TMLR 2026

254 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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$\texttt{C2-DPO}$: 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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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 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 Simple Connection from Loss Flatness to Compressed Neural Representations Shirui Chen, Stefano Recanatesi, Eric Todd SheaBrown

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

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

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

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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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Batch Entanglement Detection in Parameterized Qubit States Using Classical Bandit Algorithms Bharati K, 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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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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Bootstrapping Task Spaces for Self-Improvement Minqi Jiang, Andrei Lupu, Yoram Bachrach

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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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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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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Privacy Profiles Under Tradeoff Composition Paul Glasserman

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

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

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

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

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

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

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

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

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

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

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

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

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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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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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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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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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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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