension to Differentiable NAS
Payman Behnam, Uday Kamal, Sanjana Vijay Ganesh, Zhaoyi Li, Michael Andrew Jurado, Alind Khare, Igor Fedorov, Gaowen Liu, Alexey Tumanov A Comparison Between Humans and AI at Recognizing Objects in Unusual Poses
Netta Ollikka, Amro Kamal Mohamed Abbas, Andrea Perin, Markku Kilpeläinen, Stephane Deny A Comprehensive Survey of Contamination Detection Methods in Large Language Models
Mathieu Ravaut, Bosheng Ding, Fangkai Jiao, Hailin Chen, Xingxuan Li, Ruochen Zhao, Chengwei Qin, Caiming Xiong, Shafiq Joty A Comprehensive Survey on Knowledge Distillation
Amir M. Mansourian, Rozhan Ahmadi, Masoud Ghafouri, Amir Mohammad Babaei, Elaheh Badali Golezani, Zeynab yasamani Ghamchi, Vida Ramezanian, Alireza Taherian, Kimia Dinashi, Amirali Miri, Shohreh Kasaei A Fused Gromov-Wasserstein Approach to Subgraph Contrastive Learning
Amadou Siaka Sangare, Nicolas Dunou, Jhony H. Giraldo, Fragkiskos D. Malliaros A Gold Standard Dataset for the Reviewer Assignment Problem
Ivan Stelmakh, John Frederick Wieting, Yang Xi, Graham Neubig, Nihar B Shah A Hierarchical Nearest Neighbour Approach to Contextual Bandits
Stephen Pasteris, Madeleine Dwyer, Chris Hicks, Vasilios Mavroudis A Max-Min Approach to the Worst-Case Class Separation Problem
Mohammad Mahdi Omati, Prabhu Babu, Petre Stoica, Arash Amini A Note on the Stability of the Focal Loss
Martijn P. van Leeuwen, Koen V. Haak, Gorkem Saygili, Eric O. Postma, L.L. Sharon Ong A Novel Benchmark for Few-Shot Semantic Segmentation in the Era of Foundation Models
Reda Bensaid, Vincent Gripon, François Leduc-Primeau, Lukas Mauch, Ghouthi BOUKLI Hacene, Fabien Cardinaux A Pattern Language for Machine Learning Tasks
Benjamin Rodatz, Ian Fan, Tuomas Laakkonen, Neil John Ortega, Thomas Hoffmann, Vincent Wang A Proximal Operator for Inducing 2:4-Sparsity
Jonas M. Kübler, Yu-Xiang Wang, Shoham Sabach, Navid Ansari, Matthäus Kleindessner, Kailash Budhathoki, Volkan Cevher, George Karypis A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentation
Amaan Valiuddin, Ruud Van Sloun, Christiaan Viviers, Peter H.N. de With, Fons van der Sommen A Self-Explainable Heterogeneous GNN for Relational Deep Learning
Francesco Ferrini, Antonio Longa, Andrea Passerini, Manfred Jaeger A Shortcut-Aware Video-QA Benchmark for Physical Understanding via Minimal Video Pairs
Benno Krojer, Mojtaba Komeili, Candace Ross, Quentin Garrido, Koustuv Sinha, Nicolas Ballas, Mido Assran A Strong Baseline for Molecular Few-Shot Learning
Philippe Formont, Hugo Jeannin, Pablo Piantanida, Ismail Ben Ayed A Survey of Frontiers in LLM Reasoning: Inference Scaling, Learning to Reason, and Agentic Systems
Zixuan Ke, Fangkai Jiao, Yifei Ming, Xuan-Phi Nguyen, Austin Xu, Do Xuan Long, Minzhi Li, Chengwei Qin, PeiFeng Wang, Silvio Savarese, Caiming Xiong, Shafiq Joty A Survey of Recent Backdoor Attacks and Defenses in Large Language Models
Shuai Zhao, Meihuizi Jia, Zhongliang Guo, Leilei Gan, Xiaoyu Xu, Xiaobao Wu, Jie Fu, Feng Yichao, Fengjun Pan, Anh Tuan Luu A Survey of Reinforcement Learning from Human Feedback
Timo Kaufmann, Paul Weng, Viktor Bengs, Eyke Hüllermeier A Survey on Future Frame Synthesis: Bridging Deterministic and Generative Approaches
Ruibo Ming, Zhewei Huang, Jingwei Wu, Zhuoxuan Ju, Daxin Jiang, Jianming Hu, Lihui Peng, Shuchang Zhou A Survey on Generative Modeling with Limited Data, Few Shots, and Zero Shot
Milad Abdollahzadeh, Guimeng Liu, Touba Malekzadeh, Christopher T.H Teo, Keshigeyan Chandrasegaran, Ngai-Man Cheung A Survey on Large Language Model Acceleration Based on KV Cache Management
Haoyang Li, Yiming Li, Anxin Tian, Tianhao Tang, Zhanchao Xu, Xuejia Chen, Nicole Hu, Wei Dong, Li Qing, Lei Chen A Survey on Large Language Model-Based Social Agents in Game-Theoretic Scenarios
Xiachong Feng, Longxu Dou, Minzhi Li, Qinghao Wang, Yu Guo, Haochuan Wang, Chang Ma, Lingpeng Kong A Survey on Model MoErging: Recycling and Routing Among Specialized Experts for Collaborative Learning
Prateek Yadav, Colin Raffel, Mohammed Muqeeth, Lucas Caccia, Haokun Liu, Tianlong Chen, Mohit Bansal, Leshem Choshen, Alessandro Sordoni A Survey on the Honesty of Large Language Models
Siheng Li, Cheng Yang, Taiqiang Wu, Chufan Shi, Yuji Zhang, Xinyu Zhu, Zesen Cheng, Deng Cai, Mo Yu, Lemao Liu, Jie Zhou, Yujiu Yang, Ngai Wong, Xixin Wu, Wai Lam A Thorough Reproduction and Evaluation of $\mu$P
Georgios Vlassis, David Belius, Volodymyr Fomichov Abstraction for Bayesian Reinforcement Learning in Factored POMDPs
Rolf A. N. Starre, Sammie Katt, Mustafa Mert Çelikok, Marco Loog, Frans A Oliehoek AcademicEval: Live Long-Context LLM Benchmark
Haozhen Zhang, Tao Feng, Pengrui Han, Jiaxuan You Accelerated Training on Low-Power Edge Devices
Mohamed Aboelenien Ahmed, Kilian Pfeiffer, Osama Abboud, Ramin Khalili, Heba Khdr, Joerg Henkel Activate and Adapt: A Two-Stage Framework for Open-Set Model Adaptation
Xiasi Wang, Jiaqi Lin, Chaoqi Chen, Luyao Tang, Yi Huang, Chengsen Wang, Lei Ye, Yuan Yao Activation Sharding for Scalable Training of Large Models
Xingzi Xu, Amir Tavanaei, Kavosh Asadi, Karim Bouyarmane Active Diffusion Subsampling
Oisín Nolan, Tristan Stevens, Wessel L. van Nierop, Ruud Van Sloun Active Prompt Learning with Vision-Language Model Priors
Hoyoung Kim, Seokhee Jin, Changhwan Sung, Jaechang Kim, Jungseul Ok ADAPT to Robustify Prompt Tuning Vision Transformers
Masih Eskandar, Tooba Imtiaz, Zifeng Wang, Jennifer Dy Adapting Chat Language Models Using Only Target Unlabeled Language Data
Atsuki Yamaguchi, Terufumi Morishita, Aline Villavicencio, Nikolaos Aletras Adaptive Group Robust Ensemble Knowledge Distillation
Patrik Kenfack, Ulrich Aïvodji, Samira Ebrahimi Kahou Adaptive Mesh Quantization for Neural PDE Solvers
Winfried van den Dool, Maksim Zhdanov, Yuki M Asano, Max Welling Adaptive Multi-Step Refinement Network for Robust Point Cloud Registration
Zhi Chen, Yufan Ren, Tong Zhang, Zheng Dang, Wenbing Tao, Sabine Susstrunk, Mathieu Salzmann Adjacency Search Embeddings
Meher Chaitanya, Kshitijaa Jaglan, Ulrik Brandes ADMIRE-BayesOpt: Accelerated Data MIxture RE-Weighting for Language Models with Bayesian Optimization
Xu Ouyang, Shengzhuang Chen, Michael Arthur Leopold Pearce, Thomas Hartvigsen, Jonathan Richard Schwarz Adversarial Robustness of Graph Transformers
Philipp Foth, Lukas Gosch, Simon Geisler, Leo Schwinn, Stephan Günnemann Adversarial Subspace Generation for Outlier Detection in High-Dimensional Data
Jose Cribeiro-Ramallo, Federico Matteucci, Paul Enciu, Alexander Jenke, Vadim Arzamasov, Thorsten Strufe, Klemens Böhm Aggregating Algorithm and Axiomatic Loss Aggregation
Armando J Cabrera Pacheco, Rabanus Derr, Robert Williamson Agreement-Based Cascading for Efficient Inference
Steven Kolawole, Don Dennis, Ameet Talwalkar, Virginia Smith AI Agents That Matter
Sayash Kapoor, Benedikt Stroebl, Zachary S Siegel, Nitya Nadgir, Arvind Narayanan AlgoFormer: An Efficient Transformer Framework with Algorithmic Structures
Yihang Gao, Chuanyang Zheng, Enze Xie, Han Shi, Tianyang Hu, Yu Li, Michael Ng, Zhenguo Li, Zhaoqiang Liu Algorithm Configuration for Structured Pfaffian Settings
Maria Florina Balcan, Anh Tuan Nguyen, Dravyansh Sharma Align and Distill: Unifying and Improving Domain Adaptive Object Detection
Justin Kay, Timm Haucke, Suzanne Stathatos, Siqi Deng, Erik Young, Pietro Perona, Sara Beery, Grant Van Horn ALTA: Compiler-Based Analysis of Transformers
Peter Shaw, James Cohan, Jacob Eisenstein, Kenton Lee, Jonathan Berant, Kristina Toutanova Alternators for Sequence Modeling
Mohammad Reza Rezaei, Adji Bousso Dieng An Adversarial Perspective on Machine Unlearning for AI Safety
Jakub Łucki, Boyi Wei, Yangsibo Huang, Peter Henderson, Florian Tramèr, Javier Rando An Analysis of the Noise Schedule for Score-Based Generative Models
Stanislas Strasman, Antonio Ocello, Claire Boyer, Sylvain Le Corff, Vincent Lemaire An Embedding Is Worth a Thousand Noisy Labels
Francesco Di Salvo, Sebastian Doerrich, Ines Rieger, Christian Ledig An Information Theoretic Approach to Machine Unlearning
Jack Foster, Kyle Fogarty, Stefan Schoepf, Zack Dugue, Cengiz Oztireli, Alexandra Brintrup Approximations to Worst-Case Data Dropping: Unmasking Failure Modes
Jenny Y. Huang, David R. Burt, Yunyi Shen, Tin D. Nguyen, Tamara Broderick Are Convex Optimization Curves Convex?
Guy Barzilai, Ohad Shamir, Moslem Zamani Are Large Language Models Really Robust to Word-Level Perturbations?
Haoyu Wang, Guozheng Ma, Cong Yu, Ning Gui, Linrui Zhang, Zhiqi Huang, Suwei Ma, Yongzhe Chang, Sen Zhang, Li Shen, Xueqian Wang, Peilin Zhao, Dacheng Tao ASTRA: A Scene-Aware Transformer-Based Model for Trajectory Prediction
Izzeddin Teeti, Aniket Thomas, Munish Monga, Sachin Kumar Giroh, Uddeshya Singh, Andrew Bradley, Biplab Banerjee, Fabio Cuzzolin AT4TS : Autotune for Time Series Foundation Models
Shivani Tomar, Seshu Tirupathi, Radu Marinescu, Elizabeth M. Daly, Ivana Dusparic Attention Overlap Is Responsible for the Entity Missing Problem in Text-to-Image Diffusion Models!
Arash Mari Oriyad, Mohammadali Banayeeanzade, Reza Abbasi, Mohammad Hossein Rohban, Mahdieh Soleymani Baghshah Augmented Invertible Koopman Autoencoder for Long-Term Time Series Forecasting
Anthony Frion, Lucas Drumetz, Mauro Dalla Mura, Guillaume Tochon, Abdeldjalil AISSA El Bey Automated Black-Box Prompt Engineering for Personalized Text-to-Image Generation
Yutong He, Alexander Robey, Naoki Murata, Yiding Jiang, Joshua Nathaniel Williams, George J. Pappas, Hamed Hassani, Yuki Mitsufuji, Ruslan Salakhutdinov, J Zico Kolter Autoregressive Models in Vision: A Survey
Jing Xiong, Gongye Liu, Lun Huang, Chengyue Wu, Taiqiang Wu, Yao Mu, Yuan Yao, Hui Shen, Zhongwei Wan, Jinfa Huang, Chaofan Tao, Shen Yan, Huaxiu Yao, Lingpeng Kong, Hongxia Yang, Mi Zhang, Guillermo Sapiro, Jiebo Luo, Ping Luo, Ngai Wong AutoTrust: Benchmarking Trustworthiness in Large Vision Language Models for Autonomous Driving
Shuo Xing, Hongyuan Hua, Xiangbo Gao, Shenzhe Zhu, Renjie Li, Kexin Tian, Xiaopeng Li, Heng Huang, Tianbao Yang, Zhangyang Wang, Yang Zhou, Huaxiu Yao, Zhengzhong Tu Balanced Mixed-Type Tabular Data Synthesis with Diffusion Models
Zeyu Yang, Han Yu, Peikun Guo, Khadija Zanna, Xiaoxue Yang, Akane Sano Balancing Utility and Privacy: Dynamically Private SGD with Random Projection
Zhanhong Jiang, Md Zahid Hasan, Nastaran Saadati, Aditya Balu, Chao Liu, Soumik Sarkar Bayesian Learning-Driven Prototypical Contrastive Loss for Class-Incremental Learning
Nisha L. Raichur, Lucas Heublein, Tobias Feigl, Alexander Rügamer, Christopher Mutschler, Felix Ott Between Linear and Sinusoidal: Rethinking the Time Encoder in Dynamic Graph Learning
Hsing-Huan Chung, Shravan S Chaudhari, Xing Han, Yoav Wald, Suchi Saria, Joydeep Ghosh Beyond Joint Demonstrations: Personalized Expert Guidance for Efficient Multi-Agent Reinforcement Learning
Peihong Yu, Manav Mishra, Alec Koppel, Carl Busart, Priya Narayan, Dinesh Manocha, Amrit Singh Bedi, Pratap Tokekar Beyond Parameter Count: Implicit Bias in Soft Mixture of Experts
Youngseog Chung, Dhruv Malik, Jeff Schneider, Yuanzhi Li, Aarti Singh Bi-Mamba: Towards Accurate 1-Bit State Space Model
Shengkun Tang, Liqun Ma, Haonan Li, Mingjie Sun, Zhiqiang Shen Bigger Is Not Always Better: Scaling Properties of Latent Diffusion Models
Kangfu Mei, Zhengzhong Tu, Mauricio Delbracio, Hossein Talebi, Vishal M. Patel, Peyman Milanfar Boosting Revisited: Benchmarking and Advancing LP-Based Ensemble Methods
Fabian Akkerman, Julien Ferry, Christian Artigues, Emmanuel Hebrard, Thibaut Vidal 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 Buffer-Based Gradient Projection for Continual Federated Learning
Shenghong Dai, Jy-yong Sohn, Yicong Chen, S M Iftekharul Alam, Ravikumar Balakrishnan, Suman Banerjee, Nageen Himayat, Kangwook Lee Can Masked Autoencoders Also Listen to Birds?
Lukas Rauch, René Heinrich, Ilyass Moummad, Alexis Joly, Bernhard Sick, Christoph Scholz CAREL: Instruction-Guided Reinforcement Learning with Cross-Modal Auxiliary Objectives
Armin Saghafian, Amirmohammad Izadi, Negin Hashemi Dijujin, Mahdieh Soleymani Baghshah Causal Ordering for Structure Learning from Time Series
Pedro Sanchez, Damian Machlanski, Steven McDonagh, Sotirios A. Tsaftaris Celo: Training Versatile Learned Optimizers on a Compute Diet
Abhinav Moudgil, Boris Knyazev, Guillaume Lajoie, Eugene Belilovsky Certified Robustness to Data Poisoning in Gradient-Based Training
Philip Sosnin, Mark Niklas Mueller, Maximilian Baader, Calvin Tsay, Matthew Robert Wicker Change Point Detection in Dynamic Graphs with Decoder-Only Latent Space Model
Yik Lun Kei, Jialiang Li, Hangjian Li, Yanzhen Chen, Oscar Hernan Madrid Padilla Change Point Detection in the Frequency Domain with Statistical Reliability
Akifumi Yamada, Tomohiro Shiraishi, Shuichi Nishino, Teruyuki Katsuoka, Kouichi Taji, Ichiro Takeuchi Change Point Detection on a Separable Model for Dynamic Networks
Yik Lun Kei, Hangjian Li, Yanzhen Chen, Oscar Hernan Madrid Padilla Characterizing the Convergence of Game Dynamics via Potentialness
Martin Bichler, Davide Legacci, Panayotis Mertikopoulos, Matthias Oberlechner, Bary Pradelski Chimera: State Space Models Beyond Sequences
Aakash Lahoti, Tanya Marwah, Ratish Puduppully, Albert Gu Choose Your Model Size: Any Compression of Large Language Models Without Re-Computation
Martin Genzel, Patrick Putzky, Pengfei Zhao, Sebastian Schulze, Mattes Mollenhauer, Robert Seidel, Stefan Dietzel, Thomas Wollmann CLImage: Human-Annotated Datasets for Complementary-Label Learning
Hsiu-Hsuan Wang, Mai Tan Ha, Nai-Xuan Ye, Wei-I Lin, Hsuan-Tien Lin Closed-Form Diffusion Models
Christopher Scarvelis, Haitz Sáez de Ocáriz Borde, Justin Solomon Cluster Agnostic Network Lasso Bandits
Sofien Dhouib, Steven Bilaj, Behzad Nourani-Koliji, Setareh Maghsudi Cluster and Predict Latents Patches for Improved Masked Image Modeling
Timothée Darcet, Federico Baldassarre, Maxime Oquab, Julien Mairal, Piotr Bojanowski CNN Interpretability with Multivector Tucker Saliency Maps for Self-Supervised Models
Aymene Mohammed Bouayed, Samuel Deslauriers-gauthier, Adrian Iacovelli, David Naccache CoDe: Blockwise Control for Denoising Diffusion Models
Anuj Singh, Sayak Mukherjee, Ahmad Beirami, Hadi J. Rad CodeLutra: Boosting LLM Code Generation via Preference-Guided Refinement
Leitian Tao, Xiang Chen, Tong Yu, Tung Mai, Ryan A. Rossi, Yixuan Li, Saayan Mitra Combinatorial Multi-Armed Bandits: Arm Selection via Group Testing
Arpan Mukherjee, Shashanka Ubaru, Keerthiram Murugesan, Karthikeyan Shanmugam, Ali Tajer Cometh: A Continuous-Time Discrete-State Graph Diffusion Model
Antoine Siraudin, Fragkiskos D. Malliaros, Christopher Morris COMMA: A Communicative Multimodal Multi-Agent Benchmark
Timothy Ossowski, Danyal Maqbool, Jixuan Chen, Zefan Cai, Tyler J. Bradshaw, Junjie Hu Compressed Decentralized Momentum Stochastic Gradient Methods for Nonconvex Optimization
Wei Liu, Anweshit Panda, Ujwal Pandey, Christopher Brissette, Yikang Shen, George Slota, Naigang Wang, Jie Chen, Yangyang Xu Conditional Image Synthesis with Diffusion Models: A Survey
Zheyuan Zhan, Defang Chen, Jian-Ping Mei, Zhenghe Zhao, Jiawei Chen, Chun Chen, Siwei Lyu, Can Wang Conformal Prediction: A Theoretical Note and Benchmarking Transductive Node Classification in Graphs
Pranav Maneriker, Aditya T. Vadlamani, Anutam Srinivasan, Yuntian He, Ali Payani, Srinivasan Parthasarathy Constrained Reinforcement Learning with Smoothed Log Barrier Function
Baohe Zhang, Yuan Zhang, Hao Zhu, Shengchao Yan, Thomas Brox, Joschka Boedecker Contextualized Messages Boost Graph Representations
Brian Godwin Lim, Galvin Brice Sy Lim, Renzo Roel Tan, Kazushi Ikeda Continual Learning on CLIP via Incremental Prompt Tuning with Intrinsic Textual Anchors
Haodong Lu, Xinyu Zhang, Kristen Moore, Jason Xue, Lina Yao, Anton van den Hengel, Dong Gong Continual Pre-Training of MoEs: How Robust Is Your Router?
Benjamin Thérien, Charles-Étienne Joseph, Zain Sarwar, Ashwinee Panda, Anirban Das, Shi-Xiong Zhang, Stephen Rawls, Sambit Sahu, Eugene Belilovsky, Irina Rish Controlled Model Debiasing Through Minimal and Interpretable Updates
Federico Di Gennaro, Thibault Laugel, Vincent Grari, Marcin Detyniecki Controlled Training Data Generation with Diffusion Models
Teresa Yeo, Andrei Atanov, Harold Luc Benoit, Aleksandr Alekseev, Ruchira Ray, Pooya Esmaeil Akhoondi, Amir Zamir Convergence Aspects of Hybrid Kernel SVGD
Anson MacDonald, Scott A Sisson, Sahani Pathiraja Cooperative Minibatching in Graph Neural Networks
Muhammed Fatih Balin, Dominique LaSalle, Umit Catalyurek Counterfactual Learning of Stochastic Policies with Continuous Actions
Houssam Zenati, Alberto Bietti, Matthieu Martin, Eustache Diemert, Pierre Gaillard, Julien Mairal CroissantLLM: A Truly Bilingual French-English Language Model
Manuel Faysse, Patrick Fernandes, Nuno M Guerreiro, António Loison, Duarte Miguel Alves, Caio Corro, Nicolas Boizard, João Alves, Ricardo Rei, Pedro Henrique Martins, Antoni Bigata Casademunt, François Yvon, Andre Martins, Gautier Viaud, Celine Hudelot, Pierre Colombo Cross Entropy Versus Label Smoothing: A Neural Collapse Perspective
Li Guo, George Andriopoulos, Zifan Zhao, Zixuan Dong, Shuyang Ling, Keith W. Ross Cross-Lingual Transfer in Programming Languages: An Extensive Empirical Study
Razan Baltaji, Saurabh Pujar, Martin Hirzel, Louis Mandel, Luca Buratti, Lav R. Varshney Cumulative Reasoning with Large Language Models
Yifan Zhang, Jingqin Yang, Yang Yuan, Andrew C Yao CyberThreat-Eval: Can Large Language Models Automate Real-World Threat Research?
Xiangsen Chen, Xuan Feng, Shuo Chen, Matthieu Maitre, Sudipto Rakshit, Diana Duvieilh, Ashley Picone, Nan Tang 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 Decoding-Based Regression
Xingyou Song, Dara Bahri Deep Active Learning in the Open World
Tian Xie, Jifan Zhang, Haoyue Bai, Robert D Nowak Deep Augmentation: Dropout as Augmentation for Self-Supervised Learning
Rickard Brüel Gabrielsson, Tongzhou Wang, Manel Baradad, Justin Solomon Deep Autoregressive Models as Causal Inference Engines
Daniel Jiwoong Im, Kevin Zhang, Nakul Verma, Kyunghyun Cho Deep Koopman Learning Using Noisy Data
Wenjian Hao, Devesh Upadhyay, Shaoshuai Mou Deep Neural Networks and Brain Alignment: Brain Encoding and Decoding (Survey)
Subba Reddy Oota, Zijiao Chen, Manish Gupta, Bapi Raju Surampudi, Gael Jobard, Frederic Alexandre, Xavier Hinaut DeepRRTime: Robust Time-Series Forecasting with a Regularized INR Basis
Chandramouli Shama Sastry, Mahdi Gilany, Kry Yik-Chau Lui, Martin Magill, Alexander Pashevich Deflated Dynamics Value Iteration
Jongmin Lee, Amin Rakhsha, Ernest K. Ryu, Amir-massoud Farahmand DELTA: Dual Consistency Delving with Topological Uncertainty for Active Graph Domain Adaptation
Pengyun Wang, Yadi Cao, Chris Russell, Yanxin Shen, Junyu Luo, Ming Zhang, Siyu Heng, Xiao Luo Demystifying Amortized Causal Discovery with Transformers
Francesco Montagna, Max Cairney-Leeming, Dhanya Sridhar, Francesco Locatello Dependency-Aware Maximum Likelihood Estimation for Active Learning
Beyza Kalkanli, Tales Imbiriba, Stratis Ioannidis, Deniz Erdogmus, Jennifer Dy Design Editing for Offline Model-Based Optimization
Ye Yuan, Youyuan Zhang, Can Chen, Haolun Wu, Melody Zixuan Li, Jianmo Li, James J. Clark, Xue Liu DiffCLIP: Differential Attention Meets CLIP
Hasan Abed Al Kader Hammoud, Bernard Ghanem Differentially Private Gradient Flow Based on the Sliced Wasserstein Distance
Ilana Sebag, Muni Sreenivas Pydi, Jean-Yves Franceschi, Alain Rakotomamonjy, Mike Gartrell, Jamal Atif, Alexandre Allauzen Diffusion Model Predictive Control
Guangyao Zhou, Sivaramakrishnan Swaminathan, Rajkumar Vasudeva Raju, J Swaroop Guntupalli, Wolfgang Lehrach, Joseph Ortiz, Antoine Dedieu, Miguel Lazaro-Gredilla, Kevin Patrick Murphy Dimension Reduction via Score Ratio Matching
Ricardo Baptista, Michael Brennan, Youssef Marzouk Discovering Group Dynamics in Coordinated Time Series via Hierarchical Recurrent Switching-State Models
Michael Wojnowicz, Kaitlin Gili, Preetish Rath, Eric Miller, Jeffrey W. Miller, Clifford Lee Hancock, Meghan O'Donovan, Seth Elkin-Frankston, Tad Brunye, Michael C Hughes Discrete Audio Tokens: More than a Survey!
Pooneh Mousavi, Gallil Maimon, Adel Moumen, Darius Petermann, Jiatong Shi, Haibin Wu, Haici Yang, Anastasia Kuznetsova, Artem Ploujnikov, Ricard Marxer, Bhuvana Ramabhadran, Benjamin Elizalde, Loren Lugosch, Jinyu Li, Cem Subakan, Phil Woodland, Minje Kim, Hung-yi Lee, Shinji Watanabe, Yossi Adi, Mirco Ravanelli DisDet: Exploring Detectability of Backdoor Attack on Diffusion Models
Yang Sui, Huy Phan, Jinqi Xiao, Tianfang Zhang, Zijie Tang, Cong Shi, Yan Wang, Yingying Chen, Bo Yuan Distributed Hierarchical Decomposition Framework for Multimodal Timeseries Prediction
Wei Ye, Prashant Khanduri, Jiangweizhi Peng, Feng Tian, Jun Gao, Jie Ding, Zhi-Li Zhang, Mingyi Hong Distributed Multi-Agent Lifelong Learning
Prithviraj Tarale, Edward Rietman, Hava T Siegelmann Distributional Reduction: Unifying Dimensionality Reduction and Clustering with Gromov-Wasserstein
Hugues Van Assel, Cédric Vincent-Cuaz, Nicolas Courty, Rémi Flamary, Pascal Frossard, Titouan Vayer Distributionally Robust Coreset Selection Under Covariate Shift
Tomonari Tanaka, Hiroyuki Hanada, Hanting Yang, Aoyama Tatsuya, Yu Inatsu, Akahane Satoshi, Yoshito Okura, Noriaki Hashimoto, Taro Murayama, Hanju Lee, Shinya Kojima, Ichiro Takeuchi Diversify, Don't Fine-Tune: Scaling up Visual Recognition Training with Synthetic Images
Zhuoran Yu, Chenchen Zhu, Sean Culatana, Raghuraman Krishnamoorthi, Fanyi Xiao, Yong Jae Lee Diversity Augmentation of Dynamic User Preference Data for Boosting Personalized Text Summarizers
Parthiv Chatterjee, Shivam R Sonawane, Amey Hengle, Aditya Tanna, Sourish Dasgupta, Tanmoy Chakraborty Diversity-Driven View Subset Selection for Indoor Novel View Synthesis
Zehao Wang, Han Zhou, Matthew B. Blaschko, Tinne Tuytelaars, Minye Wu Do Concept Bottleneck Models Respect Localities?
Naveen Janaki Raman, Mateo Espinosa Zarlenga, Juyeon Heo, Mateja Jamnik Does Confidence Calibration Improve Conformal Prediction?
HuaJun Xi, Jianguo Huang, Kangdao Liu, Lei Feng, Hongxin Wei Does Equivariance Matter at Scale?
Johann Brehmer, Sönke Behrends, Pim De Haan, Taco Cohen Don’t Judge Before You CLIP: A Unified Approach for Perceptual Tasks
Amit Zalcher, Navve Wasserman, Roman Beliy, Oliver Heinimann, Michal Irani Double Machine Learning Based Structure Identification from Temporal Data
Emmanouil Angelis, Francesco Quinzan, Ashkan Soleymani, Patrick Jaillet, Stefan Bauer Downstream Task Guided Masking Learning in Masked Autoencoders Using Multi-Level Optimization
Han Guo, Ramtin Hosseini, Ruiyi Zhang, Sai Ashish Somayajula, Ranak Roy Chowdhury, Rajesh K. Gupta, Pengtao Xie Dual Caption Preference Optimization for Diffusion Models
Amir Saeidi, Yiran Lawrence Luo, Agneet Chatterjee, Shamanthak Hegde, Bimsara Pathiraja, Yezhou Yang, Chitta Baral Dynamic Pricing in the Linear Valuation Model Using Shape Constraints
Daniele Bracale, Moulinath Banerjee, Yuekai Sun, Salam Turki, Kevin Stoll Early Classification of Time Series: A Survey and Benchmark
Aurélien Renault, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire Effective Backdoor Mitigation in Vision-Language Models Depends on the Pre-Training Objective
Sahil Verma, Gantavya Bhatt, Avi Schwarzschild, Soumye Singhal, Arnav Mohanty Das, Chirag Shah, John P Dickerson, Pin-Yu Chen, Jeff Bilmes Efficient and Flexible Neural Network Training Through Layer-Wise Feedback Propagation
Leander Weber, Jim Berend, Moritz Weckbecker, Alexander Binder, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin Efficient Diffusion Models: A Survey
Hui Shen, Jingxuan Zhang, Boning Xiong, Rui Hu, Shoufa Chen, Zhongwei Wan, Xin Wang, Yu Zhang, Zixuan Gong, Guangyin Bao, Chaofan Tao, Yongfeng Huang, Ye Yuan, Mi Zhang Efficient Few-Shot Continual Learning in Vision-Language Models
Aristeidis Panos, Rahaf Aljundi, Daniel Olmeda Reino, Richard E. Turner Efficient Hardware Scaling and Diminishing Returns in Large-Scale Training of Language Models
Jared Fernandez, Luca Wehrstedt, Leonid Shamis, Mostafa Elhoushi, Kalyan Saladi, Yonatan Bisk, Emma Strubell, Jacob Kahn Efficient Knowledge Injection in LLMs via Self-Distillation
Kalle Kujanpää, Pekka Marttinen, Harri Valpola, Alexander Ilin Efficient Multi-Agent Cooperation Learning Through Teammate Lookahead
Feng Chen, Xinwei Chen, Rong-Jun Qin, Cong Guan, Lei Yuan, Zongzhang Zhang, Yang Yu Efficient Reasoning Models: A Survey
Sicheng Feng, Gongfan Fang, Xinyin Ma, Xinchao Wang Efficient Vocabulary-Free Fine-Grained Visual Recognition in the Age of Multimodal LLMs
Hari Chandana Kuchibhotla, Sai Srinivas Kancheti, Abbavaram Gowtham Reddy, Vineeth N. Balasubramanian Elucidating the Design Choice of Probability Paths in Flow Matching for Forecasting
Soon Hoe Lim, Yijin Wang, Annan Yu, Emma Hart, Michael W. Mahoney, Sherry Li, N. Benjamin Erichson Emergent Corpus Pre-Training Benefits Vision Language Models
Makanjuola Adekunmi Ogunleye, Chase Vickery, Ismini Lourentzou Emergent Neural Network Mechanisms for Generalization to Objects in Novel Orientations
Avi Cooper, Daniel Harari, Tomotake Sasaki, Spandan Madan, Hanspeter Pfister, Pawan Sinha, Xavier Boix Emergent Representations in Networks Trained with the Forward-Forward Algorithm
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