TMLR 2026

671 papers

\textsc{PGO-BEN}: Proxy-Guided Orthogonalization and Beta Ensembling for Few-Shot Domain-Incremental Learning Samrat Mukherjee, Thivyanth Venkateswaran, Eric Nuertey Coleman, Luigi Quarantiello, Julio Hurtado, Vincenzo Lomonaco, Gemma Roig, Subhasis Chaudhuri, Biplab Banerjee

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\texttt{Complex-Edit}: CoT-like Instruction Generation for Complexity-Controllable Image Editing Benchmark Siwei Yang, Mude Hui, Bingchen Zhao, Yuyin Zhou, Nataniel Ruiz, Cihang Xie

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$\texttt{C2-DPO}$: Constrained Controlled Direct Preference Optimization Kavosh Asadi, Xingzi Xu, Julien Han, Ege Beyazit, Idan Pipano, Dominique Perrault-Joncas, Shoham Sabach, Mohammad Ghavamzadeh, Karim Bouyarmane

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$\texttt{LucidAtlas}$: Learning Uncertainty-Aware, Covariate-Disentangled, Individualized Atlas Representations Yining Jiao, Sreekalyani Bhamidi, Carlton Jude Zdanski, Huaizhi Qu, Julia S Kimbell, Andrew Prince, Cameron P Worden, Samuel Kirse, Christopher Rutter, Benjamin H Shields, Jisan Mahmud, Tianlong Chen, Marc Niethammer

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$\texttt{SEM-CTRL}$: Semantically Controlled Decoding Mohammad Albinhassan, Pranava Madhyastha, Alessandra Russo

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A Bayesian Approach to Segmentation with Noisy Labels via Spatially Correlated Distributions Ryu Tadokoro, Tsukasa Takagi, Shin-ichi Maeda

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A Bayesian Bootstrap Framework for Mutual Information Neural Estimation: Bridging Classical Mutual Information Learning and Bayesian Nonparametric Learning Forough Fazeli-Asl, Michael Minyi Zhang, Linglong Kong, Bei Jiang

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A Bayesian Nonparametric Perspective on Mahalanobis Distance for Out of Distribution Detection Randolph Linderman, Noah Cowan, Yiran Chen, Scott Linderman

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A Closer Look at In-Distribution vs. Out-of-Distribution Accuracy for Open-Set Test-Time Adaptation Zefeng Li, Evan Shelhamer

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A Complete Decomposition of KL Error Using Refined Information and Mode Interaction Selection James Enouen, Mahito Sugiyama

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A Concept-Centric Approach to Multi-Modality Learning Yuchong Geng, Ao Tang

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A Distributed Generative AI Approach for Heterogeneous Multi-Domain Environments Under Data Sharing Constraints Youssef Tawfilis, Hossam Amer, Minar El-Aasser, Tallal Elshabrawy

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A Faster Generalized Two-Stage Approximate Top-K B L Yashas Samaga, Varun Yerram, Spandana Raj Babbula, Prateek Jain, Praneeth Netrapalli

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A Lower Bound for the Number of Linear Regions of Ternary ReLU Regression Neural Networks Yuta Nakahara, Manabu Kobayashi, Toshiyasu Matsushima

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A Multi-Fidelity Control Variate Approach for Policy Gradient Estimation Xinjie Liu, Cyrus Neary, Kushagra Gupta, Wesley A. Suttle, Christian Ellis, Ufuk Topcu, David Fridovich-Keil

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A Multilevel Low-Rank Newton Method with Super-Linear Convergence Rate and Its Application to Non-Convex Problems Nick Tsipinakis, Panagiotis Tigas, Panos Parpas

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A Practical Algorithm for Feature-Rich, Non-Stationary Bandit Problems William Loh, Sajib Kumer Sinha, Ankur Agarwal, Pascal Poupart

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A Quotient Homology Theory of Representation in Neural Networks Kosio Beshkov

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A Second Order Majorant Algorithm for Nonnegative Matrix Factorization Mai Quyen Pham, Jeremy Cohen, Thierry Chonavel

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A Simple and Effective Reinforcement Learning Method for Text-to-Image Diffusion Fine-Tuning Shashank Gupta, Chaitanya Ahuja, Tsung-Yu Lin, Sreya Dutta Roy, Harrie Oosterhuis, Maarten de Rijke, Satya Narayan Shukla

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A Simple Connection from Loss Flatness to Compressed Neural Representations Shirui Chen, Stefano Recanatesi, Eric Todd SheaBrown

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A Survey of Model Architectures in Information Retrieval Zhichao Xu, Fengran Mo, Zhiqi Huang, Crystina Zhang, Puxuan Yu, Bei Wang Phillips, Jimmy Lin, Vivek Srikumar

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A‌ Survey of Reasoning in Autonomous Driving Systems: Open Challenges and Emerging Paradigms Kejin Yu, Yuhan Sun, Taiqiang Wu, Ruixu Zhang, Zhiqiang Lin, Yuxin Meng, Junjie Wang, Yujiu Yang

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A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence Huan-ang Gao, Jiayi Geng, Wenyue Hua, Mengkang Hu, Xinzhe Juan, Hongzhang Liu, Shilong Liu, Jiahao Qiu, Xuan Qi, Qihan Ren, Yiran Wu, Hongru Wang, Han Xiao, Yuhang Zhou, Shaokun Zhang, Jiayi Zhang, Jinyu Xiang, Yixiong Fang, Qiwen Zhao, Dongrui Liu, Cheng Qian, Zhenhailong Wang, Minda Hu, Huazheng Wang, Qingyun Wu, Heng Ji, Mengdi Wang

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A Survey of Token Compression for Efficient Multimodal Large Language Models Kele Shao, Keda Tao, Kejia Zhang, Sicheng Feng, Mu Cai, Yuzhang Shang, Haoxuan You, Can Qin, Yang Sui, Huan Wang

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A Survey on Deep Learning Approaches for Tabular Data Generation: Utility, Alignment, Fidelity, Privacy, Diversity, and Beyond Mihaela C. Stoian, Eleonora Giunchiglia, Thomas Lukasiewicz

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A Survey on Federated Fine-Tuning of Large Language Models Yebo Wu, Chunlin Tian, Jingguang Li, He Sun, KaHou Tam, Zhanting Zhou, Haicheng Liao, Jing Xiong, Zhijiang Guo, Li Li, Cheng-zhong Xu

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A Survey on Over-Smoothing and Over-Squashing: Unified Propagation Perspectives on Graph Neural Networks and Transformers Alvaro Arroyo, Federico Barbero, Hugh Blayney, Michael M. Bronstein, Xiaowen Dong, Pietro Lio, Razvan Pascanu, Pierre Vandergheynst

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A Systematic Assessment of Weak-to-Strong Confidence Prediction in Large Language Models Tracy Yixin Zhu, Yukai Yang, Marco Morucci, Tim G. J. Rudner

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A Systematic Evaluation of Out-of-Distribution Generalization in Crop Yield Prediction Aditya Chakravarty

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A Systematic Study of In-the-Wild Model Merging for Large Language Models Oğuz Kağan Hitit, Leander Girrbach, Zeynep Akata

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A Tale of Two Goals: Leveraging Short Term Goals Performs Best in Multi-Goal Scenarios Olivier Serris, Stephane Doncieux, Olivier Sigaud

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A Tighter Bound for Reward Learning in Reinforcement Learning from Human Feedback Guoxi Chen, Xing Chen, Bo An, Ya Zhang

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A Unified Framework for Tabular Generative Modeling: Loss Functions, Benchmarks, and Improved Multi-Objective Bayesian Optimization Approaches Minh Hoang Vu, Daniel Edler, Carl Wibom, Tommy Löfstedt, Beatrice Melin, Martin Rosvall

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A Unifying Framework for Parallelizing Sequential Models with Linear Dynamical Systems Xavier Gonzalez, E. Kelly Buchanan, Hyun Dong Lee, Jerry Weihong Liu, Ke Alexander Wang, David M. Zoltowski, Leo Kozachkov, Christopher Re, Scott Linderman

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A Watermark for Black-Box Language Models Dara Bahri, John Frederick Wieting

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ABCDE: Agentic-Based Controlled Dynamic Erasure for Intent-Aware Safety Reasoning Ping Liu, Chi Zhang

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AC-PKAN: Attention-Enhanced and Chebyshev Polynomial-Based Physics-Informed Kolmogorov–Arnold Networks Hangwei Zhang, Zhimu Huang, Yan Wang

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AC$\oplus$DC Search: Behind the Winning Solution to the FlyWire Graph-Matching Challenge Daniel Lee, Arie Matsliah, Lawrence K. Saul

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Accelerating Inference of Discrete Autoregressive Normalizing Flows by Selective Jacobi Decoding Jiaru Zhang, Juanwu Lu, Xiaoyu Wu, Ziran Wang, Ruqi Zhang

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Accounting for Missing Covariates in Heterogeneous Treatment Estimation Khurram Yamin, Vibhhu Sharma, Edward Kennedy, Bryan Wilder

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Accurate Split Learning on Noisy Signals Hang Xu, Subhajit Maity, Aritra Dutta, Xin Li, Panos Kalnis

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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

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Achieving Faster than O(1/t) Convergence in General Convex Federated Learning Jie Liu, Zuang Wang, Yongqiang Wang

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Achieving Global Flatness in Decentralized Learning with Heterogeneous Data Sakshi Choudhary, Sai Aparna Aketi, Kaushik Roy

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Achieving Tighter Finite-Time Rates for Heterogeneous Federated Stochastic Approximation Under Markovian Sampling Feng Zhu, Aritra Mitra, Robert W. Heath

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ActionEQA: Action Interface for Embodied Question Answering Tianwei Bao, Qineng Wang, Kangrui Wang, Mingkai Deng, Guangyi Liu, Jiayuan Mao, Lawrence Birnbaum, Zhiting Hu, Eric P. Xing, Zhaoran Wang, Manling Li

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Active Teacher Selection for Reward Learning Rachel Freedman, Justin Svegliato, Kyle Hollins Wray, Stuart Russell

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AdaCtrl: Towards Adaptive and Controllable Reasoning via Difficulty-Aware Budgeting Shijue Huang, Hongru Wang, Wanjun Zhong, Zhaochen Su, Jiazhan Feng, Bowen Cao, Yi R. Fung

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AdaCubic: An Adaptive Cubic Regularization Optimizer for Deep Learning Ioannis Tsingalis, Constantine Kotropoulos, Corentin Briat

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Adapt via Bayesian Nonparametric Clustering: Fine-Grained Classification for Model Recycling Under Domain and Category Shift Zeya Wang, Longwen Shang, Yang Ni, Chenglong Ye

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ADAPT: Adaptive Prompt Tuning for Vision-Language Models Zhenhan Huang, Tejaswini Pedapati, Pin-Yu Chen, Jianxi Gao

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Adapting Language Models to Produce Good Class Probabilities for Classification Tasks Lautaro Estienne, Matias Vera, Elizabeth Fons, Elena Kochkina, Pablo Piantanida, Luciana Ferrer

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Adapting Vision Transformers to Ultra-High Resolution Semantic Segmentation with Relay Tokens Yohann Perron, Vladyslav Sydorov, Christophe Pottier, Loic Landrieu

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Adaptive Conformal Prediction for Quantum Machine Learning Douglas Spencer, Samual Nicholls, Michele Caprio

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Adaptive Model Selection in Offline Contextual MDP's Without Stationarity Riddhiman Bhattacharya, Sayak Chakrabarty, Imon Banerjee

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Adaptive Multi-Frame Sampling for Consistent Zero-Shot Text-to-Video Editing Thérèse Tisseau des Escotais, Clément Rambour, Bertrand Leroy, Arnaud Breloy

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Adaptive Online Mirror Descent for Tchebycheff Scalarization in Multi-Objective Learning Meitong Liu, Xiaoyuan Zhang, Chulin Xie, Kate Donahue, Han Zhao

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Addition Is Almost All You Need: Compressing Large Language Models with Double Binary Factorization Vladimír Boža, Vladimír Macko

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ADiff4TPP: Asynchronous Diffusion Models for Temporal Point Processes Amartya Mukherjee, Ruizhi Deng, He Zhao, Yuzhen Mao, Leonid Sigal, Frederick Tung

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Advantage Shaping as Surrogate Reward Maximization: Unifying Pass@K Policy Gradients Christos Thrampoulidis, Sadegh Mahdavi, Wenlong Deng

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Adversarial Attacks in Weight-Space Classifiers Tamir Shor, Ethan Fetaya, Chaim Baskin, Alex M. Bronstein

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Adversarial Attacks on Multimodal Large Language Models: A Comprehensive Survey Bhavuk Jain, Sercan O Arik, Hardeo Kumar Thakur

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Adversarial Vulnerability from On-Manifold Inseparability and Poor Off-Manifold Convergence Rajdeep Haldar, Yue Xing, Qifan Song, Guang Lin

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AI Security in the Foundation Model Era: A Comprehensive Survey from a Unified Perspective Zhenyi Wang, Siyu Luan

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AIMing for Standardised Explainability Evaluation in GNNs: A Framework and Case Study on Graph Kernel Networks Magdalena Proszewska, Siddharth N

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Algorithmic Recourse in Abnormal Multivariate Time Series Xiao Han, Lu Zhang, Yongkai Wu, Shuhan Yuan

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Algorithms for the Preordering Problem and Their Application to the Task of Jointly Clustering and Ordering the Accounts of a Social Network Jannik Irmai, Maximilian Moeller, Bjoern Andres

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Amortized Bayesian Workflow Chengkun Li, Aki Vehtari, Paul-Christian Bürkner, Stefan T. Radev, Luigi Acerbi, Marvin Schmitt

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Amplified Patch-Level Differential Privacy for Free via Random Cropping Kaan Durmaz, Jan Schuchardt, Sebastian Schmidt, Stephan Günnemann

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An Analysis of Distributional Reinforcement Learning with Gaussian Mixtures Mathis Antonetti, Henrique Donancio, Florence Forbes

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An Efficient Subset Selection Strategy Using Text-Guided Data Attribution to Mitigate Simplicity Bias Kumar Shubham, Pranav Sastry, Prathosh Ap

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An Information-Theoretic Analysis of Thompson Sampling for Logistic Bandit Problems Amaury Gouverneur, Tobias Oechtering, Mikael Skoglund

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Analyzing Best-Response Dynamics for Cooperation in Markov Potential Games Dingyang Chen, Xiaoling Zeng, Thinh T. Doan, Qi Zhang

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Any Image Restoration via Efficient Spatial-Frequency Degradation Adaptation Bin Ren, Eduard Zamfir, Zongwei Wu, Yawei Li, Yidi Li, Danda Pani Paudel, Radu Timofte, Ming-Hsuan Yang, Luc Van Gool, Nicu Sebe

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Anytime Verified Agents: Adaptive Compute Allocation for Reliable LLM Reasoning Under Budget Constraints Dipkumar Patel

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Approximately Equivariant Recurrent Generative Models for Quasi-Periodic Time Series with a Progressive Training Scheme Ruwen Fulek, Markus Lange-Hegermann

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Are Foundation Models for Computer Vision Good Conformal Predictors? Leo Fillioux, Julio Silva-Rodríguez, Ismail Ben Ayed, Paul-Henry Cournède, Maria Vakalopoulou, Stergios Christodoulidis, Jose Dolz

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Are Time-Indexed Foundation Models the Future of Time Series Imputation? Etienne Le Naour, Tahar Nabil, Adrien Petralia, Ghislain Agoua

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Are Vision Language Models Robust to Classic Uncertainty Challenges? Xi Wang, Eric Nalisnick

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ASMa: Asymmetric Spatio-Temporal Masking for Skeleton Action Representation Learning Aman Anand, Amir Eskandari, Elyas Rashno, Farhana Zulkernine

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Asymptotically and Minimax Optimal Regret Bounds for Multi-Armed Bandits with Abstention Junwen Yang, Tianyuan Jin, Vincent Y. F. Tan

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Auditing Predictive Models for Intersectional Biases Kate Boxer, Edward McFowland Iii, Daniel B. Neill

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Augmented Mixup Procedure for Privacy-Preserving Collaborative Training Mihail-Iulian Pleșa, Fabrice Clérot, Simona Elena David, Robert Poenaru

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Augmented Vision-Language Models: A Systematic Review Anthony C Davis, Burhan A. Sadiq, Tianmin Shu, Chien-Ming Huang

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Augmenting Molecular Graphs with Geometries via Machine Learning Interatomic Potentials Cong Fu, Yuchao Lin, Zachary Krueger, Haiyang Yu, Maho Nakata, Jianwen Xie, Emine Kucukbenli, Xiaofeng Qian, Shuiwang Ji

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Autofocus Retrieval: An Effective Pipeline for Multi-Hop Question Answering with Semi-Structured Knowledge Derian Boer, Stephen Linus Roth, Stefan Kramer

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Automated Attention Pattern Discovery at Scale in Large Language Models Jonathan Katzy, Razvan Mihai Popescu, Erik Mekkes, Arie van Deursen, Maliheh Izadi

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BalancedDPO: Adaptive Multi-Metric Alignment Dipesh Tamboli, Souradip Chakraborty, Aditya Malusare, Biplab Banerjee, Amrit Singh Bedi, Vaneet Aggarwal

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Batch Entanglement Detection in Parameterized Qubit States Using Classical Bandit Algorithms K. Bharati, Vikesh Siddhu, Krishna Jagannathan

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Bayesian Ensembling: Insights from Online Optimization and Empirical Bayes Daniel Waxman, Fernando Llorente, Petar Djuric

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Bayesian Network Structure Discovery Using Large Language Models Yinghuan Zhang, Yufei Zhang, Parisa Kordjamshidi, Zijun Cui

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Bayesian Sensitivity of Causal Inference Estimators Under Evidence-Based Priors Nikita Dhawan, Daniel Shen, Leonardo Cotta, Chris J. Maddison

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Benchmarking Missing Data Imputation Methods in Socioeconomic Surveys Siyi Sun, David Antony Selby, Yunchuan Huang, Ayush Patnaik, Sebastian Josef Vollmer, Seth Flaxman, Anisoara Calinescu

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BenchOverflow: Measuring Overflow in Large Language Models via Plain-Text Prompts Erin Feiglin, Nir Hutnik, Raz Lapid

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Better Language Models Exhibit Higher Visual Alignment Jona Ruthardt, Gertjan J. Burghouts, Serge Belongie, Yuki M Asano

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Beyond Accuracy: What Matters in Designing Well-Behaved Image Classification Models? Robin Hesse, Doğukan Bağcı, Bernt Schiele, Simone Schaub-Meyer, Stefan Roth

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Beyond Affinity: A Benchmark of 1d, 2D, and 3D Methods Reveals Critical Trade-Offs in Structure-Based Drug Design Kangyu Zheng, Kai Zhang, Jiale Tan, Xuehan Chen, Yingzhou Lu, Zaixi Zhang, Lichao Sun, Marinka Zitnik, Tianfan Fu, Zhiding Liang

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Beyond Expectations: Learning with Stochastic Dominance Made Practical Shicong Cen, Jincheng Mei, Hanjun Dai, Dale Schuurmans, Yuejie Chi, Bo Dai

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Beyond Semantics: The Unreasonable Effectiveness of Reasonless Intermediate Tokens Karthik Valmeekam, Vardhan Palod, Kaya Stechly, Atharva Gundawar, Subbarao Kambhampati

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Bi-Level Hierarchical Neural Contextual Bandits for Online Recommendation Yunzhe Qi, Yao Zhou, Yikun Ban, Allan Stewart, Chuanwei Ruan, Jiachuan He, Shishir Kumar Prasad, Haixun Wang, Jingrui He

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BiSSL: Enhancing the Alignment Between Self-Supervised Pretraining and Downstream Fine-Tuning via Bilevel Optimization Gustav Wagner Zakarias, Lars Kai Hansen, Zheng-Hua Tan

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BN-Pool: Bayesian Nonparametric Pooling for Graphs Daniele Castellana, Filippo Maria Bianchi

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BNEM: A Boltzmann Sampler Based on Bootstrapped Noised Energy Matching RuiKang OuYang, Bo Qiang, José Miguel Hernández-Lobato

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Boosting Text Encoder for Personalized Text-to-Image Generation NaHyeon Park, Kunhee Kim, Hyunjung Shim

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Bootstrapping Task Spaces for Self-Improvement Minqi Jiang, Andrei Lupu, Yoram Bachrach

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BrightDreamer: Generic 3D Gaussian Generative Framework for Fast Text-to-3D Synthesis Lutao Jiang, Xu Zheng, Yuanhuiyi Lyu, Jiazhou Zhou, Lin Wang

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BrowserAgent: Building Web Agents with Human-Inspired Web Browsing Actions Tao Yu, Zhengbo Zhang, Zhiheng Lyu, Junhao Gong, Hongzhu Yi, Xinming Wang, Yuxuan Zhou, Jiabing Yang, Ping Nie, Yan Huang, Wenhu Chen

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Budget-Optimized Crowdworker Allocation Sha Lai, Prakash Ishwar, Margrit Betke

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Byzantine-Robust Gossip: Insights from a Dual Approach Renaud Gaucher, Hadrien Hendrikx, Aymeric Dieuleveut

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CacheFlow: Fast Human Motion Prediction by Cached Normalizing Flow Takahiro Maeda, Jinkun Cao, Norimichi Ukita, Kris Kitani

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CADmium: Fine-Tuning Code Language Models for Text- Driven Sequential CAD Design Prashant Govindarajan, Davide Baldelli, Jay Pathak, Quentin Fournier, Sarath Chandar

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CAE: Repurposing the Critic as an Explorer in Deep Reinforcement Learning Yexin Li

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Calibration Enhanced Decision Maker: Towards Trustworthy Sequential Decision-Making with Large Sequence Models Haoyuan Sun, Bo Xia, Yifu Luo, Tiantian Zhang, Xueqian Wang

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CAPE: Generalized Convergence Prediction Across Architectures Without Full Training Alireza Pourali, Arian Boukani, Hamzeh Khazaei

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CARINOX: Inference-Time Scaling with Category-Aware Reward-Based Initial Noise Optimization and Exploration Seyed Amir Kasaei, Ali Aghayari, Arash Marioriyad, Niki Sepasian, Shayan Baghayi Nejad, MohammadAmin Fazli, Mahdieh Soleymani Baghshah, Mohammad Hossein Rohban

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CatScreen: A Large MultiModal Benchmark Dataset for Cataract Screening Mahapara Khurshid, Sonam Kumar, Dr Anusuya Bhattacharyya, Dhruve Kiyawat, Anshul Chauhan, Suklengmung Buragohain, Harsha Bhattacharjee, Limalemla Jamir, Vishali Gupta, Mona Duggal, Mayank Vatsa, Richa Singh

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CauFR-TS: Causal Time-Series Identifiability via Factorized Representations Ayanabha Ghosh, Debasis Das, Asif Ekbal

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Causal Decoding for Hallucination-Resistant Multimodal Large Language Models Shiwei Tan, Hengyi Wang, Weiyi Qin, Qi Xu, Zhigang Hua, Hao Wang

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Causal Graph Learning via Distributional Invariance of Cause-Effect Relationship Nang Hung Nguyen, Phi Le Nguyen, Thao Nguyen Truong, Trong Nghia Hoang, Masashi Sugiyama

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CEPAE: Conditional Entropy-Penalized Autoencoders for Time Series Counterfactuals Tomas Garriga, Gerard Sanz, Eduard Serrahima de Cambra, Axel Brando

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Characterizing Evolution in Expectation-Maximization Estimates for Overspecified Mixed Linear Regression Zhankun Luo, Abolfazl Hashemi

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CI-CBM: Class-Incremental Concept Bottleneck Model for Interpretable Continual Learning Amirhosein Javadi, Tuomas Oikarinen, Tara Javidi, Tsui-Wei Weng

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Classification of High-Dimensional Data with Spiked Covariance Matrix Structure Yin-Jen Chen, Minh Tang

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ClimateAgent: Multi-Agent Orchestration for Complex Climate Data Science Workflows Chenyue Li, Hyeonjae Kim, Wen Deng, Mengxi Jin, Huang Wen, Mengqian Lu, Binhang Yuan

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CLIP-SVD: Efficient and Interpretable Vision–Language Adaptation via Singular Values Taha Koleilat, Hassan Rivaz, Yiming Xiao

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Clus-UCB: A Near-Optimal Algorithm for Clustered Bandits Aakash Gore, Prasanna Chaporkar

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CodePDE: An Inference Framework for LLM-Driven PDE Solver Generation Shanda Li, Tanya Marwah, Junhong Shen, Weiwei Sun, Andrej Risteski, Yiming Yang, Ameet Talwalkar

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Collaborative QA Using Interacting LLMs. Impact of Network Structure, Node Capability and Distributed Data. Adit Jain, Vikram Krishnamurthy, Yiming Zhang

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COLT: Enhancing Video Large Language Models with Continual Tool Usage Yuyang Liu, Meng Cao, Xinyuan Shi, Xiaodan Liang

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Combinatorial Capacity of modReLU Complex Networks: VC-Dimension Bounds and Lower Limits Mehmet Altunören

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Communication-Efficient Federated AUC Maximization with Cyclic Client Participation Umesh-Vangapally, Wenhan Wu, Chen Chen, Zhishuai Guo

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Compromising Honesty and Harmlessness in Language Models via Covert Deception Attacks Laurène Vaugrante, Francesca Carlon, Maluna Menke, Thilo Hagendorff

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Concept Flow Models: Anchoring Concept-Based Reasoning with Hierarchical Bottlenecks Ya Wang, Adrian Paschke

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Condense, Don't Just Prune: Enhancing Efficiency and Performance in MoE Layer Pruning Mingyu Cao, Gen Li, Jie Ji, Jiaqi Zhang, Ajay Jaiswal, Li Shen, Xiaolong Ma, Shiwei Liu, Lu Yin

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Conformal Calibration of Statistical Confidence Sets Luben Miguel Cruz Cabezas, Guilherme Soares, Thiago Ramos, Rafael Bassi Stern, Rafael Izbicki

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Consistency Trajectory Planning: High-Quality and Efficient Trajectory Optimization for Offline Model-Based Reinforcement Learning Guanquan Wang, Takuya Hiraoka, Yoshimasa Tsuruoka

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Constant Rate Scheduling: A General Framework for Optimizing Diffusion Noise Schedule via Distributional Change Shuntaro Okada, Kenji Doi, Ryota Yoshihashi, Hirokatsu Kataoka, Tomohiro Tanaka

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Constraint-Aware Flow Matching via Randomized Exploration Zhengyan Huan, Jacob Boerma, Liping Liu, Shuchin Aeron

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Context-Aware Learned Mesh-Based Simulation via Trajectory-Level Meta-Learning Philipp Dahlinger, Niklas Freymuth, Tai Hoang, Tobias Würth, Michael Volpp, Luise Kärger, Gerhard Neumann

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Contextual Learning for Anomaly Detection in Tabular Data Spencer King, Zhilu Zhang, Ruofan Yu, Baris Coskun, Wei Ding, Qian Cui

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Continual Robot Learning via Language-Guided Skill Acquisition Shuo Cheng, Zhaoyi Li, Kelin Yu, Danfei Xu

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Continuous Treatment Effect Estimation with Cauchy-Schwarz Divergence Information Bottleneck Louk van Remmerden, Shiqin Tang, Shujian Yu

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Contrastive VQ Priors for Multi-Class Plaque Segmentation via SAM Adaptation Ruan Yizhe, Yusuke Kurose, Junichi Iho, Yoji Tokunaga, Makoto Horie, Yusaku Hayashi, Keisuke Nishizawa, Yasushi Koyama, Tatsuya Harada

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Convergence of Stochastic Gradient Langevin Dynamics in the Lazy Training Regime Noah Oberweis, Semih Cayci

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Convex Optimization with Local Label Differential Privacy: Tight Bounds in All Privacy Regimes Lynn Chua, Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Ziteng Sun, Chiyuan Zhang

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Correctness-Aware Knowledge Distillation for Enhanced Student Learning Ishan Mishra, Deepak Mishra, Jinjun Xiong

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Cost-Aware Routing for Efficient Text-to-Image Generation Qinchan Li, Kenneth Chen, Changyue Su, Wittawat Jitkrittum, Qi Sun, Patsorn Sangkloy

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Cost-Free Personalization via Information-Geometric Projection in Bayesian Federated Learning Nour Jamoussi, Giuseppe Serra, Photios A. Stavrou, Marios Kountouris

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COunterfactual Reasoning for Temporal EXplanations: Plausible and Robust Explanations for EEG-Based Seizure Detection Martina Zannotti, Bardh Prenkaj, Marco Piangerelli, Flavio Corradini, Gjergji Kasneci

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Counting Still Counts: Understanding Neural Complex Query Answering Through Query Relaxation Yannick Brunink, Daniel Daza, Yunjie He, Michael Cochez

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Covariance Density Neural Networks Om Roy, Yashar Moshfeghi, Keith M Smith

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CP-POL + PPI: Conformal Guarantees in Partially-Observed Label Space Christian Ngnie

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CRMArena-Pro: Holistic Assessment of LLM Agents Across Diverse Business Scenarios and Interactions Kung-Hsiang Huang, Akshara Prabhakar, Onkar Thorat, Divyansh Agarwal, Prafulla Kumar Choubey, Yixin Mao, Silvio Savarese, Caiming Xiong, Chien-Sheng Wu

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Cropping Outperforms Dropout as an Augmentation Strategy for Self-Supervised Training of Text Embeddings Rita González-Márquez, Philipp Berens, Dmitry Kobak

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CRoPS: A Training-Free Hallucination Mitigation Framework for Vision-Language Models Neeraj Anand, Samyak Jha, Udbhav Bamba, Rahul Rahaman

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Curvature-Aware Safety Restoration in LLMs Fine-Tuning Thong Bach, Thanh Nguyen-Tang, Dung Nguyen, Thao Minh Le, Truyen Tran

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D-Garment: Physically Grounded Latent Diffusion for Dynamic Garment Deformations Antoine Dumoulin, Adnane Boukhayma, Laurence Boissieux, Bharath Bhushan Damodaran, Pierre Hellier, Stefanie Wuhrer

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DASB - Discrete Audio and Speech Benchmark Pooneh Mousavi, Jarod Duret, Darius Petermann, Artem Ploujnikov, Luca Della Libera, Anastasia Kuznetsova, Cem Subakan, Mirco Ravanelli

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Data Compressibility Quantifies LLM Memorization Yizhan Huang, Zhe Yang, Meifang Chen, Huang Nianchen, Jianping Zhang, Michael R. Lyu

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Dealing with Uncertainty in Contextual Anomaly Detection Luca Bindini, Lorenzo Perini, Stefano Nistri, Jesse Davis, Paolo Frasconi

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Debiasing Diffusion Models via Score Guidance Piyush Tiwary, Prabhav Verma, Prathosh Ap

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deCIFer: Crystal Structure Prediction from Powder Diffraction Data Using Autoregressive Language Models Frederik Lizak Johansen, Ulrik Friis-Jensen, Erik B Dam, Kirsten M. Ø. Jensen, Rocío Mercado, Raghavendra Selvan

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Decoding Generalization from Memorization in Deep Neural Networks Simran Ketha, Venkatakrishnan Ramaswamy

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Decoding Safety Feedback from Diverse Raters: A Data-Driven Lens on Responsiveness to Severity Pushkar Mishra, Charvi Rastogi, Stephen R Pfohl, Alicia Parrish, Tian Huey Teh, Roma Patel, Mark Diaz, Ding Wang, Michela Paganini, Vinodkumar Prabhakaran, Lora Aroyo, Verena Rieser

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Deep Multimodal Learning with Missing Modality: A Survey Renjie Wu, Hu Wang, Hsiang-Ting Chen, Gustavo Carneiro

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DeepSeek-R1 Thoughtology: Let’s Think About LLM Reasoning Sara Vera Marjanovic, Arkil Patel, Vaibhav Adlakha, Milad Aghajohari, Parishad BehnamGhader, Mehar Bhatia, Aditi Khandelwal, Austin Kraft, Benno Krojer, Xing Han Lù, Nicholas Meade, Dongchan Shin, Amirhossein Kazemnejad, Gaurav Kamath, Marius Mosbach, Karolina Stanczak, Siva Reddy

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Delta-Influence: Identifying Poisons via Influence Functions Wenjie Li, Jiawei Li, Pengcheng Zeng, Christian Schroeder de Witt, Ameya Prabhu, Amartya Sanyal

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Demystifying MaskGIT Sampler and Beyond: Adaptive Order Selection in Masked Diffusion Satoshi Hayakawa, Yuhta Takida, Masaaki Imaizumi, Hiromi Wakaki, Yuki Mitsufuji

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Denoising Diffusions with Optimal Transport: Localization, Curvature, and Multi-Scale Complexity Tengyuan Liang, Kulunu Dharmakeerthi, Takuya Koriyama

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Denoising Hamiltonian Network for Physical Reasoning Congyue Deng, Brandon Y. Feng, Cecilia Garraffo, Alan Garbarz, Robin Walters, William T. Freeman, Leonidas Guibas, Kaiming He

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Density-Aware Farthest Point Sampling Paolo Climaco, Jochen Garcke

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Detecting Generalization Deficits in Large Language and Reasoning Models by Using Natural Variations in Simple Problems Marianna Nezhurina, Lucia Cipolina-Kun, Mehdi Cherti, Jenia Jitsev

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DiffCATS: Causally Associated Time-Series Generation Through Diffusion Models Giuseppe Masi, Andrea Coletta, Elizabeth Fons, Svitlana Vyetrenko, Novella Bartolini

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Differentiable Cluster Discovery in Temporal Graphs Md Hafizur Rahman, Chi-Guhn Lee

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Differentially Private and Scalable Estimation of the Network Principal Component Alireza Khayatian, Anil Vullikanti, Aritra Konar

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Differentially Private Conformal Prediction via Quantile Binary Search Ogonnaya Michael Romanus, Roberto Molinari

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DiffKGW: Stealthy and Robust Diffusion Model Watermarking Tianxin Wei, Ruizhong Qiu, Yifan Chen, Yunzhe Qi, Jiacheng Lin, Wenxuan Bao, Wenju Xu, Sreyashi Nag, Ruirui Li, Hanqing Lu, Zhengyang Wang, Chen Luo, Hui Liu, Suhang Wang, Jingrui He, Qi He, Xianfeng Tang

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Diffusion Models Are Secretly Zero-Shot 3DGS Harmonizers Vsevolod Skorokhodov, Nikita Durasov, Pascal Fua

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Diffusion Models for Solving Inverse Problems via Posterior Sampling with Piecewise Guidance Saeed Mohseni-Sehdeh, Walid Saad, Kei Sakaguchi, Tao Yu

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Diffusion Posterior Sampling for Simulation-Based Inference in Tall Data Settings Julia Linhart, Gabriel Cardoso, Alexandre Gramfort, Sylvain Le Corff, Pedro L. C. Rodrigues

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DiffusionRollout: Uncertainty-Aware Rollout Planning in Long-Horizon PDE Solving Seungwoo Yoo, Juil Koo, Daehyeon Choi, Minhyuk Sung

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Dimension-Free Error Estimate for Diffusion Model and Optimal Scheduling Valentin De Bortoli, Romuald Elie, Anna Kazeykina, Zhenjie Ren, Jiacheng Zhang

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DINOv3 Oriane Siméoni, Huy V. Vo, Maximilian Seitzer, Federico Baldassarre, Maxime Oquab, Cijo Jose, Vasil Khalidov, Marc Szafraniec, Seung Eun Yi, Michael Ramamonjisoa, Francisco Massa, Daniel Haziza, Luca Wehrstedt, Jianyuan Wang, Timothée Darcet, Théo Moutakanni, Leonel Sentana, Claire Roberts, Andrea Vedaldi, Jamie Tolan, John Brandt, Camille Couprie, Julien Mairal, Herve Jegou, Patrick Labatut, Piotr Bojanowski

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Discontinuity-Preserving Image Super-Resolution Using MRF-Regularized One-Step Diffusion Sanchar Palit, Subhasis Chaudhuri, Biplab Banerjee

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Discovering Symbolic Differential Equations with Symmetry Invariants Jianke Yang, Manu Bhat, Bryan Hu, Yadi Cao, Nima Dehmamy, Robin Walters, Rose Yu

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Disentangled Concept-Residual Models: Bridging the Interpretability–Performance Gap for Incomplete Concept Sets Renos Zabounidis, Ini Oguntola, Konghao Zhao, Joseph Campbell, Woojun Kim, Simon Stepputtis, Katia P. Sycara

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Distilled Circuits: A Mechanistic Study of Internal Restructuring in Knowledge Distillation Reilly Haskins, Benjamin Adams

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Distilled Thompson Sampling: Practical and Efficient Thompson Sampling via Imitation Learning Hongseok Namkoong, Samuel Daulton, Eytan Bakshy

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Diversity Boosts AI-Generated Text Detection Advik Raj Basani, Pin-Yu Chen

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Diversity Sampling Regularization for Multi-Domain Generalization Lakpa Tamang, Mohamed Reda Bouadjenek, Sunil Aryal, Richard Dazeley

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Do Vision Encoders Truly Explain Object Hallucination?: Mitigating Object Hallucination via Simple Fine-Grained CLIPScore Hongseok Oh, Wonseok Hwang

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Domain Indexing Collaborative Filtering for Recommender Systems Rohit Amarnath, Zihao Xu, Qi Xu, Zhigang Hua, Yan Xie, Shuang Yang, Bo Long, Hao Wang

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Domain Translation with Monolingual Lexical Distribution Yusuke Sakai, Zhi Qu, Hidetaka Kamigaito, Taro Watanabe, Xiaojiang Liu

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DOME: Distributed Online Learning Based Multi-Estimate Fusion for Cooperative Predictive Target Tracking Using a Robotic Swarm Shubhankar Gupta, Saksham Sharma, Suresh Sundaram

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Don't Let It Hallucinate: Premise Verification via Retrieval-Augmented Logical Reasoning Yuehan Qin, Li Li, Yi Nian, Xinyan Velocity Yu, Yue Zhao, Xuezhe Ma

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DRAW: Domain Weight Randomization with Bayesian Updating for LLM Pre-Training Ruonan Wang, Yongqi Qiao, Zhonglin Xie, Kun Yuan

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Drawback of Enforcing Equivariance and Its Compensation via the Lens of Expressive Power Yuzhu Chen, Tian Qin, Xinmei Tian, Fengxiang He, Dacheng Tao

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DREAMS: Preserving Both Local and Global Structure in Dimensionality Reduction Noël Kury, Dmitry Kobak, Sebastian Damrich

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Dual-Phase Continual Learning: Supervised Adaptation Meets Unsupervised Retention Vaibhav Singh, Rahaf Aljundi, Eugene Belilovsky

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DuFal: Dual-Frequency-Aware Learning for High-Fidelity Extremely Sparse-View CBCT Reconstruction Cuong Tran Van, Trong-Thang Pham, Ngoc-Son Nguyen, Duy Minh Ho Nguyen, Ngan Le

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Dynamics‑Aligned Diffusion Planning for Offline RL: A Unified Framework with Forward and Inverse Guidance Zihao Wang, Ke Jiang, Xiaoyang Tan

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E$^2$M: Double Bounded $\alpha$-Divergence Optimization for Tensor-Based Discrete Density Estimation Kazu Ghalamkari, Jesper Løve Hinrich, Morten Mørup

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EarthquakeNPP: A Benchmark for Earthquake Forecasting with Neural Point Processes Samuel Stockman, Daniel John Lawson, Maximilian J. Werner

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ECLipsE-Gen-Local: Efficient Compositional Local Lipschitz Estimates for Deep Neural Networks Yuezhu Xu, S Sivaranjani

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EdgeMask-DG*: Learning Domain-Invariant Graph Structures via Adversarial Edge Masking Rishabh Bhattacharya, Naresh Manwani

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Efficient Audiovisual Speech Processing via MUTUD: Multimodal Training and Unimodal Deployment Joanna Hong, Sanjeel Parekh, Honglie Chen, Jacob Donley, Ke Tan, Buye Xu, Anurag Kumar

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Efficient Dilated Squeeze and Excitation Neural Operator for Differential Equations Prajwal Chauhan, Salah Eddine Choutri, Saif Jabari

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EgoPlan: Towards Effective Embodied Agents via Egocentric Planning Zhirui Fang, Ming Yang, Weishuai Zeng, Junpeng Yue, Boyu Li, Jiafei Lyu, Xiu Li, Zongqing Lu

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Empowering Power Outage Prediction with Spatially Aware Hybrid Graph Neural Networks and Contrastive Learning Xuyang Shen, Zijie Pan, Diego Cerrai, Xinxuan Zhang, Christopher Colorio, Emmanouil Anagnostou, Dongjin Song

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End-to-End Deep Reinforcement Learning for Stochastic Multi-Objective Optimization in C-VRPTW Abdo Abouelrous, Laurens Bliek, Yaoxin Wu, Yingqian Zhang

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Enhancing Concept Localization in CLIP-Based Concept Bottleneck Models Rémi Kazmierczak, Steve Azzolin, Goran Frehse, Eloïse Berthier, Gianni Franchi

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Enhancing Deep Consistent Graph Metric with Affinity and Alignment for Incremental Social Event Detection Using Cross-Layer Attention Shraban Kumar Chatterjee, Shubham Gupta, Suman Kundu

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Enhancing Semantic Segmentation with Continual Self-Supervised Pre-Training Brown Ebouky, Ajad Chhatkuli, A. Cristiano I. Malossi, Christoph Studer, Roy Assaf, Andrea Bartezzaghi

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Enhancing Semi-Supervised Learning with Zero-Shot Pseudolabels Jichan Chung, Irene Y. Chen

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Estimating Expected Calibration Error for Positive-Unlabeled Learning Ryuichi Kiryo, Futoshi Futami, Masashi Sugiyama

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Evaluating the Adversarial Robustness of CNNs Layer by Layer Yaowen Wang, Daniel Cullina

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ExpertLens: Activation Steering Features Are Highly Interpretable Masha Fedzechkina, Eleonora Gualdoni, Sinead Williamson, Katherine Metcalf, Skyler Seto, Barry-John Theobald

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Explainable Error Detection in Integrated Circuits Image Segmentation via Graph Neural Networks Ma Xiaoyu, Jingyang Dai, Feng Ji, Deruo Cheng, Yiqiong Shi, Bah-Hwee Gwee

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Explainable Graph Learning for Particle Accelerator Operations Song Wang, Chris Tennant, Jundong Li

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Explaining Graph Neural Networks for Node Similarity on Graphs Daniel Daza, Cuong Xuan Chu, Trung-Kien Tran, Daria Stepanova, Michael Cochez, Paul Groth

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Explaining with Trees: Interpreting CNNs Using Hierarchies Caroline Mazini Rodrigues, Nicolas Boutry, Laurent Najman

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Exploration-Driven Optimization for Test-Time Large Language Model Reasoning ChangHao Li, Yuchen Zhuang, Chenxiao Gao, Haotian Sun, Rushi Qiang, Chao Zhang, Bo Dai

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Exploring Perceptual Limitations of Multimodal LLMs on Small Visual Objects Jiarui Zhang, Jinyi Hu, Mahyar Khayatkhoei, Filip Ilievski, Maosong Sun

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Extracting and Following Paths for Robust Relational Reasoning with Large Language Models Ge Zhang, Mohammad Ali Alomrani, Hongjian Gu, Jiaming Zhou, Yaochen Hu, Bin Wang, Qun Liu, Mark Coates, Yingxue Zhang, Jianye Hao

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Eyes on the Road, Words in the Changing Skies: Vision-Language Assistance for Autonomous Driving in Transitional Weather Madhavi Kondapally, K Naveen Kumar, C Krishna Mohan

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Facial Counterfactual Generation via Causal Mask-Guided Editing Pei Sze Tan, Sailaja Rajanala, Arghya Pal, Raphael CW Phan, Huey Fang Ong

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Fast Debiasing of the LASSO Estimator Shuvayan Banerjee, James Saunderson, Radhendushka Srivastava, Ajit Rajwade

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Fast Graph Generation via Autoregressive Noisy Filtration Modeling Markus Krimmel, Jenna Wiens, Karsten Borgwardt, Dexiong Chen

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Fast Weight Programming and Linear Transformers: From Machine Learning to Neurobiology Kazuki Irie, Samuel J. Gershman

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Feature Representation Transferring to Lightweight Models via Perception Coherence Hai-Vy Nguyen, Fabrice Gamboa, Sixin Zhang, Reda Chhaibi, Serge Gratton, Thierry Giaccone

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Fed-SB: A Silver Bullet for Extreme Communication Efficiency and Performance in (Private) Federated LoRA Fine-Tuning Raghav Singhal, Kaustubh Ponkshe, Rohit Vartak, Lav R. Varshney, Praneeth Vepakomma

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Federated Multimodal Fusion for Action Recognition Leveraging Vision-Language Embeddings and Spatio- Temporal CNNs Aditi Palit, Kalidas Yeturu

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FedLOE: Federated Domain Generalization via Locally Overfit Ensemble Ruqi Bai, David I. Inouye

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FedLog: Personalized Federated Classification with Less Communication and More Flexibility Haolin Yu, Guojun Zhang, Hongliang Li, Pascal Poupart

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Finally Outshining the Random Baseline: A Simple and Effective Solution for Active Learning in 3D Biomedical Imaging Carsten T. Lüth, Jeremias Traub, Kim-Celine Kahl, Till J. Bungert, Lukas Klein, Lars Krämer, Paul F Jaeger, Klaus Maier-Hein, Fabian Isensee

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FIT-GNN: Faster Inference Time for GNNs That ‘FIT’ in Memory Using Coarsening Shubhajit Roy, Hrriday Ruparel, Kishan Ved, Anirban Dasgupta

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FL-Sailer: Efficient and Privacy-Preserving Federated Learning for Scalable Single-Cell Epigenetic Data Analysis via Adaptive Sampling Guangyi Zhang, Yi Dai, Yiyun He, Junhao Liu

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Flow Matching for Tabular Data Synthesis Bahrul Ilmi Nasution, Floor Eijkelboom, Mark Elliot, Richard Allmendinger, Christian A. Naesseth

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Forget Less, Retain More: A Lightweight Regularizer for Rehearsal-Based Continual Learning Lama Alssum, Hasan Abed Al Kader Hammoud, Motasem Alfarra, Juan C Leon Alcazar, Bernard Ghanem

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Forgetting: A New Mechanism Towards Better Large Language Model Fine-Tuning Ali Taheri, Alireza Taban, Qizhou Wang, Shanshan Ye, Abdolreza Mirzaei, Tongliang Liu, Bo Han

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Formal Methods in Robot Policy Learning and Verification: A Survey on Current Techniques and Future Directions Anastasios Manganaris, Vittorio Giammarino, Ahmed H Qureshi, Suresh Jagannathan

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Foundation Models for Trajectory Planning in Autonomous Driving: A Review of Progress and Open Challenges Kemal Oksuz, Alexandru Buburuzan, Anthony Knittel, Yuhan Yao, Puneet K. Dokania

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Frictionless Hamiltonian Descent with Discretization and Parallel Optimization Heng Zhu, Jun-Kun Wang

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From Clutter to Clarity: Visual Recognition Through Foveated Object-Centric Learning (FocL) Amitangshu Mukherjee, Deepak Ravikumar, Kaushik Roy

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From Discrete-Time Policies to Continuous-Time Diffusion Samplers: Asymptotic Equivalences and Faster Training Julius Berner, Lorenz Richter, Marcin Sendera, Jarrid Rector-Brooks, Nikolay Malkin

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From Euclidean to Graph-Structured Data: A Survey of Collaborative Learning Rémi Bourgerie, Sarunas Girdzijauskas, Viktoria Fodor

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From Feature Visualization to Visual Circuits: Effect of Model Perturbation Geraldin Nanfack, Michael Eickenberg, Eugene Belilovsky

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From Link Prediction to Forecasting: Addressing Challenges in Batch-Based Temporal Graph Learning Moritz Lampert, Christopher Blöcker, Ingo Scholtes

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From Mice to Trains: Amortized Bayesian Inference on Graph Data Svenja Jedhoff, Elizaveta Semenova, Aura Raulo, Anne Meyer, Paul-Christian Bürkner

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From Models to Systems: A Comprehensive Survey of Efficient Multimodal Learning Pan Wang, Siwei Song, Hui Ji, Siqi Cao, Heng Yu, Zhijian Liu, Huanrui Yang, Yingyan Celine Lin, Beidi Chen, Mohit Bansal, Xiaoming Liu, Pengfei Zhou, Ming-Hsuan Yang, Tianlong Chen, Jingtong Hu

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From Preferences to Prejudice: The Role of Alignment Tuning in Shaping Social Bias in Video Diffusion Models Zefan Cai, Haoyi Qiu, Haozhe Zhao, Ke Wan, Jiachen Li, Jiuxiang Gu, Wen Xiao, Nanyun Peng, Junjie Hu

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From Weighting to Modeling: A Nonparametric Estimator for Off-Policy Evaluation Rong J.B. Zhu

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From Words to Rewards: Leveraging Natural Language for Reinforcement Learning Belen Martin Urcelay, Andreas Krause, Giorgia Ramponi

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Fuzzy PyTorch: Rapid Numerical Variability Evaluation for Deep Learning Models Inés Gonzalez Pepe, Hiba Akhaddar, Tristan Glatard, Yohan Chatelain

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Game-Theoretic Defenses for Adversarially Robust Conformal Prediction Rui Luo, Jie Bao, Suqun Cao, Chuangyin Dang, Zhixin Zhou

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Gaming and Cooperation in Federated Learning: What Can Happen and How to Monitor It Dongseok Kim, Hyoungsun Choi, Mohamed Jismy Aashik Rasool, Gisung Oh

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GenAI vs. Human Creators: Procurement Mechanism Design in Two-/Three-Layer Markets Rui Ai, David Simchi-Levi, Haifeng Xu

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Generalization Bound for a Shallow Transformer Trained Using Gradient Descent Brian Mwigo, Anirban Dasgupta

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Generalizing Coverage Plots for Simulation-Based Inference Maximilian Lipp, Benjamin Kurt Miller, Lyubov Amitonova, Patrick Forré

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Generative Causal Structure Learning with Dual Latent Spaces and Annealing Soma Bandyopadhyay, Sudeshna Sarkar

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Generative Evolutionary Meta-Solver (GEMS): Scalable Surrogate-Free Multi-Agent Reinforcement Learning Alakh Sharma, Gaurish Trivedi, Kartikey Singh Bhandari, Yash Sinha, Dhruv Kumar, Pratik Narang, Jagat Sesh Challa

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GENIE: A Visual-Only Diffusion Framework for Task- Agnostic Image Transformation Uddeshya Singh, Aniket Thomas, Aishwarya Agarwal, Srikrishna Karanam, Biplab Banerjee

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GENIE: Watermarking Graph Neural Networks for Link Prediction Venkata Sai Pranav Bachina, Aaryan Ajay Sharma, Charu Sharma, Ankit Gangwal

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Genomic Next-Token Predictors Are In-Context Learners Nathan Breslow, Aayush Mishra, Michael Schatz, Anqi Liu, Mahler Revsine, Daniel Khashabi

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GGFlow: A Graph Flow Matching Method with Efficient Optimal Transport Xiaoyang Hou, Tian Zhu, Milong Ren, Dongbo Bu, Xin Gao, Chunming Zhang, Shiwei Sun

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GIFT: A Framework Towards Global Interpretable Faithful Textual Explanations of Vision Classifiers Eloi Zablocki, Valentin Gerard, Amaia Cardiel, Eric Gaussier, Matthieu Cord, Eduardo Valle

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Glocal Smoothness: Line Search and Adaptive Sizes Can Help in Theory Too! Curtis Fox, Aaron Mishkin, Sharan Vaswani, Mark Schmidt

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Goal Achievement Guided Exploitation: A Principled Performance-Based Scheduling Framework for Reinforcement Learning Shengchao Yan, Baohe Zhang, Chenguang Huang, Joschka Boedecker, Wolfram Burgard

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Graph Coarsening Using Game Theoretic Approach Sonali Raj, Manoj Kumar, Sumit Kumar, Ruchir Gupta, Amit Kumar Jaiswal

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Graph Concept Bottleneck Models Haotian Xu, Tsui-Wei Weng, Lam M. Nguyen, Tengfei Ma

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Graph Generation via Temporal-Aware Biased Walks Resul Tugay, Eren Olug, Elif Ak, Kiymet Kaya, Şule Gündüz Öğüdücü

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GraphGini: Fostering Individual and Group Fairness in Graph Neural Networks Anuj Kumar Sirohi, Anjali Gupta, Sandeep Kumar, Amitabha Bagchi, Sayan Ranu

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GraphMERT: Efficient and Scalable Distillation of Reliable Knowledge Graphs from Unstructured Data Margarita Belova, Jiaxin Xiao, Shikhar Tuli, Niraj Jha

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GriDiT: Factorized Grid-Based Diffusion for Efficient Long Image Sequence Generation Snehal Singh Tomar, Alexandros Graikos, Arjun Krishna, Dimitris Samaras, Klaus Mueller

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Grothendieck Graph Neural Networks Framework: An Algebraic Platform for Crafting Topology-Aware GNNs Amirreza Shiralinasab Langari, Leila Yeganeh, Kim Khoa Nguyen

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Grounding Generative Evaluations of Language Models in Unsupervised Document Corpora Michael Majurski, Cynthia Matuszek

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GroundingBooth: Grounding Text-to-Image Customization Zhexiao Xiong, Wei Xiong, Jing Shi, He Zhang, Yizhi Song, Nathan Jacobs

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Guess-and-Learn (G&L): Measuring the Cumulative Error Cost of Cold-Start Adaptation Roland Arnold

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Harnessing Heterogeneity: Improving Convergence Through Partial Variance Control in Federated Learning Pranab Sahoo, Ashutosh Tripathi, Sriparna Saha, Samrat Mondal

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Hessian-Aware Training for Enhancing DNN Resilience to Bitwise Corruptions in Their Parameters Tahmid Hasan Pranto, Seijoon Kim, Lizhong Chen, Sanghyun Hong

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HiBaNG: Hierarchical Bayesian Nonparametric Granger Causal Discovery in Low-Data Regimes He Zhao, Vassili Kitsios, Terence O'kane, Edwin V. Bonilla

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Hierarchical Filtering and Refinement Classification for Few-Shot Class-Incremental Learning Li-Jun Zhao, Zhen-Duo Chen, Xin Luo, Xin-Shun Xu

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Hierarchical Mamba Meets Hyperbolic Geometry: A New Paradigm for Structured Language Embeddings Sarang Rajendra Patil, Ashish Parmanand Pandey, Ioannis Koutis, Mengjia Xu

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Hierarchical Time Series Forecasting with Robust Reconciliation Shuhei Aikawa, Aru Suzuki, Kei Yoshitake, Kanata Teshigawara, Iwabuchi Akira, Ken Kobayashi, Kazuhide Nakata

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High-Layer Attention Pruning with Rescaling Songtao Liu, Peng Liu

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Holistic Continual Learning Under Concept Drift with Adaptive Memory Realignment Alif Ashrafee, Jędrzej Kozal, Michał Woźniak, Bartosz Krawczyk

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How Well Can Preference Optimization Generalize Under Noisy Feedback? Shawn Im, Yixuan Li

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HypCBC: Domain-Invariant Hyperbolic Cross-Branch Consistency for Generalizable Medical Image Analysis Francesco Di Salvo, Sebastian Doerrich, Jonas Alle, Christian Ledig

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HyperAdapt: Simple High-Rank Adaptation Abel Gurung, Joseph Campbell

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Hypergraph Clustering Using Ricci Curvature: An Edge Transport Perspective Olympio Hacquard

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Hypothesis-Driven Feature Manifold Analysis in LLMs via Supervised Multi-Dimensional Scaling Federico Tiblias, Irina Bigoulaeva, Jingcheng Niu, Simone Balloccu, Iryna Gurevych

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Identifiable Latent Bandits: Leveraging Observational Data for Personalized Decision-Making Ahmet Zahid Balcıoğlu, Newton Mwai, Emil Carlsson, Fredrik D. Johansson

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iiANET: Inception Inspired Attention Hybrid Network for Efficient Long-Range Dependency Yunusa Haruna, Adamu Lawan, Abdulganiyu Abdu Yusuf

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Implicit Probabilistic Reasoning Does Not Reflect Explicit Answers in Large Language Models Manuel Mondal, Ljiljana Dolamic, Gérôme Bovet, Philippe Cudre-Mauroux, Julien Audiffren

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Improved Sample Complexity Bounds for Diffusion Model Training Without Empirical Risk Minimizer Access Mudit Gaur, Prashant Trivedi, Sasidhar Kunapuli, Amrit Singh Bedi, Vaneet Aggarwal

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Improving Detection of Rare Nodes in Hierarchical Multi-Label Learning Isaac Xu, Martin Gillis, Ayushi Sharma, Benjamin Misiuk, Craig J. Brown, Thomas Trappenberg

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Improving Detection of Watermarked Language Models Dara Bahri, John Frederick Wieting

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Improving Foundation Model Group Robustness with Auxiliary Sentence Embeddings Sisuo Lyu, Hong Liu, Jie Li, Yan Teng, Yingchun Wang

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Improving LLM Unlearning Robustness via Random Perturbations Dang Huu-Tien, Hoang Thanh-Tung, Anh Tuan Bui, Phuong Minh Nguyen, Le-Minh Nguyen, Naoya Inoue

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Improving Local Explainability by Learning Causal Graphs from Data Daan Roos, Sebastian Gerwinn, Jan-Willem van de Meent, Sara Magliacane

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Improving OOD Robustness via Background-Aware Test- Time-AugmentationinBlack-BoxandResourceConstrained Settings Ping Song, Adegboyega Ojo, Edward Curry

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Improving Visual Discriminability of CLIP for Training-Free Open-Vocabulary Semantic Segmentation Jinxin Zhou, Jiachen Jiang, Zhihui Zhu

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In-Context Learning in Presence of Spurious Correlations Hrayr Harutyunyan, Rafayel Darbinyan, Samvel Karapetyan, Hrant Khachatrian

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Incentive-Aware Synthetic Control: Accurate Counterfactual Estimation via Incentivized Exploration Dung Daniel Ngo, Keegan Harris, Anish Agarwal, Vasilis Syrgkanis, Steven Wu

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Incomplete Tasks Induce Shutdown Resistance in Some Frontier LLMs Jeremy Schlatter, Benjamin Weinstein-Raun, Jeffrey Ladish

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Incorporating New Knowledge into Federated Learning: Advances, Insights, and Future Directions Lixu Wang, Sun Yinggang, Yang Zhao, Jiaqi Wu, Jiahua Dong, Ating Yin, Qinbin Li, Qingqing Ye, Dusit Niyato, Tianwei Zhang, Kwok-Yan Lam, Yu Haining, Haibo Hu, Wei Dong

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Incremental3D: Real-Time Incremental 3D Scene Generation with Scene Graphs Penggang Gao, Yonas Teodros Tefera, Darwin G. Caldwell, Nikhil Deshpande

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InfGraND: An Influence-Guided GNN-to-MLP Knowledge Distillation Amir Eskandari, Aman Anand, Elyas Rashno, Farhana Zulkernine

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Influence Estimation in Statistical Models Using the Fisher Information Matrix Omri Lev, Ashia C. Wilson

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InfoScale: Unleashing Training-Free Variable-Scaled Image Generation via Effective Utilization of Information Guohui Zhang, Jiangtong Tan, Linjiang Huang, Zhonghang Yuan, Mingde Yao, Jie Huang, Feng Zhao

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Interference-Aware K-Step Reachable Communication in Multi-Agent Reinforcement Learning Ziyu Cheng, Jinsheng Ren, Jun Yang, Zhouxian Jiang, Chenzhihang Li, Rongye Shi, Bin Liang

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Interpreting Kolmogorov-Arnold Networks in Neuroimaging: A Path-Based Attribution Framework Suhrud Murthy, Venkatesh Babu Radhakrishnan, Neelam Sinha

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Intra-Cluster Mixup: An Effective Data Augmentation Technique for Complementary-Label Learning Tan-Ha Mai, Hsuan-Tien Lin

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Introducing Background Temperature to Characterise Hidden Randomness in Large Language Models Alberto Messina, Stefano Scotta

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Inverse Classification with Logistic and SoftMax Classifiers: Efficient Optimization Miguel Á. Carreira-Perpiñán, Suryabhan Singh Hada

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Investigating a Model-Agnostic and Imputation-Free Approach for Irregularly-Sampled Multivariate Time-Series Modeling Abhilash Neog, Arka Daw, Sepideh Fatemi, Medha Sawhney, Aanish Pradhan, Mary E. Lofton, Bennett J. McAfee, Adrienne Breef-Pilz, Heather L. Wander, Dexter W Howard, Cayelan C. Carey, Paul Hanson, Anuj Karpatne

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Investigating Linguistic Steering: An Analysis of Adjectival Effects Across Large Language Model Architectures Lars Malmqvist

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Involuntary Jailbreak: On Self-Prompting Attacks Yangyang Guo, Yangyan Li, Mohan Kankanhalli

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Is There a Better Source Distribution than Gaussian? Exploring Source Distributions for Image Flow Matching Junho Lee, Kwanseok Kim, Joonseok Lee

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Iterative Compositional Data Generation for Robot Control Anh-Quan Pham, Marcel Hussing, Shubhankar P. Patankar, Danielle Bassett, Jorge Mendez-Mendez, Eric Eaton

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Joint Embedding Variational Bayes Amin Oji, Paul W. Fieguth

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Jr. AI Scientist and Its Risk Report: Autonomous Scientific Exploration from a Baseline Paper Atsuyuki Miyai, Mashiro Toyooka, Takashi Otonari, Zaiying Zhao, Kiyoharu Aizawa

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KASPER: Kolmogorov Arnold Networks for Stock Prediction and Explainable Regimes Vidhi Oad, Param Pathak, Nouhaila Innan, Shalini Devendrababu, Muhammad Shafique

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Kernel Matrix Estimation of a Determinantal Point Process from a Finite Set of Samples: Properties and Algorithms Marc Castella, Jean-Christophe Pesquet

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Kernel Neural Operators (KNOs) for Scalable, Memory-Efficient, Geometrically-Flexible Operator Learning Matthew Lowery, John Turnage, Zachary Morrow, John Davis Jakeman, Akil Narayan, Shandian Zhe, Varun Shankar

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KITTEN: A Knowledge-Integrated Evaluation of Image Generation on Visual Entities Hsin-Ping Huang, Xinyi Wang, Yonatan Bitton, Hagai Taitelbaum, Gaurav Singh Tomar, Ming-Wei Chang, Xuhui Jia, Kelvin C.K. Chan, Hexiang Hu, Yu-Chuan Su, Ming-Hsuan Yang

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Language Models Are Symbolic Learners in Arithmetic Chunyuan Deng, Zhiqi Li, Roy Xie, Ruidi Chang, Hanjie Chen

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Language-Aware Information Maximization for Transductive Few-Shot CLIP Ghassen Baklouti, Maxime Zanella, Ismail Ben Ayed

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Language-Pretraining-Induced Bias: A Strong Foundation for General Vision Tasks Yaxin Luo, Zhiqiang Shen

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Large Language Model Reasoning Failures Peiyang Song, Pengrui Han, Noah Goodman

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Large Language Model-Based Data Science Agent: A Survey Ke Chen, Peiran Wang, Yaoning Yu, Xianyang Zhan, Haohan Wang

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Large Language Models for Scientific Idea Generation: A Creativity-Centered Survey Fatemeh Shahhosseini, Arash Marioriyad, Ali Momen, Mahdieh Soleymani Baghshah, Mohammad Hossein Rohban, Shaghayegh Haghjooy Javanmard

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Last-Iterate Convergence of General Parameterized Policies in Constrained MDPs Washim Uddin Mondal, Vaneet Aggarwal

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Layer Collapse Can Be Induced by Unstructured Pruning Zhu Liao, Victor Quétu, Van-Tam Nguyen, Enzo Tartaglione

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Learning Adaptive Multi-Stage Energy-Based Prior for Hierarchical Generative Model Jiali Cui, Tian Han

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Learning and Transferring Physical Models Through Derivatives Alessandro Trenta, Andrea Cossu, Davide Bacciu

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Learning Encoding-Decoding Direction Pairs to Unveil Concepts of Influence in Deep Vision Networks Alexandros Doumanoglou, Kurt Driessens, Dimitrios Zarpalas

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Learning Energy-Based Models by Self-Normalising the Likelihood Hugo Henri Joseph Senetaire, Paul Jeha, Jes Frellsen, Pierre-Alexandre Mattei

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Learning from Online Videos at Inference Time for Computer-Use Agents Yujian Liu, Ze Wang, Hao Chen, Ximeng Sun, Xiaodong Yu, Jialian Wu, Jiang Liu, Emad Barsoum, Zicheng Liu, Shiyu Chang

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Learning Lagrangian Interaction Dynamics with Sampling-Based Model Order Reduction Hrishikesh Viswanath, Yue Chang, Aleksey Panas, Julius Berner, Peter Yichen Chen, Aniket Bera

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Learning Long-Range Representations with Equivariant Messages Egor Rumiantsev, Marcel F. Langer, Tulga-Erdene Sodjargal, Michele Ceriotti, Philip Loche

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Learning Multimodal Energy-Based Model with Multimodal Variational Auto-Encoder via MCMC Revision Jiali Cui, Zhiqiang Lao, Heather Yu

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Learning Object Representations Through Amortized Inference over Probabilistic Programs Francisco Silva, Hélder P. Oliveira, Tania Pereira

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Learning Representations for Independence Testing Nathaniel Xu, Feng Liu, Danica J. Sutherland

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Learning Robust Penetration Testing Policies Under Partial Observability: A Systematic Evaluation Raphael Simon, Pieter Jules Karel Libin, Wim Mees

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Learning to Defer with an Uncertain Rejector via Conformal Prediction Yizirui Fang, Eric Nalisnick

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Learning to Imitate with Less: Efficient Individual Behavior Modeling in Chess Zhenwei Tang, Difan Jiao, Eric Xue, Reid McIlroy-Young, Jon Kleinberg, Siddhartha Sen, Ashton Anderson

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Learning to Localize Leakage of Cryptographic Sensitive Variables Jimmy Gammell, Anand Raghunathan, Abolfazl Hashemi, Kaushik Roy

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Learning to Reconstruct from Saturated Data: Audio Declipping and High-Dynamic Range Imaging Victor Sechaud, Laurent Jacques, Patrice Abry, Julián Tachella

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Learning Where It Matters: Responsible and Interpretable Text-to-Image Generation with Background Consistency Sayedmoslem Shokrolahi, Jae-Mo Kang, Il-Min Kim

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Learning-Augmented Robust Algorithmic Recourse Kshitij Kayastha, Vasilis Gkatzelis, Shahin Jabbari

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Let's Roll a BiFTA: Bi-Refinement for Fine-Grained Text-Visual Alignment in Vision-Language Models Yuhao Sun, Chengyi Cai, Jiacheng Zhang, Zesheng Ye, Xingliang Yuan, Feng Liu

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Leveraging Multimodal LLM Descriptions of Activity for Explainable Semi-Supervised Video Anomaly Detection Furkan Mumcu, Michael J. Jones, Anoop Cherian, Yasin Yilmaz

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Leveraging Recursive Methods for Efficient Federated Learning Jie Liu, Zuang Wang, Yongqiang Wang

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Leveraging the True Depth of LLMs Ramón Calvo González, Daniele Paliotta, Matteo Pagliardini, Martin Jaggi, François Fleuret

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Lifelong Open-Ended Probability Predictors Omid Madani

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LinMU: Multimodal Understanding Made Linear Hongjie Wang, Niraj Jha

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LJ-Bench: Ontology-Based Benchmark for U.S. Crime Hung Yun Tseng, Wuzhen Li, Blerina Gkotse, Grigorios Chrysos

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LLM-Based World Models Can Make Decisions Solely, but Rigorous Evaluations Are Needed Chang Yang, Xinrun Wang, Junzhe Jiang, Qinggang Zhang, Xiao Huang

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LLM-FE: Automated Feature Engineering for Tabular Data with LLMs as Evolutionary Optimizers Nikhil Abhyankar, Parshin Shojaee, Chandan K. Reddy

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LLM-RankFusion: Mitigating Intrinsic Inconsistency in LLM-Based Ranking Yifan Zeng, Ojas Tendolkar, Raymond Baartmans, Qingyun Wu, Lizhong Chen, Huazheng Wang

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LoDAdaC: A Unified Local Training-Based Decentralized Framework with Adaptive Gradients and Compressed Communication Wei Liu, Anweshit Panda, Ujwal Pandey, Haven Cook, George Slota, Naigang Wang, Jie Chen, Yangyang Xu

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Logical Anomaly Detection with Masked Image Modeling Shunsuke Sakai, Tatsuhito Hasegawa, Makoto Koshino

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LoRA-Ensemble: Efficient Uncertainty Modelling for Self-Attention Networks Dominik J. Mühlematter, Michelle Halbheer, Alexander Becker, Dominik Narnhofer, Helge Aasen, Konrad Schindler, Mehmet Ozgur Turkoglu

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Lorenza: Enhancing Generalization in Low-Rank Gradient LLM Training via Efficient Zeroth-Order Adaptive SAM Yehonathan Refael, Iftach Arbel, Ofir Lindenbaum, Tom Tirer

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LVLM-Count: Enhancing the Counting Ability of Large Vision-Language Models Muhammad Fetrat Qharabagh, Mohammadreza Ghofrani, Kimon Fountoulakis

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LZ Penalty: An Information-Theoretic Repetition Penalty for Autoregressive Language Models. Tony A Ginart, Naveen Kodali, Jason Lee, Caiming Xiong, Silvio Savarese, John Emmons

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MACAW: A Causal Generative Model for Medical Imaging Vibujithan Vigneshwaran, Erik Yuiti Ohara, Matthias Wilms, Nils Forkert

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Make Your LVLM KV Cache More Lightweight Xihao Chen, Yangyang Guo, Roger Zimmermann

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Making Video Models Adhere to User Intent with Minor Adjustments Daniel Ajisafe, Eric Hedlin, Helge Rhodin, Kwang Moo Yi

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Maximal Brain Damage Without Data or Optimization: Disrupting Neural Networks via Sign-Bit Flips Ido Galil, Moshe Kimhi, Ran El-Yaniv

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Measuring Fine-Grained Relatedness in Multitask Learning via Data Attribution Yiwen Tu, Ziqi Liu, Jiaqi W. Ma, Weijing Tang

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Mechanism-Aware Prediction of Tissue-Specific Drug Activity via Multi-Modal Biological Graphs Sally Turutov, Kira Radinsky

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MEMO: Memory-Guided Diffusion for Expressive Talking Video Generation Longtao Zheng, Yifan Zhang, Hanzhong Guo, Jiachun Pan, Zhenxiong Tan, Jiahao Lu, Chuanxin Tang, Bo An, Shuicheng Yan

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Merging Memory and Space: A State Space Neural Operator Nodens Koren, Samuel Lanthaler

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Message-Passing GNNs Fail to Approximate Sparse Triangular Factorizations Vladislav Trifonov, Ekaterina Muravleva, Ivan Oseledets

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MetaSeal: Defending Against Image Attribution Forgery Through Content-Dependent Cryptographic Watermarks Tong Zhou, Ruyi Ding, Gaowen Liu, Charles Fleming, Ramana Rao Kompella, Yunsi Fei, Xiaolin Xu, Shaolei Ren

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MetaSym: A Symplectic Meta-Learning Framework for Physical Intelligence Pranav Vaidhyanathan, Aristotelis Papatheodorou, Mark T. Mitchison, Natalia Ares, Ioannis Havoutis

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MiniGPT-Med: A Unified Vision-Language Model for Radiology Image Understanding Asma Alkhaldi, Raneem Alnajim, Layan Alabdullatef, Rawan Alyahya, Jun Chen, Deyao Zhu, Ahmed Z. Alsinan, Mohamed Elhoseiny

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MIRA: Multi-View Information Retrieval with Adaptive Routing for Test-Time Long-Video Comprehension Zecheng Hao, Wayne Ma, Yufeng Cui, Shuang Li, Xinlong Wang, Tiejun Huang

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MissNODAG: Differentiable Learning of Cyclic Causal Graphs from Incomplete Data Muralikrishnna Guruswamy Sethuraman, Razieh Nabi, Faramarz Fekri

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Mitigating Steady-State Bias in Off-Policy TD Learning via Distributional Correction Emani Naga Sai Venkata Sowmya, Amit Kesari, Ajin George Joseph

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Mitigating Unintended Memorization with LoRA in Federated Learning for LLMs Thierry Bossy, Julien Tuấn Tú Vignoud, Tahseen Rabbani, Juan R. Troncoso Pastoriza, Martin Jaggi

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MixTraining: A Better Trade-Off Between Compute and Performance Zexin Li, Jiancheng Zhang, Yufei Li, Yinglun Zhu, Cong Liu

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Mixtures of Locally Bounded Langevin Dynamics for Bayesian Model Averaging Kilian Zepf, Tareen Dawood, Aasa Feragen, Ender Konukoglu

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MixtureVitae: Open Web-Scale Pretraining Dataset with High Quality Instruction and Reasoning Data Built from Permissive-First Text Sources Huu Nguyen, Victor May, Harsh Raj, Marianna Nezhurina, Yishan Wang, Yanqi Luo, Vu Minh Chien, Taishi Nakamura, Ken Tsui, Van Khue Nguyen, David Salinas, Aleksandra Krasnodębska, Christoph Schuhmann, Mats Leon Richter, Xuan-Son Vu, Jenia Jitsev

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Modality-Inconsistent Continual Learning of Multimodal Large Language Models Weiguo Pian, Shijian Deng, Shentong Mo, Mingrui Liu, Yunhui Guo, Yapeng Tian

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Model Debiasing by Learnable Data Augmentation Pietro Morerio, Ruggero Ragonesi, Vittorio Murino

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Model-Free Learning with Heterogeneous Dynamical Systems: A Federated LQR Approach Han Wang, Leonardo Felipe Toso, Aritra Mitra, James Anderson

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Models with a Cause: Causal Discovery with Language Models on Temporally Ordered Text Data Bruce Rushing, Javier Gomez-Lavin

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Mollifier Layers: Enabling Efficient High-Order Derivatives in Inverse PDE Learning Vinayak Vinayak, Ananyae Kumar Bhartari, Vivek Shenoy

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Moment Constrained Optimal Transport for Control Applications Thomas Le Corre, Ana Busic, Sean P. Meyn

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MS-IMAP - A Multi-Scale Graph Embedding Approach for Interpretable Manifold Learning Shay Deutsch, Lionel Yelibi, Alex Tong Lin, Arjun Ravi Kannan

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mSOP-765k: A Benchmark for Multi-Modal Structured Output Predictions Bianca Lamm, Janis Keuper

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mTSBench: Benchmarking Multivariate Time Series Anomaly Detection and Model Selection at Scale Xiaona Zhou, Constantin Brif, Ismini Lourentzou

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Multi-Step Alignment as Markov Games: An Optimistic Online Mirror Descent Approach with Convergence Guarantees Yongtao Wu, Luca Viano, Kimon Antonakopoulos, Yihang Chen, Zhenyu Zhu, Quanquan Gu, Volkan Cevher

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Multimodal Deception in Explainable AI: Concept-Level Backdoor Attacks on Concept Bottleneck Models Songning Lai, Jiayu Yang, Yu Huang, Lijie Hu, TianlangXue, Zhangyi Hu, Jiaxu Li, Haicheng Liao, Zongyang Liu, Yutao Yue

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Multimodal Prescriptive Deep Learning Dimitris Bertsimas, Lisa Everest, Vasiliki Stoumpou

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Multiscale Training of Convolutional Neural Networks Shadab Ahamed, Niloufar Zakariaei, Eldad Haber, Moshe Eliasof

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Multivariate Conformal Prediction Using Optimal Transport Michal Klein, Louis Béthune, Eugene Ndiaye, Marco Cuturi

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Multiway Multislice PHATE: Visualizing Hidden Dynamics of RNNs Through Training Jiancheng Xie, Lou C Voinov, Noga Mudrik, Gal Mishne, Adam Shabti Charles

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Muon Optimizes Under Spectral Norm Constraints Lizhang Chen, Jonathan Li, Qiang Liu

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MV2MAE: Self-Supervised Video Pre-Training with Motion-Aware Multi-View Masked Autoencoders Ketul Shah, Robert Crandall, Jie Xu, Peng Zhou, Vipin Pillai, Marian George, Mayank Bansal, Rama Chellappa

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Natural Policy Gradient for Average Reward Non-Stationary Reinforcement Learning Neharika Jali, Eshika Pathak, Pranay Sharma, Guannan Qu, Gauri Joshi

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Nested Slice Sampling: Vectorized Nested Sampling for GPU-Accelerated Inference David Yallup, Namu Kroupa, Will Handley

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Neural Conditional Transport Maps Carlos Rodriguez-Pardo, Leonardo Chiani, Emanuele Borgonovo, Massimo Tavoni

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Neural Fourier Transform for Multiple Time Series Prediction Noam Koren, Kira Radinsky, Daniel Freedman

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Neurons Speak in Ranges: Breaking Free from Discrete Neuronal Attribution Muhammad Umair Haider, Hammad Rizwan, Hassan Sajjad, Peizhong Ju, A.B. Siddique

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Noise-Aware Adaptation of Pre-Trained Foundation Models for Single-Photon Image Classification Ziting Wen, Wenle Dong, Zili Zhang, Yiheng Qiang, Kemi Ding, Xiaoqiang Ren

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Nondeterministic Polynomial-Time Problem Challenge: An Ever-Scaling Reasoning Benchmark for LLMs Chang Yang, Ruiyu Wang, Junzhe Jiang, Qi Jiang, Qinggang Zhang, Yanchen Deng, Shuxin Li, Shuyue Hu, Bo Li, Florian T. Pokorny, Xiao Huang, Xinrun Wang

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Nonlinear Reconciliation: Error Reduction Theorems Lorenzo Nespoli, Anubhab Biswas, Roberto Rocchetta, Vasco Medici

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Not All CAMs Are Complete: Completeness as the Key to Faithfulness Vincenzo Buono, Peyman Sheikholharam Mashhadi, Mahmoud Rahat, Prayag Tiwari, Stefan Byttner

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Not All Rollouts Are Useful: Down-Sampling Rollouts in LLM Reinforcement Learning Yixuan Even Xu, Yash Savani, Fei Fang, J Zico Kolter

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ODE-Constrained Generative Modeling of Cardiac Dynamics for 12-Lead ECG Synthesis Yakir Yehuda, Kira Radinsky

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Offline Changepoint Localization Using a Matrix of Conformal P-Values Sanjit Dandapanthula, Aaditya Ramdas

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Offline Model-Based Optimization: Comprehensive Review Minsu Kim, Jiayao Gu, Ye Yuan, Taeyoung Yun, Zixuan Liu, Yoshua Bengio, Can Chen

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Offline Reinforcement Learning via Inverse Optimization Ioannis Dimanidis, Tolga Ok, Peyman Mohajerin Esfahani

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On a Gradient Approach to Chebyshev Center Problems with Applications to Function Learning Abhinav Raghuvanshi, Mayank Baranwal, Debasish Chatterjee

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On Adversarial Attacks in Acoustic Localization Tamir Shor, Chaim Baskin, Alex M. Bronstein

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On Calibration of Multilingual Question Answering LLMs Yahan Yang, Soham Dan, Dan Roth, Insup Lee

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On Fitting Flow Models with Large Sinkhorn Couplings Stephen Y. Zhang, Alireza Mousavi-Hosseini, Michal Klein, Marco Cuturi

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On Gossip Algorithms for Machine Learning with Pairwise Objectives Igor Colin, Aurélien Bellet, Stephan Clémençon, Joseph Salmon

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On Sketching for Gaussian Process Regression with New Statistical Guarantees Jayesh Malaviya, Rachit Chhaya, Anirban Dasgupta, Supratim Shit

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On Symmetric Losses for Policy Optimization with Noisy Preferences Soichiro Nishimori, Yu-Jie Zhang, Thanawat Lodkaew, Masashi Sugiyama

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On the (linear) Convergence of Generalized Newton Inexact ADMM Zachary Frangella, Theo Diamandis, Bartolomeo Stellato, Madeleine Udell

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On the Conditioning Consistency Gap in Conditional Neural Processes Robin Young

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On the Dynamics & Transferability of Latent Generalization During Memorization Simran Ketha, Venkatakrishnan Ramaswamy

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On the Geometry of Regularization in Adversarial Training: High-Dimensional Asymptotics and Generalization Bounds Matteo Vilucchio, Nikolaos Tsilivis, Bruno Loureiro, Julia Kempe

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On the Impact of the Parametrization of Deep Convolutional Neural Networks on Post-Training Quantization Samy Houache, Jean-François Aujol, Yann Traonmilin

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On the Importance of Pretraining Data Alignment for Atomic Property Prediction Yasir M. Ghunaim, Hasan Abed Al Kader Hammoud, Bernard Ghanem

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On Uncertainty Calibration for Equivariant Functions Edward Berman, Jacob Ginesin, Marco Pacini, Robin Walters

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On-Policy Policy Gradient Reinforcement Learning Without On-Policy Sampling Nicholas E. Corrado, Josiah P. Hanna

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One Model for All: Multi-Objective Controllable Language Models Qiang He, Yucheng Yang, Tianyi Zhou, Meng Fang, Mykola Pechenizkiy, Setareh Maghsudi

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One Pic Is All It Takes: Poisoning Visual Document Retrieval Augmented Generation with a Single Image Ezzeldin Shereen, Dan Ristea, Shae McFadden, Burak Hasircioglu, Vasilios Mavroudis, Chris Hicks

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One-Bit Distributed Mean Estimation with Unknown Variance Ritesh Kumar, Shashank Vatedka

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One-Sided Matrix Completion from Ultra-Sparse Samples Hongyang R. Zhang, Zhenshuo Zhang, Huy Nguyen, Guanghui Lan

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Online Learning with Multiple Fairness Regularizers via Graph-Structured Feedback Quan Zhou, Jakub Marecek, Robert Noel Shorten

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Open Technical Problems in Open-Weight AI Model Risk Management Stephen Casper, Kyle O'Brien, Shayne Longpre, Elizabeth Seger, Kevin Klyman, Rishi Bommasani, Aniruddha Nrusimha, Ilia Shumailov, Sören Mindermann, Steven Basart, Frank Rudzicz, Kellin Pelrine, Avijit Ghosh, Andrew Strait, Robert Kirk, Dan Hendrycks, Peter Henderson, J Zico Kolter, Geoffrey Irving, Yarin Gal, Yoshua Bengio, Dylan Hadfield-Menell

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Optimal Pattern Detection Tree for Symbolic Rule-Based Classification Young-Chae Hong, Yangho Chen

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Optimal Regret and Hard Violation for Constrained Markov Decision Processes with Adversarial Losses and Constraints Srinjoy Roy, Swagatam Das

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Optimistic Online Learning in Symmetric Cone Games Anas Barakat, Wayne Lin, John Lazarsfeld, Antonios Varvitsiotis

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OracleTSC: Oracle-Informed Reward Hurdle and Uncertainty Regularization for Traffic Signal Control Darryl C. Jacob, Xinyu Liu, Muchao Ye, Xiaoyong Yuan, Pan He

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Order from Chaos: Physical World Understanding from Glitchy Gameplay Videos Meng Cao, Haoran Tang, Haoze Zhao, Mingfei Han, Ruyang Liu, Qiang Sun, Xiaojun Chang, Ian Reid, Xiaodan Liang

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OT Score: An OT Based Confidence Score for Prototype-Assisted Source Free Unsupervised Domain Adaptation Yiming Zhang, Sitong Liu, Alex Cloninger

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Overcoming Open-Set Approaches to Adversarial Defense Edgar Wilfred Jatho, Armon Barton, Matthew Wright, Patrick McClure

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Overcoming Output Dimension Collapse: When Sparsity Enables Zero-Shot Brain-to-Image Reconstruction at Small Data Scales Kenya Otsuka, Yoshihiro Nagano, Yukiyasu Kamitani

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ParaBlock: Communication-Computation Parallel Block Coordinate Federated Learning for Large Language Models Yujia Wang, Yuanpu Cao, Jinghui Chen

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Paradoxical Noise Preference in RNNs Noah Izaac Eckstein, Manoj Srinivasan

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Parameter Efficient Continual Learning with Dynamic Low- Rank Adaptation Prashant Shivaram Bhat, Shakib Yazdani, Elahe Arani, Bahram Zonooz

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Pave Your Own Path: Graph Gradual Domain Adaptation on Fused Gromov-Wasserstein Geodesics Zhichen Zeng, Ruizhong Qiu, Wenxuan Bao, Tianxin Wei, Xiao Lin, Yuchen Yan, Tarek F. Abdelzaher, Jiawei Han, Hanghang Tong

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PDEInvBench: A Comprehensive Dataset and Design Space Exploration of Neural Networks for PDE Inverse Problems Divyam Goel, Nithin Chalapathi, Sanjeev Raja, Aditi S. Krishnapriyan

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Physics-Informed Deep B-Spline Networks Zhuoyuan Wang, Raffaele Romagnoli, Saviz Mowlavi, Yorie Nakahira

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PipelineRL: Faster On-Policy Reinforcement Learning for Long Sequence Generation Alexandre Piché, Ehsan Kamalloo, Rafael Pardinas, Xiaoyin Chen, Dzmitry Bahdanau

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Policy Learning with a Language Bottleneck Megha Srivastava, Cédric Colas, Dorsa Sadigh, Jacob Andreas

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Post-Training Adaptive Conformal Prediction for Incomplete Time Series Baiting Chen, Xiaofan Zhou, Lu Cheng

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PredLDM: Spatiotemporal Sequence Prediction with Latent Diffusion Models Yechao Xu, Zhengxing Sun, Qian Li, Jiao Qu

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Preference-Based Gradient Estimation for ML-Guided Approximate Combinatorial Optimization Arman Mielke, Uwe Bauknecht, Thilo Strauss, Mathias Niepert

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Prescribe-Then-Select: Adaptive Policy Selection for Contextual Stochastic Optimization Caio de Próspero Iglesias, Kimberly Villalobos Carballo, Dimitris Bertsimas

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Primus: Enforcing Attention Usage for 3D Medical Image Segmentation Tassilo Wald, Saikat Roy, Fabian Isensee, Constantin Ulrich, Sebastian Ziegler, Dasha Trofimova, Raphael Stock, Michael Baumgartner, Gregor Koehler, Klaus Maier-Hein

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training Yangyi Chen, Hao Peng, Tong Zhang, Heng Ji

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PRISM: Diversifying Dataset Distillation by Decoupling Architectural Priors Brian Bernhard Moser, Shalini Sarode, Federico Raue, Stanislav Frolov, Krzysztof Adamkiewicz, Arundhati Shanbhag, Joachim Folz, Tobias Christian Nauen, Andreas Dengel

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PRISM: PRIor from Corpus Statistics for Topic Modeling Tal Ishon, Yoav Goldberg, Uri Shaham

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PriSM: Prior-Guided Search Methods for Query Efficient Black-Box Attacks Pavlos Ntais, Thanassis Avgerinos

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PrismBench: Dynamic and Flexible Benchmarking of LLMs Code Generation with Monte Carlo Tree Search Vahid Majdinasab, Amin Nikanjam, Foutse Khomh

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Privacy Profiles Under Tradeoff Composition Paul Glasserman

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Probabilistic Pretraining for Improved Neural Regression Boris N. Oreshkin, Shiv Kumar Tavker, Dmitry Efimov

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Probing Layer-Wise Memorization and Generalization in Deep Neural Networks via Model Stitching Aishwarya Gupta, Indranil Saha, Piyush Rai

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Proc-to-Spec: A Functorial mAP of Network Processes Shanfeng Hu

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Process Reward Models That Think Muhammad Khalifa, Rishabh Agarwal, Lajanugen Logeswaran, Jaekyeom Kim, Hao Peng, Moontae Lee, Honglak Lee, Lu Wang

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Prompt Estimation from Prototypes for Federated Prompt Tuning of Vision Transformers M Yashwanth, Sharannya Ghosh, Aditay Tripathi, Anirban Chakraborty

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Prompt-Based Adaptation in Large-Scale Vision Models: A Survey Xi Xiao, Yunbei Zhang, Lin Zhao, Yiyang Liu, Xiaoying Liao, Zheda Mai, Xingjian Li, Xiao Wang, Hao Xu, Jihun Hamm, Xue Lin, Min Xu, Qifan Wang, Tianyang Wang, Cheng Han

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Proper Orthogonal Decomposition for Scalable Training of Graph Neural Networks Abhishek A, Manohar Kaul, Mohit Meena, Mahesh Chandran

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Properties and Limitations of Geometric Tempering for Gradient Flow Dynamics Francesca Romana Crucinio, Sahani Pathiraja

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Provable Domain Adaptation for Offline Reinforcement Learning with Limited Samples Weiqin Chen, Xinjie Zhang, Sandipan Mishra, Santiago Paternain

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Provably Efficient Reward Transfer in Reinforcement Learning with Discrete Markov Decision Processes Kevin Jatin Vora, Yu Zhang

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Proxy-Anchor and EVT-Driven Continual Learning Method for Generalized Category Discovery Alireza Fathalizadeh, Roozbeh Razavi-Far

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PruneFuse: Efficient Data Selection via Weight Pruning and Network Fusion Humaira Kousar, Hasnain Irshad Bhatti, Jaekyun Moon

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Pull-to-Outlier & Contrastive Objective-Level (POCO) Unlearning: A Framework for Sample and Objective Forgetting Agil Aghasanli, Plamen P Angelov

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Quantifying Structure in CLIP Embeddings: A Statistical Framework for Concept Interpretation Jitian Zhao, Chenghui Li, Frederic Sala, Karl Rohe

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Quantile $q$-Learning: Revisiting Offline Extreme $q$-Learning with Quantile Regression Xinming Gao, Shangzhe Li, Yujin Cai, Wenwu Yu

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Quantitative Analysis of the Effect of Density Ratio Estimation in Covariate Shift Adaptation Chenglin Yu, Zhengyu Zhou, Weiwei Liu

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Quantum Rationale-Aware Graph Contrastive Learning for Jet Discrimination Md Abrar Jahin, Md Akmol Masud, Dr. M. F. Mridha, Nilanjan Dey, Zeyar Aung

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QuickVideo: Real-Time Long Video Understanding with System Algorithm Co-Design Benjamin Schneider, Dongfu Jiang, Chao Du, Tianyu Pang, Wenhu Chen

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Random Projection-Induced Gaussian Latent Features for Arbitrary Style Transfer Weizhi Lu, Zhongzheng Li, Dongchen Gao, Mingrui Chen, Weiyu Li, Jinglin Zhang, Wei Zhang

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Rank-1 Approximation of Inverse Fisher for Natural Policy Gradients in Deep Reinforcement Learning Yingxiao Huo, Satya Prakash Dash, Radu Stoican, Samuel Kaski, Mingfei Sun

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Re-Evaluating Minimum Bayes Risk Decoding for Automated Speech Recognition Tasks Yuu Jinnai

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Re:Form --- Reducing Human Priors in Scalable Formal Software Verification with RL in LLMs: A Preliminary Study on Dafny Chuanhao Yan, Fengdi Che, Xuhan Huang, Xu Xu, Xin Li, Yizhi Li, Xingwei Qu, Jingzhe Shi, Chenghua Lin, Yaodong Yang, Binhang Yuan, Hang Zhao, Yu Qiao, Bowen Zhou, Jie Fu

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Reasoning-Driven Synthetic Data Generation and Evaluation Tim R. Davidson, Benoit Seguin, Enrico Bacis, Cesar Ilharco, Hamza Harkous

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Reconciling In-Context and In-Weight Learning via Dual Representation Space Encoding Guanyu Chen, Ruichen Wang, Tianren Zhang, Feng Chen

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RegMean++: Enhancing Effectiveness and Generalization of Regression Mean for Model Merging The-Hai Nguyen, Dang Huu-Tien, Takeshi Suzuki, Le-Minh Nguyen

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Regret Minimization in Linear Bandits with Offline Data via Extended D-Optimal Exploration. Sushant Vijayan, Arun Suggala, Karthikeyan Shanmugam, Soumyabrata Pal

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Relative Geometry of Neural Forecasters: Linking Accuracy and Alignment in Learned Latent Geometry Deniz Kucukahmetler, Maximilian Jean Hemmann, Julian Mosig von Aehrenfeld, Maximilian Amthor, Christian Deubel, Nico Scherf, Diaaeldin Taha

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Reproducibility Study: Understanding Multi-Agent LLM Cooperation in the GovSim Framework Alessio Silverio, Carmen Michaela Chezan, Mathijs van Sprang, Tom Cappendijk, Martin Smit

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Repulsive Monte Carlo on the Sphere for the Sliced Wasserstein Distance Vladimir Petrovic, Rémi Bardenet, Agnes Desolneux

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Reranker Optimization via Geodesic Distances on k-NN Manifolds Wen G Gong

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Rethinking Coreset Selection: The Surprising Effectiveness of Soft Labels Saumyaranjan Mohanty, Deexitha Vattivella, Konda Reddy Mopuri

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Rethinking Disentanglement Under Dependent Factors of Variation Antonio Almudévar, Alfonso Ortega

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Rethinking Mixture-of-Agents: Is Mixing Different Large Language Models Beneficial? Wenzhe Li, Yong Lin, Mengzhou Xia, Chi Jin

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Rethinking the Mixture of Vision Encoders Paradigm for Enhanced Visual Understanding in Multimodal LLMs Mozhgan Nasr Azadani, James Riddell, Sean Sedwards, Krzysztof Czarnecki

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Retrieval as a Decision: Training-Free Adaptive Gating for Efficient RAG Yufeng Wang, Lu Wei, Haibin Ling

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Retrospective Feature Estimation for Continual Learning Nghia D. Nguyen, Hieu Trung Nguyen, Ang Li, Hoang Pham, Viet Anh Nguyen, Khoa D Doan

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Return Augmented Decision Transformer for Off-Dynamics Reinforcement Learning Ruhan Wang, Yu Yang, Zhishuai Liu, Dongruo Zhou, Pan Xu

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ReVision: Refining Video Diffusion with Explicit 3D Motion Modeling Qihao Liu, Ju He, Qihang Yu, Liang-Chieh Chen, Alan Yuille

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Revisit, Extend, and Enhance Hessian-Free Influence Functions Ziao Yang, Han Yue, Jian Chen, Hongfu Liu

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Revisiting "Edit Away and My Face Will Not Stay: Personal Biometric Defense Against Malicious Generative Editing" Luis Vitor Zerkowski, Soham Chaudhuri, Finley Helms, Jelle Sombekke, Udit Thakur

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Reward Engineering for Spatial Epidemic Simulations: A Reinforcement Learning Platform for Individual Behavioral Learning Radman Rakhshandehroo, Daniel Coombs

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Riemannian Generative Decoder Andreas Bjerregaard, Søren Hauberg, Anders Krogh

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RLHF in an SFT Way: From Optimal Solution to Reward-Weighted Alignment Yuhao Du, Zhuo Li, Pengyu Cheng, Zhihong Chen, Yuejiao Xie, Xiang Wan, Anningzhe Gao

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Robust Clustering Using Gaussian Mixtures in the Presence of Cellwise Outliers Pushpendra Rajpurohit, Petre Stoica, Prabhu Babu

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Robust Conformal Prediction for Infrequent Classes Jens-Michalis Papaioannou, Sebastian Jäger, Alexei Figueroa, David Stutz, Betty van Aken, Keno Bressem, Wolfgang Nejdl, Felix Gers, Alexander Löser, Felix Biessmann

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RPATH: Explaining Time Series Mixture of Experts Routing via Ensemble Consensus and Structural Robustness Temesgen Mikael Abraha, Yves Lucet

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RT2I-Bench: Evaluating Robustness of Text-to-Image Systems Against Adversarial Attacks Athanasios Glentis, Ioannis Tsaknakis, Jiangweizhi Peng, Xun Xian, Yihua Zhang, Gaowen Liu, Charles Fleming, Mingyi Hong

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S$^2$Transformer: Scalable Structured Transformers for Global Station Weather Forecasting Hongyi Chen, Xiucheng Li, Xinyang Chen, Yun Cheng, Jing Li, Kehai Chen, Liqiang Nie

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SA-PEF: Step-Ahead Partial Error Feedback for Efficient Federated Learning Dawit Kiros Redie, Reza Arablouei, Stefan Werner

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Safe Reinforcement Learning Using Action Projection: Safeguard the Policy or the Environment? Hannah Markgraf, Shambhuraj Sawant, Hanna Krasowski, Lukas Schäfer, Sebastien Gros, Matthias Althoff

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SAMAT: A Stereotype-Aware Multimodal Transformer for Interpretable Misogynistic Meme Detection gopendra Vikram Singh, Arpan Phukan, Kushal Kanwar, Asif Ekbal

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Sample-Wise Adaptive Weighting for Transfer Consistency in Adversarial Distillation Hongsin Lee, Hye Won Chung

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Scalable Equilibrium Propagation via Intermediate Error Signals for Deep Convolutional CRNNs Jiaqi Lin, Malyaban Bal, Abhronil Sengupta

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Scalable Physical Source-to-Field Inference with Hypernetworks Berian James, Stefan Pollok, Ignacio Peis, Elizabeth Louise Baker, Jes Frellsen, Rasmus Bjørk

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Scaling Gaussian Process Regression with Full Derivative Observations Daniel Huang

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Scaling Large Language Models with Fully Sparse Activations Hongyu Wang, Shuming Ma, Ruiping Wang, Furu Wei

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Seeing Is Simulating: Differentiable Physics for Interaction-Aware Material Estimation Chun Feng, Hao Zhang, Haolan Xu, Narendra Ahuja

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Segmentation from Attention: Training-Free Layer Selection and One-Shot Tuning for Segmentation in VLMs Mir Rayat Imtiaz Hossain, Mennatullah Siam, Leonid Sigal, James J. Little

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Self-Supervised Laplace Approximation for Bayesian Uncertainty Quantification Julian Rodemann, Alexander Marquard, Thomas Augustin, Michele Caprio

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SelfPrompt: Confidence-Aware Semi-Supervised Tuning for Improved Vision-Language Model Adaptation Shuvendu Roy, Ali Etemad

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Semantic-Aware Adversarial Fine-Tuning for CLIP Jiacheng Zhang, Jinhao Li, Hanxun Huang, Sarah Monazam Erfani, Benjamin I. P. Rubinstein, Feng Liu

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Semantic-Drive: Trustworthy and Efficient Long-Tail Data Curation via Open-Vocabulary Grounding and Neuro-Symbolic VLM Consensus Antonio Guillen-Perez

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Semi-Supervised Cross-Domain Imitation Learning Li-Min Chu, Kai-Siang Ma, Ming-Hong Chen, Ping-Chun Hsieh

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SemVAD: Fusing Semantic and Vision Features for Weakly Supervised Video Anomaly Detection Hamza Karim, Yasin Yilmaz

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SensX: Model-Agnostic Local Feature Attribution via Calibrated Global Sensitivity Analysis Manu Aggarwal, Nicholas Cogan, Vipul Periwal

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Sequential Causal Discovery with Noisy Language Model Priors Prakhar Verma, David Arbour, Sunav Choudhary, Harshita Chopra, Arno Solin, Atanu R. Sinha

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SiLVR: A Simple Language-Based Video Reasoning Framework Ce Zhang, Yan-Bo Lin, Ziyang Wang, Mohit Bansal, Gedas Bertasius

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Simplifying Optimal Transport Through Schatten-$p$ Regularization Tyler Maunu

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Single-Loop Algorithms for Stochastic Non-Convex Optimization with Weakly-Convex Constraints Ming Yang, Gang Li, Quanqi Hu, Qihang Lin, Tianbao Yang

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SMILE: A Composite Lexical-Semantic Metric for Question-Answering Evaluation Shrikant Kendre, Austin Xu, Honglu Zhou, Michael S Ryoo, Shafiq Joty, Juan Carlos Niebles

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SocialFusion: Addressing Social Degradation in Pre-Trained Vision-Language Models Hamza Tahboub, Weiyan Shi, Gang Hua, Huaizu Jiang

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Sociodynamics of Reinforcement Learning Yann Bouteiller, Karthik Soma, Giovanni Beltrame

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Socrates Loss: Unifying Confidence Calibration and Classification by Leveraging the Unknown Sandra Gómez-Gálvez, Tobias Olenyi, Gillian Dobbie, Katerina Taskova

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SoftMax Is $1/2$-Lipschitz: A Tight Bound Across All $\ell_p$ Norms Pravin Nair

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SokoBench: Evaluating Long-Horizon Planning and Reasoning in Large Language Models Sebastiano Monti, Carlo Nicolini, Giovanni Pellegrini, Jacopo Staiano, Bruno Lepri

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Solving Inverse Problems via Diffusion-Based Priors: An Approximation-Free Ensemble Sampling Approach Haoxuan Chen, Yinuo Ren, Martin Renqiang Min, Lexing Ying, Zachary Izzo

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Source-Optimal Training Is Transfer-Suboptimal C. Evans Hedges

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SPARC: Concept-Aligned Sparse Autoencoders for Cross-Model and Cross-Modal Interpretability Ali Nasiri-Sarvi, Hassan Rivaz, Mahdi S. Hosseini

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Sparse Mean Estimation in Adversarial Settings via Incremental Learning Jianhao Ma, Rui Ray Chen, Yinghui He, Salar Fattahi, Wei Hu

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SpecEval: Evaluating Model Adherence to Behavior Specifications Ahmed M Ahmed, Kevin Klyman, Yi Zeng, Sanmi Koyejo, Percy Liang

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SpikingBrain: Spiking Brain-Inspired Large Models Yuqi Pan, Yupeng Feng, JingHao Zhuang, Siyu Ding, Han Xu, Zehao Liu, Bohan Sun, Yuhong Chou, Xuerui Qiu, Anlin Deng, Anjie Hu, Shurong Wang, Peng Zhou, Man Yao, Jibin Wu, Jian Yang, 孙国梁, Bo Xu, Guoqi Li

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SpikingMamba: Towards Energy-Efficient Large Language Models via Knowledge Distillation from Mamba Yulong Huang, Jianxiong Tang, Chao Wang, Ziyi Wang, Jianguo Zhang, Zhichao Lu, Bojun Cheng, Luziwei Leng

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SPoT: Subpixel Placement of Tokens in Vision Transformers Martine Hjelkrem-Tan, Marius Aasan, Gabriel Y. Arteaga, Adín Ramírez Rivera

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SSFL: Discovering Sparse Unified Subnetworks at Initialization for Efficient Federated Learning Riyasat Ohib, Bishal Thapaliya, Gintare Karolina Dziugaite, Jingyu Liu, Vince D. Calhoun, Sergey Plis

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SSL-SLR: Self-Supervised Representation Learning for Sign Language Recognition Ariel Basso Madjoukeng, Jérôme Fink, Pierre Poitier, Edith Belise Kenmogne, Benoit Frenay

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State Design Matters: How Representations Shape Dynamic Reasoning in Large Language Models Annie Wong, Aske Plaat, Thomas Bäck, Niki van Stein, Anna V Kononova

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Statistical Inference for Generative Model Comparison Zijun Gao, Han Su, Yan Sun

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STEALTH: Secure Transformer for Encrypted Alignment of Latent Text Embeddings via Semantic Isomorphism Enforcement (SIE) Loss Function Nafew Azim, Nabeel Mohammed

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Steering Dialogue Dynamics for Robustness Against Multi-Turn Jailbreaking Attacks Hanjiang Hu, Alexander Robey, Changliu Liu

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Steering Large Reasoning Models Towards Concise Reasoning via Flow Matching Yawei Li, Benjamin Bergner, Yinghan Zhao, Vihang Prakash Patil, Bei Chen, Cheng Wang

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Stepwise Guided Policy Optimization: Coloring Your Incorrect Reasoning in GRPO Peter Chen, Xiaopeng Li, Ziniu Li, Xi Chen, Tianyi Lin

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StethoLM: Audio Language Model for Cardiopulmonary Analysis Across Clinical Tasks Yishan Wang, Tsai-Ning Wang, Mathias Funk, Aaqib Saeed

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StFT: Spatio-Temporal Fourier Transformer for Long-Term Dynamics Prediction Da Long, Shandian Zhe, Samuel Williams, Leonid Oliker, Zhe Bai

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Still Competitive: Revisiting Recurrent Models for Irregular Time Series Prediction Ankitkumar Joshi, Milos Hauskrecht

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Stochastic Multi-Objective Multi-Armed Bandits: Regret Definition and Algorithm Mansoor Davoodi, Setareh Maghsudi

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StructEval: Benchmarking LLMs' Capabilities to Generate Structural Outputs Jialin Yang, Dongfu Jiang, Tony He, Sherman Siu, Yuxuan Zhang, Disen Liao, Zhuofeng Li, Huaye Zeng, Yiming Jia, Haozhe Wang, Benjamin Schneider, Chi Ruan, Wentao Ma, Zhiheng Lyu, Yifei Wang, Yi Lu, Quy Duc Do, Ziyan Jiang, Ping Nie, Wenhu Chen

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Structure Is Supervision: Multiview Masked Autoencoders for Radiology Sonia Laguna, Andrea Agostini, Alain Ryser, Samuel Ruiperez-Campillo, Irene Cannistraci, Moritz Vandenhirtz, Stephan Mandt, Nicolas Deperrois, Farhad Nooralahzadeh, Michael Krauthammer, Thomas M. Sutter, Julia E Vogt

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Sublinear Algorithms for Estimating Wasserstein and TV Distances: Applications to Fairness and Privacy Auditing Debabrota Basu, Debarshi Chanda

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Subspace Based Federated Unlearning Guanghao Li, Li Shen, Yan Sun, Yue Hu, Han Hu, Dacheng Tao

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Super-Linear: A Lightweight Pretrained Mixture of Linear Experts for Time Series Forecasting Liran Nochumsohn, Raz Marshanski, Hedi Zisling, Omri Azencot

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Supervised Score Aggregation for Active Anomaly Detection Kevin Bleakley, Martin Royer, Benjamin Auder

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SURFACEBENCH: A Geometry-Aware Benchmark for Symbolic Surface Discovery Sanchit Kabra, Shobhnik Kriplani, Parshin Shojaee, Chandan K. Reddy

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Symbolic Quantile Regression for the Interpretable Prediction of Conditional Quantiles Cas Oude Hoekstra, Floris den Hengst

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Symbolic Recovery of PDEs from Measurement Data Erion Morina, Philipp Scholl, Martin Holler

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Symmetry in Neural Network Parameter Spaces Bo Zhao, Robin Walters, Rose Yu

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Synapse: Adaptive Arbitration of Complementary Expertise in Time Series Foundational Models Sarkar Snigdha Sarathi Das, Palash Goyal, Mihir Parmar, Yiwen Song, Long Le, Lesly Miculicich, Jinsung Yoon, Rui Zhang, Hamid Palangi, Tomas Pfister

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Synergistic Benefits of Joint Molecule Generation and Property Prediction Adam Izdebski, Jan Olszewski, Pankhil Gawade, Krzysztof Koras, Serra Korkmaz, Valentin Rauscher, Jakub M. Tomczak, Ewa Szczurek

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Synergizing Deconfounding and Temporal Generalization for Time-Series Counterfactual Outcome Estimation Yiling Liu, Juncheng Dong, Chen Fu, Wei Shi, Ziyang Jiang, Qi Xu, Zhigang Hua, David Carlson

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SynQuE: Estimating Synthetic Dataset Quality Without Annotations Arthur Chen, Victor Zhong

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SyntheRela: A Benchmark for Synthetic Relational Database Generation Valter Hudovernik, Martin Jurkovic, Erik Štrumbelj

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T$^3$-S2S: Training-Free Triplet Tuning for Sketch to Scene Synthesis in Controllable Concept Art Generation Zhenhong Sun, Yifu Wang, Yonhon Ng, Yongzhi Xu, Daoyi Dong, Hongdong Li, Pan Ji

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TABASCO: A Fast, Simplified Model for Molecular Generation with Improved Physical Quality Carlos Vonessen, Charles Harris, Miruna Cretu, Pietro Lio

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Tabby: A Language Model Architecture for Tabular and Structured Data Synthesis Sonia Cromp, Satya Sai Srinath Namburi Gnvv, Mohammed Alkhudhayri, Catherine Cao, Samuel Guo, Nicholas Roberts, Frederic Sala

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TabRep: Training Tabular Diffusion Models with a Simple and Effective Continuous Representation Jacob Si, Zijing Ou, Mike Qu, Zhengrui Xiang, Yingzhen Li

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TACO: Training-Free Sound Prompted Segmentation via Semantically Constrained Audio-Visual CO-Factorization Hugo Malard, Michel Olvera, Stéphane Lathuilière, Slim Essid

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Task-Specific Exploration in Meta-Reinforcement Learning via Task Reconstruction Radu Stoican, Angelo Cangelosi, Christian Goerick, Thomas H Weisswange

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Teaching Invariance Using Privileged Mediation Information Dylan Zapzalka, Maggie Makar

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Template-Based Probes Are Imperfect Lenses for Counterfactual Bias Evaluation in LLMs Farnaz Kohankhaki, D. B. Emerson, Jacob-Junqi Tian, Laleh Seyyed-Kalantari, Faiza Khan Khattak

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Ternary Momentum for Quantized Training Noga Bar, Amit Attia, Michal Moshkovitz, Dotan Di Castro

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Test-Time Adaptation for Unsupervised Combinatorial Optimization Yiqiao Liao, Farinaz Koushanfar, Parinaz Naghizadeh

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TextOCVP: Object-Centric Video Prediction with Language Guidance Angel Villar-Corrales, Gjergj Plepi, Sven Behnke

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The Clever Hans Mirage: A Comprehensive Survey on Spurious Correlations in Machine Learning Wenqian Ye, Luyang Jiang, Eric Xie, Guangtao Zheng, Yunsheng Ma, Xu Cao, Dongliang Guo, Daiqing Qi, Zeyu He, Yijun Tian, Christopher W. Porter, Megan Coffee, Zhe Zeng, Sheng Li, Ziran Wang, Ting-Hao Kenneth Huang, James Matthew Rehg, Henry Kautz, Aidong Zhang

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The Confusion Is Real: GRAPHIC - A Network Science Approach to Confusion Matrices in Deep Learning Johanna S. Fröhlich, Bastian Heinlein, Jan U. Claar, Hans Rosenberger, Vasileios Belagiannis, Ralf R. Müller

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The Cost of Replicability in Active Learning Rupkatha Hira, Dominik Kau, Jessica Sorrell

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The Final-Stage Bottleneck: A Systematic Dissection of the R-Learner for Network Causal Inference Sairam S, Sara Girdhar, Shivam Soni

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The Five Ws of Multi-Agent Communication: Who Talks to Whom, When, What, and Why - A Survey from MARL to Emergent Language and LLMs Jingdi Chen, Hanqing Yang, Zongjun Liu, Carlee Joe-Wong

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The Geometry of Algorithmic Stability: A Hodge Theoretic View on Structural vs. Statistical Instability Karen Sargsyan

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The Internal Growth Function: A More General PAC Framework for Scenario Decision Making Guillaume O Berger, Raphael Jungers

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The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Guibin Zhang, Hejia Geng, Xiaohang Yu, Zhenfei Yin, Zaibin Zhang, Zelin Tan, Heng Zhou, Zhong-Zhi Li, Xiangyuan Xue, Yijiang Li, Yifan Zhou, Yang Chen, Chen Zhang, Yutao Fan, Zihu Wang, Songtao Huang, Francisco Piedrahita Velez, Yue Liao, Hongru Wang, Mengyue Yang, Heng Ji, Jun Wang, Shuicheng Yan, Philip Torr, Lei Bai

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The Pitfalls of Text Degeneration When Aligning LLMs Through Model Merge Peijun Qing, Lei Hsiung, Hefan Zhang, Haiquan Lu, Xingjian Diao, Chiyu Ma, Saeed Hassanpour, Soroush Vosoughi

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The Role of Feature Interactions in Graph-Based Tabular Deep Learning Elias Dubbeldam, Reza Mohammadi, Marit Schoonhoven, Ilker Birbil

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The Shape of Attraction in UMAP: Exploring the Embedding Forces in Dimensionality Reduction Mohammad Tariqul Islam, Jason W. Fleischer

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The Speed-up Factor: A Quantitative Multi-Iteration Active Learning Performance Metric Hannes Kath, Thiago S. Gouvêa, Daniel Sonntag

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The Synergy Dilemma of Long-CoT SFT and RL: Investigating Post-Training Techniques for Reasoning VLMs Jierun Chen, Tiezheng Yu, Haoli Bai, Lewei Yao, Jiannan Wu, Kaican Li, Fei Mi, Chaofan Tao, Lei Zhu, Manyi Zhang, Xiao-Hui Li, Lu Hou, Lifeng Shang, Qun Liu

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The Transformer Cookbook Andy Yang, Christopher Watson, Anton Xue, Satwik Bhattamishra, Jose Llarena, William Merrill, Emile Dos Santos Ferreira, Anej Svete, David Chiang

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Theoretically Understanding Data Reconstruction Leakage in Federated Learning Binghui Zhang, Zifan Wang, Meng Pang, Yuan Hong, Binghui Wang

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There Are No Champions in Supervised Long-Term Time Series Forecasting Lorenzo Brigato, Rafael Morand, Knut Joar Strømmen, Maria Panagiotou, Markus Schmidt, Stavroula Mougiakakou

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Thermodynamically Consistent Latent Dynamics Identification for Parametric Systems Xiaolong He, Yeonjong Shin, Anthony Gruber, Sohyeon Jung, Kookjin Lee, Youngsoo Choi

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Think2SQL: Blueprinting Reward Density and Advantage Scaling for Effective Text-to-SQL Reasoning Simone Papicchio, Simone Rossi, Luca Cagliero, Paolo Papotti

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ThinkEval: Practical Evaluation of Knowledge Leakage in LLM Editing Using Thought-Based Knowledge Graphs Manit Baser, Dinil Mon Divakaran, Mohan Gurusamy

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ThinkPrune: Pruning Long Chain-of-Thought of LLMs via Reinforcement Learning Bairu Hou, Yang Zhang, Jiabao Ji, Yujian Liu, Kaizhi Qian, Jacob Andreas, Shiyu Chang

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Thought-Retriever: Don't Just Retrieve Raw Data, Retrieve Thoughts for Memory-Augmented Agentic Systems Tao Feng, Pengrui Han, Guanyu Lin, Ge Liu, Jiaxuan You

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Through the Judge's Eyes: Inferred Thinking Traces Improve Reliability of LLM Raters Xingjian Zhang, Tianhong Gao, Suliang Jin, Tianhao Wang, Teng Ye, Eytan Adar, Qiaozhu Mei

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TOAST: Transformer Optimization Using Adaptive and Simple Transformations Irene Cannistraci, Simone Antonelli, Emanuele Palumbo, Thomas M. Sutter, Emanuele Rodolà, Bastian Rieck, Julia E Vogt

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ToMoE: Converting Dense Large Language Models to Mixture-of-Experts Through Dynamic Structural Pruning Shangqian Gao, Ting Hua, Reza Shirkavand, Chi-Heng Lin, Zheng Tang, Zhengao Li, Longge Yuan, Fangyi Li, Zeyu Zhang, Alireza Ganjdanesh, Qian Lou, Jie Xu, Yen-Chang Hsu

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Topological Inductive Bias Fosters Multiple Instance Learning in Data-Scarce Scenarios Salome Kazeminia, Carsten Marr, Bastian Rieck

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Topology- and Gradient-Guided Knowledge Distillation for Point Cloud Semantic Segmentation Luu Tung Hai, Thinh D. Le, Zhicheng Ding, Qing Tian, Truong-Son Hy

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Topology-Guided Graph Pre-Training and Prompt Learning on Directed Graphs Peiyu Liang, Chenguang Yang, Yixuan He, Rong Pan, Yuzhou Chen

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Toward Efficient Influence Function: Dropout as a Compression Tool Yuchen Zhang, Mohammad Mohammadi Amiri

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Towards Customized Knowledge Distillation for Efficient Dense Image Predictions Dong Zhang, Pingcheng Dong, Long Chen, Kwang-Ting Cheng

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Towards Fair In-Context Learning with Tabular Foundation Models Patrik Kenfack, Samira Ebrahimi Kahou, Ulrich Aïvodji

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Towards Fast Safe Online Reinforcement Learning via Policy Finetuning Keru Chen, Honghao Wei, Zhigang Deng, Sen Lin

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Towards Generalized Certified Robustness with Multi-Norm Training Enyi Jiang, David Shu Cheung, Gagandeep Singh

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Towards Multimodal Active Learning: Efficient Learning with Limited Paired Data Jiancheng Zhang, Yinglun Zhu

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Towards Online Multimodal Social Interaction Understanding Xinpeng Li, Shijian Deng, Bolin Lai, Weiguo Pian, James Matthew Rehg, Yapeng Tian

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Towards Scalable Language-Image Pre-Training for 3D Medical Imaging Chenhui Zhao, Yiwei Lyu, Asadur Zaman Chowdury, Edward S Harake, Akhil Kondepudi, Akshay T Rao, Xinhai Hou, Honglak Lee, Todd C Hollon

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Towards Understanding Neural Collapse: The Effects of Batch Normalization and Weight Decay Leyan Pan, Xinyuan Cao

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Training More Robust Classification Model via Discriminative Loss and Gaussian Noise Injection Hai-Vy Nguyen, Fabrice Gamboa, Sixin Zhang, Reda Chhaibi, Serge Gratton, Thierry Giaccone

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Training Speedups via Batching for Geometric Learning: An Analysis of Static and Dynamic Algorithms Daniel T. Speckhard, Tim Bechtel, Sebastian Kehl, Jonathan Godwin, Claudia Draxl

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Training-Conditional Coverage Bounds Under Covariate Shift Mehrdad Pournaderi, Yu Xiang

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Transformers as Implicit State Estimators: In-Context Learning in Dynamical Systems Usman Akram, Haris Vikalo

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Transformers in the Dark: Navigating Unknown Search Spaces via Bandit Feedback Jungtaek Kim, Thomas Zeng, Ziqian Lin, Minjae Lee, Chungpa Lee, Jy-yong Sohn, Hyung Il Koo, Kangwook Lee

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Transitioning Heads Conundrum: The Hidden Bottleneck in Long-Tailed Class-Incremental Learning Rahul Vigneswaran, Hari Chandana Kuchibhotla, Vineeth N. Balasubramanian

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TRecViT: A Recurrent Video Transformer Viorica Patraucean, Xu Owen He, Joseph Heyward, Chuhan Zhang, Mehdi S. M. Sajjadi, George-Cristian Muraru, Artem Zholus, Mahdi Karami, Ross Goroshin, Yutian Chen, Simon Osindero, Joao Carreira, Razvan Pascanu

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TS-Reasoner: Domain-Oriented Time Series Inference Agents for Reasoning and Automated Analysis Wen Ye, Wei Yang, Defu Cao, Yizhou Zhang, Lumingyuan Tang, Jie Cai, Yan Liu

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Tube Loss: A Novel Loss Function for Prediction Interval Estimation Pritam Anand, Tathagata Bandyopadhyay, Suresh Chandra

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Tumor-Anchored Deep Feature Random Forests for Out-of-Distribution Detection in Lung Cancer Segmentation Aneesh Rangnekar, Harini Veeraraghavan

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ULTra: Unveiling Latent Token Interpretability in Transformer-Based Understanding and Segmentation Hesam Hosseini, Ghazal Hosseini Mighan, Amirabbas Afzali, Sajjad Amini, Amir Houmansadr

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UltraEdit: Training-, Subject-, and Memory-Free Lifelong Editing in Language Models Xiaojie Gu, Ziying Huang, Jia-Chen Gu, Kai Zhang

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Uncertainty-Aware Surrogate-Based Amortized Bayesian Inference for Computationally Expensive Models Stefania Scheurer, Philipp Reiser, Tim Brünnette, Wolfgang Nowak, Anneli Guthke, Paul-Christian Bürkner

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Uncertainty-Aware Systems for Human-AI Collaboration Vasco Pearson, Jean V. Alves, Jacopo Bono, Mario A. T. Figueiredo, Pedro Bizarro

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Uncovering the Computational Roles of Nonlinearity in Sequence Modeling Using Almost-Linear RNNs Manuel Brenner, Georgia Koppe

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Uncovering the Redundancy in Transformers via a Unified Study of Layer Dropping Shwai He, Guoheng Sun, Zheyu Shen, Ang Li

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Understanding Accelerated Gradient Methods: Lyapunov Analyses and Hamiltonian-Assisted Interpretations Penghui Fu, Zhiqiang Tan

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Understanding Guidance Scale in Diffusion Models from a Geometric Perspective Zhiyuan Zhan, Liuzhuozheng Li, Masashi Sugiyama

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Unifying VXAI: A Systematic Review and Framework for the Evaluation of Explainable AI David Dembinsky, Adriano Lucieri, Stanislav Frolov, Hiba Najjar, Ko Watanabe, Andreas Dengel

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UniRec: Unified Multimodal Encoding for LLM-Based Recommendations Zijie Lei, Tao Feng, Zhigang Hua, Yan Xie, Guanyu Lin, Shuang Yang, Ge Liu, Jiaxuan You

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Unlearning in Diffusion Models Under Data Constraints: A Variational Inference Approach Subhodip Panda, M S Varun, Shreyans Jain, Sarthak Kumar Maharana, Prathosh Ap

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Unlocking [CLS] Features for Continual Post-Training Murat Onur Yildirim, Elif Ceren Gok Yildirim, Joaquin Vanschoren

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Unrealized Expectations: Comparing AI Methods vs Classical Algorithms for Maximum Independent Set Yikai Wu, Haoyu Zhao, Sanjeev Arora

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Unstable Unlearning: The Hidden Risk of Concept Resurgence in Diffusion Models Vinith Menon Suriyakumar, Rohan Alur, Ayush Sekhari, Manish Raghavan, Ashia C. Wilson

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Unsupervised Domain Adaptation for Binary Classification with an Unobservable Source Subpopulation Chao Ying, Jun Jin, Haotian Zhang, Qinglong Tian, Yanyuan Ma, Sharon Li, Jiwei Zhao

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V-OCBF: Learning Safety Filters from Offline Data via Value-Guided Offline Control Barrier Functions Mumuksh Tayal, Manan Tayal, Aditya Singh, Shishir Kolathaya, Ravi Prakash

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Variance Matters: Improving Domain Adaptation via Stratified Sampling Andrea Napoli, Paul White

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Variational Visual Question Answering for Uncertainty-Aware Selective Prediction Tobias Jan Wieczorek, Nathalie Daun, Mohammad Emtiyaz Khan, Marcus Rohrbach

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Vejde: A Framework for Inductive Deep Reinforcement Learning Based on Factor Graph Color Refinement Jakob Nyberg, Pontus Johnson

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VEM: Environment-Free Exploration for Training GUI Agent with Value Environment Model Mengzhuo Chen, Jiani Zheng, Lu Wang, Fangkai Yang, Chaoyun Zhang, Lingrui Mei, Wenjie Yin, Qingwei Lin, Dongmei Zhang, Saravan Rajmohan

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VICON: Vision In-Context Operator Networks for Multi-Physics Fluid Dynamics Prediction Yadi Cao, Yuxuan Liu, Liu Yang, Rose Yu, Hayden Schaeffer, Stanley Osher

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Video Prediction Transformers Without Recurrence or Convolution Yujin Tang, Lu Qi, Xiangtai Li, Chao Ma, Ming-Hsuan Yang

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VidHal: Benchmarking Hallucinations in Vision LLMs Wey Yeh Choong, Yangyang Guo, Mohan Kankanhalli

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ViTaPEs: Visuotactile Position Encodings for Cross-Modal Alignment in Multimodal Transformers Fotios Lygerakis, Ozan Özdenizci, Elmar Rueckert

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VLM2Vec-V2: Advancing Multimodal Embedding for Videos, Images, and Visual Documents Rui Meng, Ziyan Jiang, Ye Liu, Mingyi Su, Xinyi Yang, Yuepeng Fu, Can Qin, Raghuveer Thirukovalluru, Xuan Zhang, Zeyuan Chen, Ran Xu, Caiming Xiong, Yingbo Zhou, Wenhu Chen, Semih Yavuz

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VScan: Rethinking Visual Token Reduction for Efficient Large Vision-Language Models Ce Zhang, Kaixin Ma, Tianqing Fang, Wenhao Yu, Hongming Zhang, Zhisong Zhang, Haitao Mi, Dong Yu

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WAREX: Web Agent Reliability Evaluation on Existing Benchmarks Su Kara, Fazle Elahi Faisal, Suman Nath

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Wasserstein Bounds for Generative Diffusion Models with Gaussian Tail Targets Wang Xixian, Zhongjian Wang

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Watermarking Degrades Alignment in Language Models: Analysis and Mitigation Apurv Verma, Hai Phan, Shubhendu Trivedi

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Weakly-Supervised Disentangled Representation Learning via Filter-Based Adaptive Swapping Zhenyu Zong, Qidi Wang, Simon Yu, Hongpeng Cao, Yanbing Mao, Han Zhao, Lui Sha, Huajie Shao

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What One View Reveals, Another Conceals: 3D-Consistent Visual Reasoning with LLMs Dan Kushnir, László Freund

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When Are Two Scores Better than One? Investigating Ensembles of Diffusion Models Raphaël Razafindralambo, Rémy Sun, Damien Garreau, Frederic Precioso, Pierre-Alexandre Mattei

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When Attention Collapses: How Degenerate Layers in LLMs Enable Smaller, Stronger Models Sunny Sanyal, Ravid Shwartz-Ziv, Alex Dimakis, Sujay Sanghavi

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When Does LoRA Reuse Work? Theoretical Limits and Mechanisms for Recycling LoRAs Without Data Access Mei-Yen Chen, Thi Thu Uyen Hoang, Michael Hahn, M. Saquib Sarfraz

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Wikipedia in the Era of LLMs: Evolution and Risks Siming Huang, Yuliang Xu, Mingmeng Geng, Yao Wan, Dongping Chen

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XCTFormer: Leveraging Cross-Channel and Cross-Time Dependencies for Enhanced Time-Series Analysis Israel Zexer, Omri Azencot

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You Only Train Once: Differentiable Subset Selection for Omics Data Daphné Chopard, Jorge da Silva Gonçalves, Irene Cannistraci, Thomas M. Sutter, Julia E Vogt

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Α-OCC: Uncertainty-Aware Camera-Based 3D Semantic Occupancy Prediction Sanbao Su, Nuo Chen, Chenchen Lin, Felix Juefei-Xu, Chen Feng, Fei Miao

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