Paperjam

#5101 · Joao Monteiro, Pierre-André Noël, Étienne Marcotte, Sai Rajeswar Mudumba, Valentina Zantedeschi, David Vazquez, Nicolas Chapados, Chris Pal, Perouz Taslakian

AgentBoard: An Analytical Evaluation Board of Multi-turn LLM Agents

#5102 · Ma Chang, Junlei Zhang, Zhihao Zhu, Cheng Yang, Yujiu Yang, Yaohui Jin, Zhenzhong Lan, Lingpeng Kong, Junxian He

FindingEmo: An Image Dataset for Emotion Recognition in the Wild

#5103 · Laurent Mertens, Elahe Yargholi, Hans Op de Beeck, Jan Van den Stock, Joost Vennekens

Causal Discovery from Event Sequences by Local Cause-Effect Attribution

#5104 · Joscha Cüppers, Sascha Xu, Ahmed Musa, Jilles Vreeken

Causal discovery with endogenous context variables

#5105 · Wiebke Günther, Oana-Iuliana Popescu, Martin Rabel, Urmi Ninad, Andreas Gerhardus, Jakob Runge

Do causal predictors generalize better to new domains?

#5106 · Vivian Nastl, Moritz Hardt

Sample Efficient Bayesian Learning of Causal Graphs from Interventions

#5107 · Zihan Zhou, Muhammad Qasim Elahi, Murat Kocaoglu

Ordering-Based Causal Discovery for Linear and Nonlinear Relations

#5108 · Zhuopeng Xu, Yujie Li, Cheng Liu, Ning Gui

Natural Counterfactuals With Necessary Backtracking

#5109 · GUANG-YUAN HAO, Jiji Zhang, Biwei Huang, Hao Wang, Kun Zhang

Marrying Causal Representation Learning with Dynamical Systems for Science

#5110 · Dingling Yao, Caroline Muller, Francesco Locatello

Through the Looking-Glass: Tracing Shifts in AI Data Consent across the Web

#5200 · Shayne Longpre, Robert Mahari, Ariel Lee, Campbell Lund, Hamidah Oderinwale, William Brannon, Nayan Saxena, Naana Obeng-Marnu, Tobin South, Cole Hunter, Kevin Klyman, Christopher Klamm, Hailey Schoelkopf, Nikhil Singh, Manuel Cherep, Ahmad Anis, An Dinh, Caroline Shamiso Chitongo, Da Yin, Damien Sileo, Deividas Mataciunas, Diganta Misra, Emad Alghamdi, Enrico Shippole, Jianguo Zhang, Joanna Materzynska, Kun Qian, Kushagra Tiwary, Lester James V. Miranda, Manan Dey, Minnie Liang, Mohammed Hamdy, Niklas Muennighoff, Seonghyeon Ye, Seungone Kim, Shrestha Mohanty, Vipul Gupta, Vivek Sharma, Minh Chien Vu, Xuhui Zhou, Yizhi Li, Caiming Xiong, Luis Villa, Stella Biderman, Hanlin Li, Daphne Ippolito, Sara Hooker, Jad Kabbara, Alex Pentland

ActionAtlas: A VideoQA Benchmark for Fine-grained Action Recognition

#5201 · Mohammadreza (Reza) Salehi, Jae Sung Park, Aditya Kusupati, Ranjay Krishna, Yejin Choi, Hannaneh Hajishirzi, Ali Farhadi

StreamBench: Towards Benchmarking Continuous Improvement of Language Agents

#5202 · Cheng-Kuang Wu, Zhi Rui Tam, Chieh-Yen Lin, Yun-Nung (Vivian) Chen, Hung-yi Lee

Cross-Care: Assessing the Healthcare Implications of Pre-training Data on Language Model Bias

#5203 · Shan Chen, Jack Gallifant, Mingye Gao, Pedro Moreira, Nikolaj Munch, Ajay Muthukkumar, Arvind Rajan, Jaya Kolluri, Amelia Fiske, Janna Hastings, Hugo Aerts, Brian Anthony, Leo Anthony Celi, William La Cava, Danielle Bitterman

PUZZLES: A Benchmark for Neural Algorithmic Reasoning

#5204 · Benjamin Estermann, Luca Lanzendörfer, Yannick Niedermayr, Roger Wattenhofer

Dispelling the Mirage of Progress in Offline MARL through Standardised Baselines and Evaluation

#5205 · Juan Formanek, Callum R. Tilbury, Louise Beyers, Jonathan Shock, Arnu Pretorius

The Multimodal Universe: Enabling Large-Scale Machine Learning with 100TBs of Astronomical Scientific Data

#5206 · Eirini Angeloudi, Jeroen Audenaert, Micah Bowles, Benjamin M. Boyd, David Chemaly, Brian Cherinka, Ioana Ciucă, Miles Cranmer, Aaron Do, Matthew Grayling, Erin E. Hayes, Tom Hehir, Shirley Ho, Marc Huertas-Company, Kartheik Iyer, Maja Jablonska, Francois Lanusse, Henry Leung, Kaisey Mandel, Rafael Martínez-Galarza, Peter Melchior, Lucas Meyer, Liam Parker, Helen Qu, Jeff Shen, Michael Smith, Connor Stone, Mike Walmsley, John Wu

IKEA Manuals at Work: 4D Grounding of Assembly Instructions on Internet Videos

#5207 · Yunong Liu, Weiyu Liu, Shubh Khanna, Cristobal Eyzaguirre, Manling Li, Juan Carlos Niebles, Vineeth Ravi, Saumitra Mishra, Jiajun Wu

NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking

#5208 · Daniel Dauner, Marcel Hallgarten, Tianyu Li, Xinshuo Weng, Zhiyu Huang, Zetong Yang, Hongyang Li, Igor Gilitschenski, Boris Ivanovic, Marco Pavone, Andreas Geiger, Kashyap Chitta

SR-CACO-2: A Dataset for Confocal Fluorescence Microscopy Image Super-Resolution

#5209 · Soufiane Belharbi, Mara Whitford, Phuong Hoang, Shakeeb Murtaza, Luke McCaffrey, Eric Granger

BeanCounter: A low-toxicity, large-scale, and open dataset of business-oriented text

#5210 · Siyan Wang, Bradford Levy

RAGChecker: A Fine-grained Framework for Diagnosing Retrieval-Augmented Generation

#5211 · Dongyu Ru, Lin Qiu, Xiangkun Hu, Tianhang Zhang, Peng Shi, Shuaichen Chang, Cheng Jiayang, Cunxiang Wang, Shichao Sun, Huanyu Li, Zizhao Zhang, Binjie Wang, Jiarong Jiang, Tong He, Zhiguo Wang, Pengfei Liu, Yue Zhang, Zheng Zhang

RoleAgent: Building, Interacting, and Benchmarking High-quality Role-Playing Agents from Scripts

#5300 · Jiaheng Liu, Zehao Ni, Haoran Que, Sun, Noah Wang, Jian Yang, JiakaiWang, Hongcheng Guo, Z.Y. Peng, Ge Zhang, Jiayi Tian, Xingyuan Bu, Ke Xu, Wenge Rong, Junran Peng, ZHAO-XIANG ZHANG

SLICE-100K: A Multimodal Dataset for Extrusion-based 3D Printing

#5301 · Anushrut Nirmal Jignasu, Kelly Marshall, Ankush Kumar Mishra, Lucas Nerone Rillo, Baskar Ganapathysubramanian, Aditya Balu, Chinmay Hegde, Adarsh Krishnamurthy

SubjECTive-QA: A dataset for the subjective evaluation of answers in Earnings Call Transcripts (ECTs)

#5302 · Huzaifa Pardawala, Siddhant Sukhani, Veer Kejriwal, Rohan Bhasin, Abhishek Pillai, Dhruv Adha, Tarun Mandapati, Andrew DiBiasio, Agam Shah, Sudheer Chava

DECO-Bench: Unified Benchmark for Decoupled Task-Agnostic Synthetic Data Release

#5303 · Farzaneh Askari, Lingjuan Lyu, Vivek Sharma

Evaluating Numerical Reasoning in Text-to-Image Models

#5304 · Ivana Kajic, Olivia Wiles, Isabela Albuquerque, Matthias Bauer, Su Wang, Jordi Pont-Tuset, Aida Nematzadeh

NovoBench: Benchmarking Deep Learning-based \emph{De Novo} Sequencing Methods in Proteomics

#5305 · Jingbo Zhou, Shaorong Chen, Jun Xia, Sizhe Liu, Tianze Ling, Wenjie Du, Yue Liu, Jianwei Yin, Stan Z. Li

MMBench-Video: A Long-Form Multi-Shot Benchmark for Holistic Video Understanding

#5306 · Xinyu Fang, Kangrui Mao, Haodong Duan, Xiangyu Zhao, Yining Li, Dahua Lin, Kai Chen

ConvBench: A Multi-Turn Conversation Evaluation Benchmark with Hierarchical Ablation Capability for Large Vision-Language Models

#5307 · Shuo Liu, Kaining Ying, Hao Zhang, yue yang, Yuqi Lin, Tianle Zhang, Chuanhao Li, Yu Qiao, Ping Luo, Wenqi Shao, Kaipeng Zhang

WorkArena++: Towards Compositional Planning and Reasoning-based Common Knowledge Work Tasks

#5308 · Léo Boisvert, Megh Thakkar, Maxime Gasse, Massimo Caccia, Thibault de Chezelles, Quentin Cappart, Nicolas Chapados, Alexandre Lacoste, Alexandre Drouin

Noisy Ostracods: A Fine-Grained, Imbalanced Real-World Dataset for Benchmarking Robust Machine Learning and Label Correction Methods

#5309 · Jiamian Hu, Hong Yuanyuan, Yihua Chen, He Wang, Moriaki Yasuhara

Benchmarking LLMs via Uncertainty Quantification

#5310 · Fanghua Ye, Mingming Yang, Jianhui Pang, Longyue Wang, Derek Wong, Emine Yilmaz, Shuming Shi, Zhaopeng Tu

SpreadsheetBench: Towards Challenging Real World Spreadsheet Manipulation

#5311 · Zeyao Ma, Bohan Zhang, Jing Zhang, Jifan Yu, Xiaokang Zhang, Xiaohan Zhang, Sijia Luo, Xi Wang, Jie Tang

Norms for Managing Datasets: A Systematic Review of NeurIPS Datasets

#5400 · Yiwei Wu, Leah Ajmani, Shayne Longpre, Hanlin Li

BenchX: A Unified Benchmark Framework for Medical Vision-Language Pretraining on Chest X-Rays

#5401 · Yang Zhou, Tan Faith, Yanyu Xu, Sicong Leng, Xinxing Xu, Yong Liu, Rick Siow Mong Goh

Embodied Agent Interface: Benchmarking LLMs for Embodied Decision Making

#5402 · Manling Li, Shiyu Zhao, Qineng Wang, Kangrui Wang, Yu Zhou, Sanjana Srivastava, Cem Gokmen, Tony Lee, Erran Li Li, Ruohan Zhang, Weiyu Liu, Percy Liang, Li Fei-Fei, Jiayuan Mao, Jiajun Wu

MLLMGuard: A Multi-dimensional Safety Evaluation Suite for Multimodal Large Language Models

#5403 · Tianle Gu, Zeyang Zhou, Kexin Huang, Liang Dandan, Yixu Wang, Haiquan Zhao, Yuanqi Yao, xingge qiao, Keqing wang, Yujiu Yang, Yan Teng, Yu Qiao, Yingchun Wang

Nuclear Fusion Diamond Polishing Dataset

#5404 · Antonios Alexos, Junze Liu, Shashank Galla, Sean Hayes, Kshitij Bhardwaj, Alexander Schwartz, Monika Biener, Pierre Baldi, Satish Bukkapatnam, Suhas Bhandarkar

MMLONGBENCH-DOC: Benchmarking Long-context Document Understanding with Visualizations

#5405 · Yubo Ma, Yuhang Zang, Liangyu Chen, Meiqi Chen, Yizhu Jiao, Xinze Li, Xinyuan Lu, Ziyu Liu, Yan Ma, Xiaoyi Dong, Pan Zhang, Liangming Pan, Yu-Gang Jiang, Jiaqi Wang, Yixin Cao, Aixin Sun

BLEnD: A Benchmark for LLMs on Everyday Knowledge in Diverse Cultures and Languages

#5406 · Junho Myung, Nayeon Lee, Yi Zhou, Jiho Jin, Rifki Putri, Dimosthenis Antypas, Hsuvas Borkakoty, Eunsu Kim, Carla Perez-Almendros, Abinew Ali Ayele, Victor Gutierrez Basulto, Yazmin Ibanez-Garcia, Hwaran Lee, Shamsuddeen H Muhammad, Kiwoong Park, Anar Rzayev, Nina White, Seid Muhie Yimam, Mohammad Taher Pilehvar, Nedjma Ousidhoum, Jose Camacho-Collados, Alice Oh

RealMAN: A Real-Recorded and Annotated Microphone Array Dataset for Dynamic Speech Enhancement and Localization

#5407 · Bing Yang, Changsheng Quan, Yabo Wang, Pengyu Wang, Yujie Yang, Ying Fang, Nian Shao, Hui Bu, Xin Xu, Xiaofei Li

SS3DM: Benchmarking Street-View Surface Reconstruction with a Synthetic 3D Mesh Dataset

#5408 · Yubin Hu, Kairui Wen, Heng Zhou, Xiaoyang Guo, Yong-jin Liu

FEDMEKI: A Benchmark for Scaling Medical Foundation Models via Federated Knowledge Injection

#5409 · Jiaqi Wang, Xiaochen Wang, Lingjuan Lyu, Jinghui Chen, Fenglong Ma

Towards Open Respiratory Acoustic Foundation Models: Pretraining and Benchmarking

#5410 · Yuwei Zhang, Tong Xia, Jing Han, Yu Wu, Georgios Rizos, Yang Liu, Mohammed Mosuily, J Ch, Cecilia Mascolo

SureMap: Simultaneous mean estimation for single-task and multi-task disaggregated evaluation

#5500 · Misha Khodak, Lester Mackey, Alexandra Chouldechova, Miro Dudik

Fairness-Aware Estimation of Graphical Models

#5501 · Zhuoping Zhou, Davoud Ataee Tarzanagh, Bojian Hou, Qi Long, Li Shen

Geometry Cloak: Preventing TGS-based 3D Reconstruction from Copyrighted Images

#5502 · Qi Song, Ziyuan Luo, Ka Chun Cheung, Simon See, Renjie Wan

Proportional Fairness in Non-Centroid Clustering

#5503 · Ioannis Caragiannis, Evi Micha, Nisarg Shah

Towards Harmless Rawlsian Fairness Regardless of Demographic Prior

#5504 · Xuanqian Wang, Jing Li, Ivor Tsang, Yew Soon Ong

Fair and Welfare-Efficient Constrained Multi-Matchings under Uncertainty

#5505 · Elita Lobo, Justin Payan, Cyrus Cousins, Yair Zick

Do Counterfactually Fair Image Classifiers Satisfy Group Fairness? -- A Theoretical and Empirical Study

#5506 · Sangwon Jung, Sumin Yu, Sanghyuk Chun, Taesup Moon

FairMedFM: Fairness Benchmarking for Medical Imaging Foundation Models

#5507 · Ruinan Jin, Zikang Xu, Yuan Zhong, Qingsong Yao, DOU QI, S. Kevin Zhou, Xiaoxiao Li

Reproducibility study of "Robust Fair Clustering: A Novel Fairness Attack and Defense Framework"

#5508 · Lucas Ponticelli, Vincent Loos, Eren Kocadag, Kacper Bartosik

Reproducibility Study of "Robust Fair Clustering: A Novel Fairness Attack and Defense Framework"

#5509 · Iason Skylitsis, Zheng Feng, Idries Nasim, Camille Niessink

Can LLMs Implicitly Learn Numeric Parameter Constraints in Data Science APIs?

#5510 · Yinlin Deng, Chunqiu Steven Xia, Zhezhen Cao, Meiziniu Li, LINGMING ZHANG

Fairness-Aware Meta-Learning via Nash Bargaining

#5600 · Yi Zeng, Xuelin Yang, Li Chen, Cristian Ferrer, Ming Jin, Michael Jordan, Ruoxi Jia

DLAD: Improving Logits-based Detector without Logits from Black-box LLMs

#5601 · Cong Zeng, Shengkun Tang, Xianjun Yang, Yuanzhou Chen, Yiyou Sun, Zhiqiang Xu, Yao Li, Haifeng Chen, Wei Cheng, Dongkuan (DK) Xu

On the Computational Landscape of Replicable Learning

#5602 · Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas, Felix Zhou

Is Cross-validation the Gold Standard to Estimate Out-of-sample Model Performance?

#5603 · Garud Iyengar, Henry Lam, Tianyu Wang

Provable Benefit of Cutout and CutMix for Feature Learning

#5604 · Junsoo Oh, Chulhee Yun

Oracle-Efficient Differentially Private Learning with Public Data

#5605 · Adam Block, Mark Bun, Rathin Desai, Abhishek Shetty, Steven Wu

Distribution Learning with Valid Outputs Beyond the Worst-Case

#5606 · Nicholas Rittler, Kamalika Chaudhuri

Realizable $H$-Consistent and Bayes-Consistent Loss Functions for Learning to Defer

#5607 · Anqi Mao, Mehryar Mohri, Yutao Zhong

On the Complexity of Learning Sparse Functions with Statistical and Gradient Queries

#5608 · Nirmit Joshi, Theodor Misiakiewicz, Nati Srebro

Near-Optimality of Contrastive Divergence Algorithms

#5609 · Pierre Glaser, Kevin Han Huang, Arthur Gretton

Towards a Theoretical Understanding of the 'Reversal Curse' via Training Dynamics

#5610 · Hanlin Zhu, Baihe Huang, Shaolun Zhang, Michael Jordan, Jiantao Jiao, Yuandong Tian, Stuart J Russell

Derandomizing Multi-Distribution Learning

#5700 · Kasper Green Larsen, Omar Montasser, Nikita Zhivotovskiy

Online Estimation via Offline Estimation: An Information-Theoretic Framework

#5701 · Dylan J Foster, Yanjun Han, Jian Qian, Alexander Rakhlin

Solving Sparse \& High-Dimensional-Output Regression via Compression

#5702 · Renyuan Li, Zhehui Chen, Guanyi Wang

Metric Transforms and Low Rank Representations of Kernels for Fast Attention

#5703 · Timothy Chu, Josh Alman, Gary L. Miller, Shyam Narayanan, Mark Sellke, Zhao Song

The Price of Implicit Bias in Adversarially Robust Generalization

#5704 · Nikolaos Tsilivis, Natalie Frank, Nati Srebro, Julia Kempe

Semi-Supervised Sparse Gaussian Classification: Provable Benefits of Unlabeled Data

#5705 · Eyar Azar, Boaz Nadler

Credit Attribution and Stable Compression

#5706 · Roi Livni, Shay Moran, Kobbi Nissim, Chirag Pabbaraju

Entropy testing and its application to testing Bayesian networks

#5707 · Clément L Canonne, Qiping Yang

4+3 Phases of Compute-Optimal Neural Scaling Laws

#5708 · Elliot Paquette, Courtney Paquette, Lechao Xiao, Jeffrey Pennington

Separation and Bias of Deep Equilibrium Models on Expressivity and Learning Dynamics

#5709 · Zhoutong Wu, Yimu Zhang, Cong Fang, Zhouchen Lin

Robust Mixture Learning when Outliers Overwhelm Small Groups

#5710 · Daniil Dmitriev, Rares-Darius Buhai, Stefan Tiegel, Alexander Wolters, Gleb Novikov, Amartya Sanyal, David Steurer, Fanny Yang

Lower Bounds of Uniform Stability in Gradient-Based Bilevel Algorithms for Hyperparameter Optimization

#5800 · Rongzhen Wang, Chenyu Zheng, Guoqiang Wu, Xu Min, Xiaolu Zhang, Jun Zhou, Chongxuan LI

An Adaptive Approach for Infinitely Many-armed Bandits under Generalized Rotting Constraints

#5801 · Jung-hun Kim, Milan Vojnovic, Se-Young Yun

Robust Neural Contextual Bandit against Adversarial Corruptions

#5802 · Yunzhe Qi, Yikun Ban, Arindam Banerjee, Jingrui He

Saliency-driven Experience Replay for Continual Learning

#5803 · Giovanni Bellitto, Federica Proietto Salanitri, Matteo Pennisi, Matteo Boschini, Lorenzo Bonicelli, Angelo Porrello, SIMONE CALDERARA, Simone Palazzo, Concetto Spampinato

Online Non-convex Learning in Dynamic Environments

#5804 · Zhipan Xu, Lijun Zhang

Sample Complexity of Posted Pricing for a Single Item

#5805 · Billy Jin, Thomas Kesselheim, Will Ma, Sahil Singla

Communication Bounds for the Distributed Experts Problem

#5806 · Zhihao Jia, Qi Pang, Trung Tran, David Woodruff, Zhihao Zhang, Wenting Zheng

Online Control with Adversarial Disturbance for Continuous-time Linear Systems

#5807 · Jingwei Li, Jing Dong, Can Chang, Baoxiang Wang, Jingzhao Zhang

Online Composite Optimization Between Stochastic and Adversarial Environments

#5808 · Yibo Wang, SIJIA CHEN, Wei Jiang, Wenhao Yang, Yuanyu Wan, Lijun Zhang

Towards Efficient and Optimal Covariance-Adaptive Algorithms for Combinatorial Semi-Bandits

#5809 · Julien Zhou, Pierre Gaillard, Thibaud Rahier, Houssam Zenati, Julyan Arbel

Almost Minimax Optimal Best Arm Identification in Piecewise Stationary Linear Bandits

#5810 · Yunlong Hou, Vincent Tan, Zixin Zhong

FUGAL: Feature-fortified Unrestricted Graph Alignment

#5900 · Aditya Bommakanti, Harshith Vonteri, Konstantinos Skitsas, Sayan Ranu, Davide Mottin, Panagiotis Karras

Multidimensional Fractional Programming for Normalized Cuts

#5901 · Yannan Chen, Beichen Huang, Licheng Zhao, Kaiming Shen

Exploring Jacobian Inexactness in Second-Order Methods for Variational Inequalities: Lower Bounds, Optimal Algorithms and Quasi-Newton Approximations

#5902 · Artem Agafonov, Petr Ostroukhov, Roman Mozhaev, Konstantin Yakovlev, Eduard Gorbunov, Martin Takac, Alexander Gasnikov, Dmitry Kamzolov

Semidefinite Relaxations of the Gromov-Wasserstein Distance

#5903 · Junyu Chen, Binh T. Nguyen, Shang Koh, Yong Sheng Soh

Nesterov acceleration despite very noisy gradients

#5904 · Kanan Gupta, Jonathan W. Siegel, Stephan Wojtowytsch

SkipPredict: When to Invest in Predictions for Scheduling

#5905 · Rana Shahout, Michael Mitzenmacher

From Linear to Linearizable Optimization: A Novel Framework with Applications to Stationary and Non-stationary DR-submodular Optimization

#5906 · Mohammad Pedramfar, Vaneet Aggarwal

Why Warmup the Learning Rate? Underlying Mechanisms and Improvements

#5907 · Dayal Singh Kalra, Maissam Barkeshli

An Improved Empirical Fisher Approximation for Natural Gradient Descent

#5908 · Xiaodong Wu, Wenyi Yu, Chao Zhang, Phil Woodland

The High Line: Exact Risk and Learning Rate Curves of Stochastic Adaptive Learning Rate Algorithms

#5909 · Elizabeth Collins-Woodfin, Inbar Seroussi, Begoña García Malaxechebarría, Andrew W. Mackenzie, Elliot Paquette, Courtney Paquette

Bandits with Abstention under Expert Advice

#5910 · Stephen Pasteris, Alberto Rumi, Maximilian Thiessen, Shota Saito, Atsushi Miyauchi, Fabio Vitale, Mark Herbster

Piecewise-Stationary Bandits with Knapsacks

#5911 · Xilin Zhang, Wang Chi Cheung

Revisiting Ensembling in One-Shot Federated Learning

#6000 · Youssef Allouah, Akash Dhasade, Rachid Guerraoui, Nirupam Gupta, Anne-marie Kermarrec, Rafael Pinot, Rafael Pires, Rishi Sharma

CoBo: Collaborative Learning via Bilevel Optimization

#6001 · Diba Hashemi, Lie He, Martin Jaggi

BitDelta: Your Fine-Tune May Only Be Worth One Bit

#6002 · James Liu, Guangxuan Xiao, Kai Li, Jason Lee, Song Han, Tri Dao, Tianle Cai

FIARSE: Model-Heterogeneous Federated Learning via Importance-Aware Submodel Extraction

#6003 · Feijie Wu, Xingchen Wang, Yaqing Wang, TIanci Liu, Lu Su, Jing Gao

Fundamental Convergence Analysis of Sharpness-Aware Minimization

#6004 · Pham Khanh, Hoang-Chau Luong, Boris Mordukhovich, Dat Tran

Collaboration! Towards Robust Neural Methods for Routing Problems

#6005 · Jianan Zhou, Yaoxin Wu, Zhiguang Cao, Wen Song, Jie Zhang, Zhiqi Shen

Generalization Bound and Learning Methods for Data-Driven Projections in Linear Programming

#6006 · Shinsaku Sakaue, Taihei Oki

Learning to Solve Quadratic Unconstrained Binary Optimization in a Classification Way

#6007 · Ming Chen, Jie Chun, Shang Xiang, Luona Wei, Yonghao Du, Qian Wan, Yuning Chen, Yingwu Chen

Loss Landscape Characterization of Neural Networks without Over-Parametrization

#6008 · Rustem Islamov, Niccolò Ajroldi, Antonio Orvieto, Aurelien Lucchi

A Globally Optimal Portfolio for m-Sparse Sharpe Ratio Maximization

#6009 · Yizun Lin, Zhao-Rong Lai, Cheng Li

Nonconvex Federated Learning on Compact Smooth Submanifolds With Heterogeneous Data

#6010 · Jiaojiao Zhang, Jiang Hu, Anthony Man-Cho So, Mikael Johansson

Efficient Sign-Based Optimization: Accelerating Convergence via Variance Reduction

#6011 · Wei Jiang, Sifan Yang, Wenhao Yang, Lijun Zhang

Adam with model exponential moving average is effective for nonconvex optimization

#6012 · Kwangjun Ahn, Ashok Cutkosky

Differentially Private Optimization with Sparse Gradients

#6100 · Badih Ghazi, Cristóbal Guzmán, Pritish Kamath, Ravi Kumar, Pasin Manurangsi

Privacy without Noisy Gradients: Slicing Mechanism for Generative Model Training

#6101 · Kristjan Greenewald, Yuancheng Yu, Hao Wang, Kai Xu

Stepping Forward on the Last Mile

#6102 · Chen Feng, Jay Zhuo, Parker Zhang, Ramchalam Kinattinkara Ramakrishnan, Zhaocong Yuan, Andrew Zou Li

Approximation-Aware Bayesian Optimization

#6103 · Natalie Maus, Kyurae Kim, David Eriksson, Geoff Pleiss, John Cunningham, Jacob Gardner

Bayesian Optimisation with Unknown Hyperparameters: Regret Bounds Logarithmically Closer to Optimal

#6104 · Juliusz Ziomek, Masaki Adachi, Michael A Osborne

Stopping Bayesian Optimization with Probabilistic Regret Bounds

#6105 · James Wilson

Minimizing UCB: a Better Local Search Strategy in Local Bayesian Optimization

#6106 · ZHEYI FAN, Wenyu Wang, Szu Hui Ng, Qingpei Hu

Decision-Focused Learning with Directional Gradients

#6107 · Michael Huang, Vishal Gupta

Localized Adaptive Risk Control

#6108 · Matteo Zecchin, Osvaldo Simeone

Conformal Inverse Optimization

#6109 · Bo Lin, Erick Delage, Timothy Chan

Regularized Adaptive Momentum Dual Averaging with an Efficient Inexact Subproblem Solver for Training Structured Neural Network

#6110 · Zih-Syuan Huang, Ching-pei Lee

Private Edge Density Estimation for Random Graphs: Optimal, Efficient and Robust

#6200 · Hongjie Chen, Jingqiu Ding, Yiding Hua, David Steurer

Disentangled Style Domain for Implicit $z$-Watermark Towards Copyright Protection

#6201 · Junqiang Huang, Zhaojun Guo, Ge Luo, Zhenxing Qian, Sheng Li, Xinpeng Zhang

Sample-Efficient Private Learning of Mixtures of Gaussians

#6202 · Hassan Ashtiani, Mahbod Majid, Shyam Narayanan

DataStealing: Steal Data from Diffusion Models in Federated Learning with Multiple Trojans

#6203 · Yuan Gan, Jiaxu Miao, Yi Yang

Exactly Minimax-Optimal Locally Differentially Private Sampling

#6204 · Hyun-Young Park, Shahab Asoodeh, Si-Hyeon Lee

LLM Dataset Inference: Did you train on my dataset?

#6205 · Pratyush Maini, Hengrui Jia, Nicolas Papernot, Adam Dziedzic

Differential Privacy in Scalable General Kernel Learning via $K$-means Nystr{\"o}m Random Features

#6206 · Bonwoo Lee, Jeongyoun Ahn, Cheolwoo Park

A Huber Loss Minimization Approach to Mean Estimation under User-level Differential Privacy

#6207 · Puning Zhao, Lifeng LAI, Li Shen, Qingming Li, Jiafei Wu, Zhe Liu

Nearly Tight Black-Box Auditing of Differentially Private Machine Learning

#6208 · Meenatchi Sundaram Muthu Selva Annamalai, Emiliano De Cristofaro

Prior-itizing Privacy: A Bayesian Approach to Setting the Privacy Budget in Differential Privacy

#6209 · Zeki Kazan, Jerome Reiter

Reimagining Mutual Information for Enhanced Defense against Data Leakage in Collaborative Inference

#6210 · Lin Duan, Jingwei Sun, Jinyuan Jia, Yiran Chen, Maria Gorlatova

Enhancing Robustness in Deep Reinforcement Learning: A Lyapunov Exponent Approach

#6300 · Rory Young, Nicolas Pugeault

Neural Combinatorial Optimization for Robust Routing Problem with Uncertain Travel Times

#6301 · Pei Xiao, Zizhen Zhang, Jinbiao Chen, Jiahai Wang, Zhenzhen Zhang

Genetic-guided GFlowNets for Sample Efficient Molecular Optimization

#6302 · Hyeonah Kim, Minsu Kim, Sanghyeok Choi, Jinkyoo Park

Off-Policy Selection for Initiating Human-Centric Experimental Design

#6303 · Ge Gao, Xi Yang, Qitong Gao, Song Ju, Miroslav Pajic, Min Chi

Span-Based Optimal Sample Complexity for Weakly Communicating and General Average Reward MDPs

#6304 · Matthew Zurek, Yudong Chen

Constrained Latent Action Policies for Model-Based Offline Reinforcement Learning

#6305 · Marvin Alles, Philip Becker-Ehmck, Patrick van der Smagt, Maximilian Karl

GTA: Generative Trajectory Augmentation with Guidance for Offline Reinforcement Learning

#6306 · Jaewoo Lee, Sujin Yun, Taeyoung Yun, Jinkyoo Park

Towards an Information Theoretic Framework of Context-Based Offline Meta-Reinforcement Learning

#6307 · Lanqing Li, Hai Zhang, Xinyu Zhang, Shatong Zhu, Yang YU, Junqiao Zhao, Pheng-Ann Heng

An Offline Adaptation Framework for Constrained Multi-Objective Reinforcement Learning

#6308 · Qian Lin, Zongkai Liu, Danying Mo, Chao Yu

On Differentially Private U Statistics

#6309 · Kamalika Chaudhuri, Po-Ling Loh, Shourya Pandey, Purnamrita Sarkar

HEPrune: Fast Private Training of Deep Neural Networks With Encrypted Data Pruning

#6310 · Yancheng Zhang, Mengxin Zheng, Yuzhang Shang, Xun Chen, Qian Lou

Enabling Adaptive Agent Training in Open-Ended Simulators by Targeting Diversity

#6400 · Robby Costales, Stefanos Nikolaidis

Improving Deep Reinforcement Learning by Reducing the Chain Effect of Value and Policy Churn

#6401 · Hongyao Tang, Glen Berseth

Multi-turn Reinforcement Learning with Preference Human Feedback

#6402 · Lior Shani, Aviv Rosenberg, Asaf Cassel, Oran Lang, Daniele Calandriello, Avital Zipori, Hila Noga, Orgad Keller, Bilal Piot, Idan Szpektor, Avinatan Hassidim, Yossi Matias, Remi Munos

Federated Ensemble-Directed Offline Reinforcement Learning

#6403 · Desik Rengarajan, Nitin Ragothaman, Dileep Kalathil, Srinivas Shakkottai

Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning

#6404 · Zhishuai Liu, Pan Xu

Local Linearity: the Key for No-regret Reinforcement Learning in Continuous MDPs

#6405 · Davide Maran, Alberto Maria Metelli, Matteo Papini, Marcello Restelli

Rethinking Model-based, Policy-based, and Value-based Reinforcement Learning via the Lens of Representation Complexity

#6406 · Guhao Feng, Han Zhong

JaxMARL: Multi-Agent RL Environments and Algorithms in JAX

#6407 · Alexander Rutherford, Benjamin Ellis, Matteo Gallici, Jonathan Cook, Andrei Lupu, Garðar Ingvarsson Juto, Timon Willi, Ravi Hammond, Akbir Khan, Christian Schroeder de Witt, Alexandra Souly, Saptarashmi Bandyopadhyay, Mikayel Samvelyan, Minqi Jiang, Robert Lange, Shimon Whiteson, Bruno Lacerda, Nick Hawes, Tim Rocktäschel, Chris Lu, Jakob Foerster

WFCRL: A Multi-Agent Reinforcement Learning Benchmark for Wind Farm Control

#6408 · Claire Bizon Monroc, Ana Busic, Donatien Dubuc, Jiamin Zhu

Kaleidoscope: Learnable Masks for Heterogeneous Multi-agent Reinforcement Learning

#6409 · Xinran Li, Ling Pan, Jun Zhang

Learning to Balance Altruism and Self-interest Based on Empathy in Mixed-Motive Games

#6410 · Fanqi Kong, Yizhe Huang, Song-Chun Zhu, Siyuan Qi, Xue Feng

A Method for Evaluating Hyperparameter Sensitivity in Reinforcement Learning

#6500 · Jacob Adkins, Michael Bowling, Adam White

Last-Iterate Global Convergence of Policy Gradients for Constrained Reinforcement Learning

#6501 · Alessandro Montenegro, Marco Mussi, Matteo Papini, Alberto Maria Metelli

Policy Mirror Descent with Lookahead

#6502 · Kimon Protopapas, Anas Barakat

SeeA*: Efficient Exploration-Enhanced A* Search by Selective Sampling

#6503 · Dengwei Zhao, Shikui Tu, Lei Xu

SkiLD: Unsupervised Skill Discovery Guided by Factor Interactions

#6504 · Zizhao Wang, Jiaheng Hu, Caleb Chuck, Stephen Chen, Roberto Martín-Martín, Amy Zhang, Scott Niekum, Peter Stone

Belief-State Query Policies for User-Aligned Planning under Partial Observability

#6505 · Daniel Bramblett, Siddharth Srivastava

Parallelizing Model-based Reinforcement Learning Over the Sequence Length

#6506 · Zirui Wang, Yue DENG, Junfeng Long, Yin Zhang

Inference via Interpolation: Contrastive Representations Provably Enable Planning and Inference

#6507 · Benjamin Eysenbach, Vivek Myers, Ruslan Salakhutdinov, Sergey Levine

Reward Machines for Deep RL in Noisy and Uncertain Environments

#6509 · Andrew Li, Zizhao Chen, Toryn Klassen, Pashootan Vaezipoor, Rodrigo Toro Icarte, Sheila McIlraith

Learning to Cooperate with Humans using Generative Agents

#6510 · Yancheng Liang, Daphne Chen, Abhishek Gupta, Simon Du, Natasha Jaques

Exploring the Edges of Latent State Clusters for Goal-Conditioned Reinforcement Learning

#6600 · Yuanlin Duan, Guofeng Cui, He Zhu

RL-GPT: Integrating Reinforcement Learning and Code-as-policy

#6601 · Shaoteng Liu, Haoqi Yuan, Minda Hu, Yanwei Li, Yukang Chen, Shu Liu, Zongqing Lu, Jiaya Jia

Rethinking Inverse Reinforcement Learning: from Data Alignment to Task Alignment

#6603 · Weichao Zhou, Wenchao Li

Learning World Models for Unconstrained Goal Navigation

#6604 · Yuanlin Duan, Wensen Mao, He Zhu

Speculative Monte-Carlo Tree Search

#6605 · Scott Cheng, Mahmut T Kandemir, Ding-Yong Hong

In-Trajectory Inverse Reinforcement Learning: Learn Incrementally From An Ongoing Trajectory

#6606 · Shicheng Liu, Minghui Zhu

Focus On What Matters: Separated Models For Visual-Based RL Generalization

#6607 · Di Zhang, Bowen Lv, Hai Zhang, Feifan Yang, Junqiao Zhao, Hang Yu, Chang Huang, Hongtu Zhou, Chen Ye, changjun jiang

Multi-Reward Best Policy Identification

#6608 · Alessio Russo, Filippo Vannella

Externally Valid Policy Evaluation from Randomized Trials Using Additional Observational Data

#6609 · Sofia Ek, Dave Zachariah

Boosted Conformal Prediction Intervals

#6610 · Ran Xie, Rina Barber, Emmanuel Candes

Initializing Services in Interactive ML Systems for Diverse Users

#6611 · Avinandan Bose, Mihaela Curmei, Daniel Jiang, Jamie Morgenstern, Sarah Dean, Lillian Ratliff, Maryam Fazel

Adaptive Sampling for Efficient Softmax Approximation

#6612 · Tavor Baharav, Ryan Kang, Colin Sullivan, Mo Tiwari, Eric Luxenberg, David Tse, Mert Pilanci

Contracting with a Learning Agent

#6700 · Guru Guruganesh, Yoav Kolumbus, Jon Schneider, Inbal Talgam-Cohen, Emmanouil-Vasileios Vlatakis-Gkaragkounis, Joshua Wang, S. Weinberg

Efficiency of the First-Price Auction in the Autobidding World

#6701 · Yuan Deng, Jieming Mao, Vahab Mirrokni, Hanrui Zhang, Song Zuo

Aggregating Quantitative Relative Judgments: From Social Choice to Ranking Prediction

#6702 · Yixuan Xu, Hanrui Zhang, Yu Cheng, Vincent Conitzer

Maximizing utility in multi-agent environments by anticipating the behavior of other learners

#6703 · Angelos Assos, Yuval Dagan, Constantinos Daskalakis

IODA: Instance-Guided One-shot Domain Adaptation for Super-Resolution

#6704 · Zaizuo Tang, Yu-Bin Yang

TALoS: Enhancing Semantic Scene Completion via Test-time Adaptation on the Line of Sight

#6705 · Hyun-Kurl Jang, Jihun Kim, Hyeokjun Kweon, Kuk-Jin Yoon

Cloud Object Detector Adaptation by Integrating Different Source Knowledge

#6706 · Shuaifeng Li, Mao Ye, Lihua Zhou, Nianxin Li, Siying Xiao, Song Tang, Xiatian Zhu

CLIPCEIL: Domain Generalization through CLIP via Channel rEfinement and Image-text aLignment

#6707 · Xi Yu, Shinjae Yoo, Yuewei Lin

Safe Time-Varying Optimization based on Gaussian Processes with Spatio-Temporal Kernel

#6708 · Jialin Li, Marta Zagorowska, Giulia De Pasquale, Alisa Rupenyan, John Lygeros

Batched Energy-Entropy acquisition for Bayesian Optimization

#6709 · Felix Teufel, Carsten Stahlhut, Jesper Ferkinghoff-Borg

Optimal Design for Human Preference Elicitation

#6710 · Subhojyoti Mukherjee, Anusha Lalitha, Kousha Kalantari, Aniket Anand Deshmukh, Ge Liu, Yifei Ma, Branislav Kveton

Is Knowledge Power? On the (Im)possibility of Learning from Strategic Interactions

#6800 · Nivasini Ananthakrishnan, Nika Haghtalab, Chara Podimata, Kunhe Yang

Putting Gale & Shapley to Work: Guaranteeing Stability Through Learning

#6801 · Hadi Hosseini, Sanjukta Roy, Duohan Zhang

Mechanism design augmented with output advice

#6802 · George Christodoulou, Alkmini Sgouritsa, Ioannis Vlachos

Autobidder's Dilemma: Why More Sophisticated Autobidders Lead to Worse Auction Efficiency

#6803 · Yuan Deng, Jieming Mao, Vahab Mirrokni, Hanrui Zhang, Song Zuo

Polynomial-Time Computation of Exact $\Phi$-Equilibria in Polyhedral Games

#6804 · Gabriele Farina, Charilaos Pipis

Dueling over Dessert, Mastering the Art of Repeated Cake Cutting

#6805 · Simina Branzei, MohammadTaghi Hajiaghayi, Reed Phillips, Suho Shin, Kun Wang

Policy Aggregation

#6806 · Parand A. Alamdari, Soroush Ebadian, Ariel Procaccia

A theoretical case-study of Scalable Oversight in Hierarchical Reinforcement Learning

#6807 · Tom Yan, Zachary Lipton

Improved Regret of Linear Ensemble Sampling

#6808 · Harin Lee, Min-hwan Oh

Occupancy-based Policy Gradient: Estimation, Convergence, and Optimality

#6809 · Audrey Huang, Nan Jiang

MetaCURL: Non-stationary Concave Utility Reinforcement Learning

#6810 · Bianca Marin Moreno, Margaux Brégère, Pierre Gaillard, Nadia Oudjane

Nearly Optimal Approximation of Matrix Functions by the Lanczos Method

#6900 · Noah Amsel, Tyler Chen, Anne Greenbaum, Cameron Musco, Christopher Musco

Adaptive Experimentation When You Can't Experiment

#6901 · Yao Zhao, Kwang-Sung Jun, Tanner Fiez, Lalit Jain

Learning from Noisy Labels via Conditional Distributionally Robust Optimization

#6902 · Hui GUO, Grace Yi, Boyu Wang

Generalized Fast Exact Conformalization

#6903 · Diyang Li

Off-policy estimation with adaptively collected data: the power of online learning

#6904 · Jeonghwan Lee, Cong Ma

Progressive Entropic Optimal Transport Solvers

#6905 · Parnian Kassraie, Aram-Alexandre Pooladian, Michal Klein, James Thornton, Jonathan Niles-Weed, Marco Cuturi

Aligning Embeddings and Geometric Random Graphs: Informational Results and Computational Approaches for the Procrustes-Wasserstein Problem

#6906 · Mathieu Even, Luca Ganassali, Jakob Maier, Laurent Massoulié

Corruption-Robust Linear Bandits: Minimax Optimality and Gap-Dependent Misspecification

#6907 · Haolin Liu, Artin Tajdini, Andrew Wagenmaker, Chen-Yu Wei

Reinforcement Learning with Lookahead Information

#6908 · Nadav Merlis

Statistical Efficiency of Distributional Temporal Difference Learning

#6909 · Yang Peng, Liangyu Zhang, Zhihua Zhang

Balancing Context Length and Mixing Times for Reinforcement Learning at Scale

#6910 · Matthew Riemer, Khimya Khetarpal, Janarthanan Rajendran, Sarath Chandar

Learning-Augmented Approximation Algorithms for Maximum Cut and Related Problems

#7000 · Vincent Cohen-Addad, Tommaso d’Orsi, Anupam Gupta, Euiwoong Lee, Debmalya Panigrahi

The Space Complexity of Approximating Logistic Loss

#7001 · Gregory Dexter, Petros Drineas, Rajiv Khanna

MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark

#7002 · Yubo Wang, Xueguang Ma, Ge Zhang, Yuansheng Ni, Abhranil Chandra, Shiguang Guo, Weiming Ren, Aaran Arulraj, Xuan He, Ziyan Jiang, Tianle Li, Max KU, Kai Wang, Alex Zhuang, Rongqi Fan, Xiang Yue, Wenhu Chen

Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations

#7003 · Hao Chen, Ankit Shah, Jindong Wang, Ran Tao, Yidong Wang, Xiang Li, Xing Xie, Masashi Sugiyama, Rita Singh, Bhiksha Raj

FineStyle: Fine-grained Controllable Style Personalization for Text-to-image Models

#7004 · Gong Zhang, Kihyuk Sohn, Meera Hahn, Humphrey Shi, Irfan Essa

B-ary Tree Push-Pull Method is Provably Efficient for Distributed Learning on Heterogeneous Data

#7005 · Runze You, Shi Pu

Unveiling Induction Heads: Provable Training Dynamics and Feature Learning in Transformers

#7006 · Siyu Chen, Heejune Sheen, Tianhao Wang, Zhuoran Yang

Adaptable Logical Control for Large Language Models

#7007 · Honghua Zhang, Po-Nien Kung, Masahiro Yoshida, Guy Van den Broeck, Nanyun Peng

The Sample-Communication Complexity Trade-off in Federated Q-Learning

#7008 · Sudeep Salgia, Yuejie Chi

Boosting Semi-Supervised Scene Text Recognition via Viewing and Summarizing

#7009 · Yadong Qu, Yuxin Wang, Bangbang Zhou, Zixiao Wang, Hongtao Xie, Yongdong Zhang

Autoformalize Mathematical Statements by Symbolic Equivalence and Semantic Consistency

#7010 · Zenan Li, Yifan Wu, Zhaoyu Li, Xinming Wei, Xian Zhang, Fan Yang, Xiaoxing Ma

Model Collapse Demystified: The Case of Regression

#7100 · Elvis Dohmatob, Yunzhen Feng, Julia Kempe

Transformers Represent Belief State Geometry in their Residual Stream

#7101 · Adam Shai, Paul Riechers, Lucas Teixeira, Alexander Oldenziel, Sarah Marzen

Spiking Transformer with Experts Mixture

#7102 · Zhaokun Zhou, Yijie Lu, Yanhao Jia, Kaiwei Che, Jun Niu, Liwei Huang, Xinyu Shi, Yuesheng Zhu, Guoqi Li, Zhaofei Yu, Li Yuan

MILP-StuDio: MILP Instance Generation via Block Structure Decomposition

#7103 · Haoyang Liu, Jie Wang, Wanbo Zhang, Zijie Geng, Yufei Kuang, Xijun Li, Bin Li, Yongdong Zhang, Feng Wu

SaulLM-54B & SaulLM-141B: Scaling Up Domain Adaptation for the Legal Domain

#7104 · Pierre Colombo, Telmo Pessoa Pires, Malik Boudiaf, Rui Melo, Gabriel Hautreux, Etienne Malaboeuf, Johanne Charpentier, Dominic Culver, Michael Desa

VLG-CBM: Training Concept Bottleneck Models with Vision-Language Guidance

#7105 · Divyansh Srivastava, Ge Yan, Lily Weng

Last-Iterate Convergence for Generalized Frank-Wolfe in Monotone Variational Inequalities

#7106 · Zaiwei Chen, Eric Mazumdar

Matching the Statistical Query Lower Bound for $k$-Sparse Parity Problems with Sign Stochastic Gradient Descent

#7107 · Yiwen Kou, Zixiang Chen, Quanquan Gu, Sham Kakade

Policy Learning from Tutorial Books via Understanding, Rehearsing and Introspecting

#7108 · Xiong-Hui Chen, Ziyan Wang, Yali Du, Shengyi Jiang, Meng Fang, Yang Yu, Jun Wang

FOOGD: Federated Collaboration for Both Out-of-distribution Generalization and Detection

#7109 · Xinting Liao, Weiming Liu, Pengyang Zhou, Fengyuan Yu, Jiahe Xu, Jun Wang, Wenjie Wang, Chaochao Chen, Xiaolin Zheng

Grokking of Implicit Reasoning in Transformers: A Mechanistic Journey to the Edge of Generalization

#7110 · Boshi Wang, Xiang Yue, Yu Su, Huan Sun

OW-VISCapTor: Abstractors for Open-World Video Instance Segmentation and Captioning

#7200 · Anwesa Choudhuri, Girish Chowdhary, Alex Schwing

Distributional regression: CRPS-error bounds for model fitting, model selection and convex aggregation

#7201 · Dombry Clement, Ahmed Zaoui

Improving Generalization and Convergence by Enhancing Implicit Regularization

#7202 · Mingze Wang, Jinbo Wang, Haotian He, Zilin Wang, Guanhua Huang, Feiyu Xiong, Zhiyu li, Weinan E, Lei Wu

Wasserstein Gradient Boosting: A Framework for Distribution-Valued Supervised Learning

#7203 · Takuo Matsubara

On Weak Regret Analysis for Dueling Bandits

#7204 · El Mehdi Saad, Alexandra Carpentier, Tomáš Kocák, Nicolas Verzelen

Nonparametric Classification on Low Dimensional Manifolds using Overparameterized Convolutional Residual Networks

#7205 · Zixuan Zhang, Kaiqi Zhang, Minshuo Chen, Yuma Takeda, Mengdi Wang, Tuo Zhao, Yu-Xiang Wang

Sparsity-Agnostic Linear Bandits with Adaptive Adversaries

#7206 · Tianyuan Jin, Kyoungseok Jang, Nicolò Cesa-Bianchi

DiffPO: A causal diffusion model for learning distributions of potential outcomes

#7207 · Yuchen Ma, Valentyn Melnychuk, Jonas Schweisthal, Stefan Feuerriegel

VisionLLM v2: An End-to-End Generalist Multimodal Large Language Model for Hundreds of Vision-Language Tasks

#7208 · Jiannan Wu, Muyan Zhong, Sen Xing, Zeqiang Lai, Zhaoyang Liu, Zhe Chen, Wenhai Wang, Xizhou Zhu, Lewei Lu, Tong Lu, Ping Luo, Yu Qiao, Jifeng Dai

Self-playing Adversarial Language Game Enhances LLM Reasoning

#7209 · Pengyu Cheng, Tianhao Hu, Han Xu, Zhisong Zhang, Yong Dai, Lei Han, nan du, Xiaolong Li

Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Generation

#7210 · Guillaume Huguet, James Vuckovic, Kilian FATRAS, Eric Thibodeau-Laufer, Pablo Lemos, Riashat Islam, Chenghao Liu, Jarrid Rector-Brooks, Tara Akhound-Sadegh, Michael Bronstein, Alexander Tong, Joey Bose

Stochastic Optimal Control Matching

#7304 · Carles Domingo i Enrich, Jiequn Han, Brandon Amos, Joan Bruna, Ricky T. Q. Chen

Unified Generative and Discriminative Training for Multi-modal Large Language Models

#7305 · Wei Chow, Juncheng Li, Qifan Yu, Kaihang Pan, Hao Fei, Zhiqi Ge, Shuaiyang, Siliang Tang, Hanwang Zhang, QIANRU SUN

Low Precision Local Training is Enough for Federated Learning

#7306 · Zhiwei Li, Yiqiu LI, Binbin Lin, Zhongming Jin, Weizhong Zhang

Generalized Eigenvalue Problems with Generative Priors

#7307 · Zhaoqiang Liu, Wen Li, Junren Chen

Entity Alignment with Noisy Annotations from Large Language Models

#7308 · CHEN SHENGYUAN, Qinggang Zhang, Junnan Dong, Wen Hua, Qing Li, Xiao Huang

CAT: Coordinating Anatomical-Textual Prompts for Multi-Organ and Tumor Segmentation

#7309 · Zhongzhen Huang, Yankai Jiang, Rongzhao Zhang, Shaoting Zhang, Xiaofan Zhang