Paperjam

The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models

#5106 · Hannah Rose Kirk, Alexander Whitefield, Paul Rottger, Andrew M. Bean, Katerina Margatina, Rafael Mosquera-Gomez, Juan Ciro, Max Bartolo, Adina Williams, He He, Bertie Vidgen, Scott Hale

UltraEdit: Instruction-based Fine-Grained Image Editing at Scale

#5107 · Haozhe Zhao, Xiaojian (Shawn) Ma, Liang Chen, Shuzheng Si, Rujie Wu, Kaikai An, Peiyu Yu, Minjia Zhang, Qing Li, Baobao Chang

A Large-Scale Human-Centric Benchmark for Referring Expression Comprehension in the LMM Era

#5108 · Fangyun Wei, Jinjing Zhao, Kun Yan, Hongyang Zhang, Chang Xu

Cooperation, Competition, and Maliciousness: LLM-Stakeholders Interactive Negotiation

#5109 · Sahar Abdelnabi, Amr Gomaa, Sarath Sivaprasad, Lea Schönherr, Mario Fritz

Muharaf: Manuscripts of Handwritten Arabic Dataset for Cursive Text Recognition

#5110 · Mehreen Saeed, Adrian Chan, Anupam Mijar, joseph Moukarzel, Gerges Habchi, Carlos Younes, amin elias, Chau-Wai Wong, Akram Khater

SHDocs: A dataset, benchmark, and method to efficiently generate high-quality, real-world specular highlight data with near-perfect alignment

#5200 · Jovin Leong, Koa Di, Benjamin Cham, Shaun Heng

GC-Bench: An Open and Unified Benchmark for Graph Condensation

#5201 · Qingyun Sun, Ziying Chen, Beining Yang, Cheng Ji, Xingcheng Fu, Sheng Zhou, Hao Peng, Jianxin Li, Philip S Yu

Arctique: An artificial histopathological dataset unifying realism and controllability for uncertainty quantification

#5202 · Jannik Franzen, Claudia Winklmayr, Vanessa Emanuela Guarino, Christoph Karg, Xiaoyan Yu, Nora Koreuber, Jan Albrecht, Philip Bischoff, Dagmar Kainmueller

SolarCube: An Integrative Benchmark Dataset Harnessing Satellite and In-situ Observations for Large-scale Solar Energy Forecasting

#5203 · Ruohan Li, Yiqun Xie, Xiaowei Jia, Dongdong Wang, Yanhua Li, Yingxue Zhang, Zhihao Wang, Zhili Li

MmCows: A Multimodal Dataset for Dairy Cattle Monitoring

#5204 · Hien Vu, Omkar Chandrakant Prabhune, Unmesh Raskar, Dimuth Panditharatne, Hanwook Chung, Christopher Choi, Younghyun Kim

Evaluating Large Vision-and-Language Models on Children's Mathematical Olympiads

#5205 · Anoop Cherian, Kuan-Chuan Peng, Suhas Lohit, Joanna Matthiesen, Kevin Smith, Josh Tenenbaum

Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation?

#5206 · Pedro R. A. S. Bassi, Wenxuan Li, Yucheng Tang, Fabian Isensee, Zifu Wang, Jieneng Chen, Yu-Cheng Chou, Tassilo Wald, Constantin Ulrich, Michael Baumgartner, Saikat Roy, Klaus Maier-Hein, Paul Jaeger, Yiwen Ye, Yutong Xie, Jianpeng Zhang, Ziyang Chen, Yong Xia, Yannick Kirchhoff, Maximilian R. Rokuss, Pengcheng Shi, Ting Ma, Yuxin Du, Fan BAI, Tiejun Huang, Bo Zhao, Zhaohu Xing, Lei Zhu, Saumya Gupta, Haonan Wang, Xiaomeng Li, Ziyan Huang, Jin Ye, Junjun He, Yousef Sadegheih, Afshin Bozorgpour, Pratibha Kumari, Reza Azad, Dorit Merhof, Hanxue Gu, Haoyu Dong, Jichen Yang, Maciej Mazurowski, Linshan Wu, Jia-Xin Zhuang, Hao CHEN, Holger Roth, Daguang Xu, Matthew Blaschko, Sergio Decherchi, Andrea Cavalli, Alan Yuille, Zongwei Zhou

DetectEval: Benchmarking LLM-Generated Text Detection in Real-World Scenarios

#5207 · Junchao Wu, Runzhe Zhan, Derek Wong, Shu Yang, Xinyi Yang, Yulin Yuan, Lidia Chao

VERIFIED: A Video Corpus Moment Retrieval Benchmark for Fine-Grained Video Understanding

#5208 · Houlun Chen, Xin Wang, Hong Chen, Zeyang Zhang, Wei Feng, Bin Huang, Jia Jia, Wenwu Zhu

DivSafe: Evaluating the Generalization of LLM Safety Training Across Diverse Tasks and Prompt Types

#5209 · Yutao Mou, Shikun Zhang, Wei Ye

CableInspect-AD: An Expert-Annotated Anomaly Detection Dataset

#5210 · Akshatha Arodi, Margaux Luck, Jean-Luc Bedwani, Aldo Zaimi, Ge Li, Nicolas Pouliot, Julien Beaudry, Gaetan Marceau Caron

Semi-Truths: A Large-Scale Dataset for Testing Robustness of AI-Generated Image Detectors

#5211 · Anisha Pal, Julia Kruk, Mansi Phute, Manognya Bhattaram, Diyi Yang, Duen Horng Chau, Judy Hoffman

DrivingDojo Dataset: Advancing Interactive and Knowledge-Enriched Driving World Model

#5300 · Yuqi Wang, Ke Cheng, Jiawei He, Qitai Wang, Hengchen Dai, Yuntao Chen, Fei Xia, ZHAO-XIANG ZHANG

Game-Traversal-Benchmark: Evaluating Planning Abilities Of Large Language Models Via Traversing 2D Game Maps

#5301 · Muhammad Umair Nasir, Steven James, Julian Togelius

DART-Eval: A Comprehensive DNA Language Model Evaluation Benchmark on Regulatory DNA

#5302 · Aman Patel, Arpita Singhal, Austin Wang, Anusri Pampari, Maya Kasowski, Anshul Kundaje

Benchmarking Generative Models on Computational Thinking Tests in Elementary Visual Programming

#5303 · Victor-Alexandru Pădurean, Adish Singla

AllClear: A Comprehensive Dataset and Benchmark for Cloud Removal in Satellite Imagery

#5304 · Hangyu Zhou, Chia-Hsiang Kao, Cheng Perng Phoo, Utkarsh Mall, Bharath Hariharan, Kavita Bala

Multi-Chain Graphs of Graphs: A New Paradigm in Blockchain Dataset

#5305 · Bingqiao Luo, Zhen Zhang, Qian Wang, Bingsheng He

USCILab3D: A Large-scale, Long-term, Semantically Annotated Outdoor Dataset

#5306 · Kiran Lekkala, Henghui Bao, Peixu Cai, Wei Lim, Chen Liu, Laurent Itti

FinBen: An Holistic Financial Benchmark for Large Language Models

#5307 · Qianqian Xie, Weiguang Han, Zhengyu Chen, Ruoyu Xiang, Xiao Zhang, Yueru He, Mengxi Xiao, Dong Li, Yongfu Dai, Duanyu Feng, Yijing Xu, Haoqiang Kang, Ziyan Kuang, Chenhan Yuan, Kailai Yang, Zheheng Luo, Tianlin Zhang, Zhiwei Liu, GUOJUN XIONG, Zhiyang Deng, Yuechen Jiang, Zhiyuan Yao, Haohang Li, Yangyang Yu, Gang Hu, Huang Jiajia, Xiaoyang Liu, Alejandro Lopez-Lira, Benyou Wang, Yanzhao Lai, Hao Wang, Min Peng, Sophia Ananiadou, Jimin Huang

RedPajama: an Open Dataset for Training Large Language Models

#5308 · Maurice Weber, Dan Fu, Quentin Anthony, Yonatan Oren, Shane Adams, Anton Alexandrov, Xiaozhong Lyu, Huu Nguyen, Xiaozhe Yao, Virginia Adams, Ben Athiwaratkun, Rahul Chalamala, Kezhen Chen, Max Ryabinin, Tri Dao, Percy Liang, Christopher Ré, Irina Rish, Ce Zhang

CryoBench: Datasets and Benchmarks for Heterogeneous Cryo-EM Reconstruction

#5309 · Minkyu Jeon, Rishwanth Raghu, Miro Astore, Geoffrey Woollard, J. Feathers, Alkin Kaz, Sonya Hanson, Pilar Cossio, Ellen Zhong

A multi-UAV dataset for multi-object tracking and re-identification of wild antelopes

#5310 · Hemal Naik, Junran Yang, Dipin Das, Margaret Crofoot, Akanksha Rathore, Vivek Hari Sridhar

Advancing Video Anomaly Detection: A Concise Review and a New Dataset

#5311 · Liyun Zhu, Lei Wang, Arjun Raj, Tom Gedeon, Chen Chen

Einsum Benchmark: Enabling the Development of Next-Generation Tensor Execution Engines

#5400 · Mark Blacher, Christoph Staudt, Julien Klaus, Maurice Wenig, Niklas Merk, Alexander Breuer, Max Engel, Sören Laue, Joachim Giesen

BABILong: Testing the Limits of LLMs with Long Context Reasoning-in-a-Haystack

#5401 · Yury Kuratov, Aydar Bulatov, Petr Anokhin, Ivan Rodkin, Dmitry Sorokin, Artyom Sorokin, Mikhail Burtsev

HW-GPT-Bench: Hardware-Aware Architecture Benchmark for Language Models

#5402 · Rhea Sukthanker, Arber Zela, Benedikt Staffler, Aaron Klein, Lennart Purucker, Jörg Franke, Frank Hutter

A Benchmark Suite for Evaluating Neural Mutual Information Estimators on Unstructured Datasets

#5403 · Kyungeun Lee, Wonjong Rhee

MMScan: A Multi-Modal 3D Scene Dataset with Hierarchical Grounded Language Annotations

#5404 · Ruiyuan Lyu, Tai WANG, Jingli Lin, Shuaiyang, Xiaohan Mao, Yilun Chen, Runsen Xu, Haifeng Huang, Chenming Zhu, Dahua Lin, Jiangmiao Pang

GTSinger: A Global Multi-Technique Singing Corpus with Realistic Music Scores for All Singing Tasks

#5405 · Yu Zhang, Changhao Pan, Wenxiang Guo, Ruiqi Li, Zhiyuan Zhu, Jialei Wang, Wenhao Xu, Jingyu Lu, Zhiqing Hong, Chuxin Wang, Lichao Zhang, Jinzheng He, Ziyue Jiang, Yuxin Chen, Chen Yang, Jiecheng Zhou, Xinyu Cheng, Zhou Zhao

SWT-Bench: Testing and Validating Real-World Bug-Fixes with Code Agents

#5406 · Niels Mündler, Mark Müller, Jingxuan He, Martin Vechev

Animal-Bench: Benchmarking Multimodal Video Models for Animal-centric Video Understanding

#5407 · Yinuo Jing, Ruxu Zhang, Kongming Liang, Yongxiang Li, Zhongjiang He, Zhanyu Ma, Jun Guo

Reproducibility study of FairAC

#5408 · Gijs de Jong, Macha Meijer, Derck Prinzhorn, Harold Ruiter

ABCFair: an Adaptable Benchmark approach for Comparing Fairness Methods

#5409 · MaryBeth Defrance, Maarten Buyl, Tijl De Bie

FairJob: A Real-World Dataset for Fairness in Online Systems

#5410 · Mariia Vladimirova, Federico Pavone, Eustache Diemert

Harnessing Multiple Correlated Networks for Exact Community Recovery

#5500 · Miklos Z. Racz, Jifan Zhang

Replicability in Learning: Geometric Partitions and KKM-Sperner Lemma

#5501 · Jason Vander Woude, Peter Dixon, A. Pavan, Jamie Radcliffe, N. V. Vinodchandran

OxonFair: A Flexible Toolkit for Algorithmic Fairness

#5502 · Eoin Delaney, Zihao Fu, Sandra Wachter, Brent Mittelstadt, Chris Russell

Decision-Making Behavior Evaluation Framework for LLMs under Uncertain Context

#5503 · Jingru (Jessica) Jia, Zehua Yuan, Junhao Pan, Paul McNamara, Deming Chen

Fair Secretaries with Unfair Predictions

#5504 · Eric Balkanski, Will Ma, Andreas Maggiori

Monoculture in Matching Markets

#5505 · Kenny Peng, Nikhil Garg

Mitigating Spurious Correlations via Disagreement Probability

#5506 · Hyeonggeun Han, Sehwan Kim, Hyungjun Joo, Sangwoo Hong, Jungwoo Lee

Free-Rider and Conflict Aware Collaboration Formation for Cross-Silo Federated Learning

#5507 · Mengmeng Chen, Xiaohu Wu, Xiaoli Tang, Tiantian He, Yew Soon Ong, QIQI LIU, Qicheng Lao, Han Yu

Perceptual Fairness in Image Restoration

#5508 · Guy Ohayon, Michael Elad, Tomer Michaeli

Mitigating Biases in Blackbox Feature Extractors for Image Classification Tasks

#5509 · Abhipsa Basu, Saswat Subhajyoti Mallick, Venkatesh Babu R

Theoretical and Empirical Insights into the Origins of Degree Bias in Graph Neural Networks

#5510 · Arjun Subramonian, Jian Kang, Yizhou Sun

Optimal Private and Communication Constraint Distributed Goodness-of-Fit Testing for Discrete Distributions in the Large Sample Regime

#5600 · Lasse Vuursteen

Differentiable Quantum Computing for Large-scale Linear Control

#5601 · Connor Clayton, Jiaqi Leng, Gengzhi Yang, Yi-Ling Qiao, Ming Lin, Xiaodi Wu

Learning from Snapshots of Discrete and Continuous Data Streams

#5602 · Pramith Devulapalli, Steve Hanneke

Active Classification with Few Queries under Misspecification

#5603 · Vasilis Kontonis, Mingchen Ma, Christos Tzamos

On the Comparison between Multi-modal and Single-modal Contrastive Learning

#5604 · Wei Huang, Andi Han, Yongqiang Chen, Yuan Cao, Zhiqiang Xu, Taiji Suzuki

Statistical-Computational Trade-offs for Density Estimation

#5605 · Anders Aamand, Alexandr Andoni, Justin Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal, Haike Xu

A two-scale Complexity Measure for Deep Learning Models

#5606 · Massimiliano Datres, Gian Leonardi, Alessio Figalli, David Sutter

Statistical Estimation in the Spiked Tensor Model via the Quantum Approximate Optimization Algorithm

#5607 · Leo Zhou, Joao Basso, Song Mei

Active Learning of General Halfspaces: Label Queries vs Membership Queries

#5608 · Ilias Diakonikolas, Daniel Kane, Mingchen Ma

Group-wise oracle-efficient algorithms for online multi-group learning

#5609 · Samuel Deng, Jingwen Liu, Daniel Hsu

Efficient Graph Matching for Correlated Stochastic Block Models

#5610 · Shuwen Chai, Miklos Z. Racz

Contextual Multinomial Logit Bandits with General Value Functions

#5700 · Mengxiao Zhang, Haipeng Luo

No-Regret Learning for Fair Multi-Agent Social Welfare Optimization

#5701 · Mengxiao Zhang, Ramiro Deo-Campo Vuong, Haipeng Luo

Improved Analysis for Bandit Learning in Matching Markets

#5702 · Fang Kong, Zilong Wang, Shuai Li

The Many Faces of Optimal Weak-to-Strong Learning

#5703 · Mikael Møller Høgsgaard, Kasper Green Larsen, Markus Engelund Mathiasen

Information-theoretic Generalization Analysis for Expected Calibration Error

#5704 · Futoshi Futami, Masahiro Fujisawa

Training Dynamics of Transformers to Recognize Word Co-occurrence via Gradient Flow Analysis

#5705 · Hongru Yang, Bhavya Kailkhura, Zhangyang "Atlas" Wang, Yingbin Liang

Exploring the Precise Dynamics of Single-Layer GAN Models: Leveraging Multi-Feature Discriminators for High-Dimensional Subspace Learning

#5706 · Andrew Bond, Zafer Dogan

A Nearly Optimal and Low-Switching Algorithm for Reinforcement Learning with General Function Approximation

#5707 · Heyang Zhao, Jiafan He, Quanquan Gu

Optimal Parallelization of Boosting

#5708 · Arthur da Cunha, Mikael Møller Høgsgaard, Kasper Green Larsen

Distributed Least Squares in Small Space via Sketching and Bias Reduction

#5709 · Sachin Garg, Kevin Tan, Michal Derezinski

On the Impacts of the Random Initialization in the Neural Tangent Kernel Theory

#5710 · Guhan Chen, Yicheng Li, Qian Lin

Strategic Littlestone Dimension: Improved Bounds on Online Strategic Classification

#5800 · Saba Ahmadi, Kunhe Yang, Hanrui Zhang

Taming Heavy-Tailed Losses in Adversarial Bandits and the Best-of-Both-Worlds Setting

#5801 · Duo Cheng, Xingyu Zhou, Bo Ji

Optimal Multiclass U-Calibration Error and Beyond

#5802 · Haipeng Luo, Spandan Senapati, Vatsal Sharan

On the Minimax Regret for Contextual Linear Bandits and Multi-Armed Bandits with Expert Advice

#5803 · Shinji Ito

Multi-model Ensemble Conformal Prediction in Dynamic Environments

#5804 · Erfan Hajihashemi, Yanning Shen

No-Regret M${}^{\natural}$-Concave Function Maximization: Stochastic Bandit Algorithms and NP-Hardness of Adversarial Full-Information Setting

#5805 · Taihei Oki, Shinsaku Sakaue

Improved learning rates in multi-unit uniform price auctions

#5806 · Marius Potfer, Dorian Baudry, Hugo Richard, Vianney Perchet, Cheng Wan

PRODuctive bandits: Importance Weighting No More

#5807 · Julian Zimmert, Teodor Vanislavov Marinov

A Simple and Adaptive Learning Rate for FTRL in Online Learning with Minimax Regret of $\Theta(T^{2/3})$ and its Application to Best-of-Both-Worlds

#5808 · Taira Tsuchiya, Shinji Ito

Reawakening knowledge: Anticipatory recovery from catastrophic interference via structured training

#5809 · Yanlai Yang, Matt Jones, Michael Mozer, Mengye Ren

Online Weighted Paging with Unknown Weights

#5810 · Orin Levy, Noam Touitou, Aviv Rosenberg

Exact, Tractable Gauss-Newton Optimization in Deep Reversible Architectures Reveal Poor Generalization

#5900 · Davide Buffelli, Jamie McGowan, Wangkun Xu, Alexandru Cioba, Da-shan Shiu, Guillaume Hennequin, Alberto Bernacchia

Nonparametric Instrumental Variable Regression through Stochastic Approximate Gradients

#5901 · Yuri Fonseca, Caio Peixoto, Yuri Saporito

BPQP: A Differentiable Convex Optimization Framework for Efficient End-to-End Learning

#5902 · Jianming Pan, Zeqi Ye, Xiao Yang, Xu Yang, Weiqing Liu, Lewen Wang, Jiang Bian

Non-asymptotic Analysis of Biased Adaptive Stochastic Approximation

#5903 · Sobihan Surendran, Adeline Fermanian, Antoine Godichon-Baggioni, Sylvain Le Corff

Memory-Efficient LLM Training with Online Subspace Descent

#5904 · Kaizhao Liang, Bo Liu, Lizhang Chen, Qiang Liu

Stochastic Extragradient with Flip-Flop Shuffling & Anchoring: Provable Improvements

#5905 · Jiseok Chae, Chulhee Yun, Donghwan Kim

SequentialAttention++ for Block Sparsification: Differentiable Pruning Meets Combinatorial Optimization

#5906 · Taisuke Yasuda, Kyriakos Axiotis, Gang Fu, Mohammadhossein Bateni, Vahab Mirrokni

Exploratory Retrieval-Augmented Planning For Continual Embodied Instruction Following

#5907 · Minjong Yoo, Jinwoo Jang, Wei-Jin Park, Honguk Woo

The Road Less Scheduled

#5908 · Aaron Defazio, Xingyu Yang, Ahmed Khaled, Konstantin Mishchenko, Harsh Mehta, Ashok Cutkosky

Stochastic contextual bandits with graph feedback: from independence number to MAS number

#5909 · Yuxiao Wen, Yanjun Han, Zhengyuan Zhou

F-OAL: Forward-only Online Analytic Learning with Fast Training and Low Memory Footprint in Class Incremental Learning

#5910 · HUIPING ZHUANG, Yuchen Liu, Run He, Kai Tong, Ziqian Zeng, Cen Chen, Yi Wang, Lap-Pui Chau

An Equivalence Between Static and Dynamic Regret Minimization

#5911 · Andrew Jacobsen, Francesco Orabona

Learning diffusion at lightspeed

#6000 · Antonio Terpin, Nicolas Lanzetti, Martín Gadea, Florian Dorfler

Derivatives of Stochastic Gradient Descent in parametric optimization

#6001 · Franck Iutzeler, Edouard Pauwels, Samuel Vaiter

Functionally Constrained Algorithm Solves Convex Simple Bilevel Problem

#6002 · Huaqing Zhang, Lesi Chen, Jing Xu, Jingzhao Zhang

Interpretable Lightweight Transformer via Unrolling of Learned Graph Smoothness Priors

#6003 · VIET HO TAM THUC DO, Parham Eftekhar, Seyed Alireza Hosseini, Gene Cheung, Philip Chou

Adaptive Proximal Gradient Method for Convex Optimization

#6004 · Yura Malitsky, Konstantin Mishchenko

A Simple and Optimal Approach for Universal Online Learning with Gradient Variations

#6005 · Yu-Hu Yan, Peng Zhao, Zhi-Hua Zhou

Promoting Fairness Among Dynamic Agents in Online-Matching Markets under Known Stationary Arrival Distributions

#6006 · Will Ma, Pan Xu

A Combinatorial Algorithm for the Semi-Discrete Optimal Transport Problem

#6007 · Pankaj Agarwal, Sharath Raghvendra, Pouyan Shirzadian, Keegan Yao

Freya PAGE: First Optimal Time Complexity for Large-Scale Nonconvex Finite-Sum Optimization with Heterogeneous Asynchronous Computations

#6008 · Alexander Tyurin, Kaja Gruntkowska, Peter Richtarik

Leveraging partial stragglers within gradient coding

#6009 · Aditya RAMAMOORTHY, Ruoyu Meng, Vrinda Girimaji

LSH-MoE: Communication-efficient MoE Training via Locality-Sensitive Hashing

#6010 · Xiaonan Nie, Liu Qibin, Fangcheng Fu, Shenhan Zhu, Xupeng Miao, Xiaoyang Li, Yang Zhang, Shouda Liu, Bin CUI

SpaFL: Communication-Efficient Federated Learning With Sparse Models And Low Computational Overhead

#6011 · Minsu Kim, Walid Saad, Merouane DEBBAH, Choong Hong

Thinking Forward: Memory-Efficient Federated Finetuning of Language Models

#6012 · Kunjal Panchal, Nisarg Parikh, Sunav Choudhary, Lijun Zhang, Yuriy Brun, Hui Guan

The Collusion of Memory and Nonlinearity in Stochastic Approximation With Constant Stepsize

#6100 · Dongyan Lucy Huo, Yixuan Zhang, Yudong Chen, Qiaomin Xie

Addressing Bias in Online Selection with Limited Budget of Comparisons

#6101 · Ziyad Benomar, Evgenii Chzhen, Nicolas Schreuder, Vianney Perchet

Bayesian Nonparametrics Meets Data-Driven Distributionally Robust Optimization

#6102 · Nicola Bariletto, Nhat Ho

Remove that Square Root: A New Efficient Scale-Invariant Version of AdaGrad

#6103 · Sayantan Choudhury, Nazarii Tupitsa, Nicolas Loizou, Samuel Horváth, Martin Takac, Eduard Gorbunov

Learnability of high-dimensional targets by two-parameter models and gradient flow

#6104 · Dmitry Yarotsky

The Star Geometry of Critic-Based Regularizer Learning

#6105 · Oscar Leong, Eliza O'Reilly, Yong Sheng Soh

Learning to Handle Complex Constraints for Vehicle Routing Problems

#6106 · Jieyi Bi, Yining Ma, Jianan Zhou, Wen Song, Zhiguang Cao, Yaoxin Wu, Jie Zhang

Rethinking the Capacity of Graph Neural Networks for Branching Strategy

#6107 · Ziang Chen, Jialin Liu, Xiaohan Chen, Wang, Wotao Yin

IPM-LSTM: A Learning-Based Interior Point Method for Solving Nonlinear Programs

#6108 · Xi Gao, Jinxin Xiong, Akang Wang, qihong duan, Jiang Xue, Qingjiang Shi

pFedClub: Controllable Heterogeneous Model Aggregation for Personalized Federated Learning

#6109 · Jiaqi Wang, Qi Li, Lingjuan Lyu, Fenglong Ma

Near-Optimal Distributed Minimax Optimization under the Second-Order Similarity

#6110 · Qihao Zhou, Haishan Ye, Luo Luo

Semi-Random Matrix Completion via Flow-Based Adaptive Reweighting

#6200 · Jonathan Kelner, Jerry Li, Allen Liu, Aaron Sidford, Kevin Tian

Guided Trajectory Generation with Diffusion Models for Offline Model-based Optimization

#6201 · Taeyoung Yun, Sujin Yun, Jaewoo Lee, Jinkyoo Park

Multi-Stage Predict+Optimize for (Mixed Integer) Linear Programs

#6202 · Xinyi Hu, Jasper Lee, Jimmy Lee, Peter Stuckey

Automatic Outlier Rectification via Optimal Transport

#6203 · Jose Blanchet, Jiajin Li, Markus Pelger, Greg Zanotti

No Free Lunch Theorem and Black-Box Complexity Analysis for Adversarial Optimisation

#6204 · Per Kristian Lehre, Shishen Lin

Inversion-based Latent Bayesian Optimization

#6205 · Jaewon Chu, Jinyoung Park, Seunghun Lee, Hyunwoo Kim

No-Regret Bandit Exploration based on Soft Tree Ensemble Model

#6206 · Shogo Iwazaki, Shinya Suzumura

Newton Losses: Using Curvature Information for Learning with Differentiable Algorithms

#6207 · Felix Petersen, Christian Borgelt, Tobias Sutter, Hilde Kuehne, Oliver Deussen, Stefano Ermon

Private Algorithms for Stochastic Saddle Points and Variational Inequalities: Beyond Euclidean Geometry

#6208 · Raef Bassily, Cristóbal Guzmán, Michael Menart

Differentially Private Set Representations

#6209 · Sarvar Patel, Giuseppe Persiano, Joon Young Seo, Kevin Yeo

Unified Mechanism-Specific Amplification by Subsampling and Group Privacy Amplification

#6210 · Jan Schuchardt, Mihail Stoian, Arthur Kosmala, Stephan Günnemann

Dual Critic Reinforcement Learning under Partial Observability

#6300 · Jinqiu Li, Enmin Zhao, Tong Wei, Junliang Xing, SHIMING XIANG

Real-Time Recurrent Learning using Trace Units in Reinforcement Learning

#6301 · Esraa Elelimy, Adam White, Michael Bowling, Martha White

Distributional Preference Alignment of LLMs via Optimal Transport

#6302 · Igor Melnyk, Youssef Mroueh, Brian Belgodere, Mattia Rigotti, Apoorva Nitsure, Mikhail Yurochkin, Kristjan Greenewald, Jiri Navratil, Jarret Ross

A Simulation Benchmark for Autonomous Racing with Large-Scale Human Data

#6303 · Adrian Remonda, Nicklas Hansen, Ayoub Raji, Nicola Musiu, Marko Bertogna, Eduardo Veas, Xiaolong Wang

Uncertainty-based Offline Variational Bayesian Reinforcement Learning for Robustness under Diverse Data Corruptions

#6304 · Rui Yang, Jie Wang, Guoping Wu, Bin Li

Entropy-regularized Diffusion Policy with Q-Ensembles for Offline Reinforcement Learning

#6305 · Ruoqi Zhang, Ziwei Luo, Jens Sjölund, Thomas Schön, Per Mattsson

Doubly Mild Generalization for Offline Reinforcement Learning

#6306 · Yixiu Mao, Qi Wang, Yun Qu, Yuhang Jiang, Xiangyang Ji

Worst-Case Offline Reinforcement Learning with Arbitrary Data Support

#6307 · Kohei Miyaguchi

BECAUSE: Bilinear Causal Representation for Generalizable Offline Model-based Reinforcement Learning

#6308 · Haohong Lin, Wenhao Ding, Jian Chen, Laixi Shi, Jiacheng Zhu, Bo Li, DING ZHAO

Measuring Dejavu Memorization Efficiently

#6309 · Narine Kokhlikyan, Bargav Jayaraman, Florian Bordes, Chuan Guo, Kamalika Chaudhuri

Private Stochastic Convex Optimization with Heavy Tails: Near-Optimality from Simple Reductions

#6310 · Hilal Asi, Daogao Liu, Kevin Tian

The Surprising Ineffectiveness of Pre-Trained Visual Representations for Model-Based Reinforcement Learning

#6400 · Moritz Schneider, Robert Krug, Narunas Vaskevicius, Luigi Palmieri, Joschka Boedecker

Generalizing Consistency Policy to Visual RL with Prioritized Proximal Experience Regularization

#6401 · Haoran Li, Zhennan Jiang, YUHUI CHEN, Dongbin Zhao

Time-Constrained Robust MDPs

#6402 · Adil Zouitine, David Bertoin, Pierre Clavier, Matthieu Geist, Emmanuel Rachelson

No Representation, No Trust: Connecting Representation, Collapse, and Trust Issues in PPO

#6403 · Skander Moalla, Andrea Miele, Daniil Pyatko, Razvan Pascanu, Caglar Gulcehre

Mitigating Partial Observability in Decision Processes via the Lambda Discrepancy

#6404 · Cameron Allen, Aaron Kirtland, Ruo Yu Tao, Sam Lobel, Daniel Scott, Nicholas Petrocelli, Omer Gottesman, Ronald Parr, Michael Littman, George Konidaris

Decision Mamba: A Multi-Grained State Space Model with Self-Evolution Regularization for Offline RL

#6405 · Qi Lv, Xiang Deng, Gongwei Chen, MICHAEL YU WANG, Liqiang Nie

Disentangled Unsupervised Skill Discovery for Efficient Hierarchical Reinforcement Learning

#6406 · Jiaheng Hu, Zizhao Wang, Peter Stone, Roberto Martín-Martín

Autoregressive Policy Optimization for Constrained Allocation Tasks

#6407 · David Winkel, Niklas Strauß, Maximilian Bernhard, Zongyue Li, Thomas Seidl, Matthias Schubert

No Regrets: Investigating and Improving Regret Approximations for Curriculum Discovery

#6408 · Alexander Rutherford, Michael Beukman, Timon Willi, Bruno Lacerda, Nick Hawes, Jakob Foerster

Diffusion-Reward Adversarial Imitation Learning

#6409 · Chun-Mao Lai, Hsiang-Chun Wang, Ping-Chun Hsieh, Frank Wang, Min-Hung Chen, Shao-Hua Sun

Reinforcement Learning Under Latent Dynamics: Toward Statistical and Algorithmic Modularity

#6410 · Philip Amortila, Dylan J Foster, Nan Jiang, Akshay Krishnamurthy, Zak Mhammedi

Graph Learning for Numeric Planning

#6500 · Dillon Chen, Sylvie Thiebaux

Towards Effective Planning Strategies for Dynamic Opinion Networks

#6501 · Bharath Muppasani, Protik Nag, Vignesh Narayanan, Biplav Srivastava, Michael Huhns

Measuring Mutual Policy Divergence for Multi-Agent Sequential Exploration

#6502 · Haowen Dou, Lujuan Dang, Zhirong Luan, Badong Chen

Reciprocal Reward Influence Encourages Cooperation From Self-Interested Agents

#6503 · John L Zhou, Weizhe Hong, Jonathan Kao

MADiff: Offline Multi-agent Learning with Diffusion Models

#6504 · Zhengbang Zhu, Minghuan Liu, Liyuan Mao, Bingyi Kang, Minkai Xu, Yong Yu, Stefano Ermon, Weinan Zhang

Integrating Suboptimal Human Knowledge with Hierarchical Reinforcement Learning for Large-Scale Multiagent Systems

#6505 · Dingbang Liu, Shohei Kato, Wen Gu, Fenghui Ren, Jun Yan, Guoxin Su

Opponent Modeling based on Subgoal Inference

#6506 · XiaoPeng Yu, Jiechuan Jiang, Zongqing Lu

Melting Pot Contest: Charting the Future of Generalized Cooperative Intelligence

#6507 · Rakshit Trivedi, Akbir Khan, Jesse Clifton, Lewis Hammond, Edgar Duéñez-Guzmán, Dipam Chakraborty, John Agapiou, Jayd Matyas, Sasha Vezhnevets, Barna Pásztor, Yunke Ao, Omar G. Younis, Jiawei Huang, Benjamin Swain, Haoyuan Qin, Deng, Ziwei Deng, Utku Erdoğanaras, Yue Zhao, Marko Tesic, Natasha Jaques, Jakob Foerster, Vincent Conitzer, José Hernández-Orallo, Dylan Hadfield-Menell, Joel Leibo

SustainDC: Benchmarking for Sustainable Data Center Control

#6508 · Avisek Naug, Antonio Guillen-Perez, Ricardo Luna Gutierrez, Vineet Gundecha, Desik Rengarajan, Sahand Ghorbanpour, Sajad Mousavi, Ashwin Ramesh Babu, Dejan Markovikj, Lekhapriya Dheeraj Kashyap, Soumyendu Sarkar

ZSC-Eval: An Evaluation Toolkit and Benchmark for Multi-agent Zero-shot Coordination

#6509 · Xihuai Wang, Shao Zhang, Wenhao Zhang, Wentao Dong, Jingxiao Chen, Ying Wen, Weinan Zhang

BenchMARL: Benchmarking Multi-Agent Reinforcement Learning

#6510 · Matteo Bettini, Amanda Prorok, Vincent MOENS

SPO: Sequential Monte Carlo Policy Optimisation

#6600 · Matthew Macfarlane, Edan Toledo, Donal Byrne, Paul Duckworth, Alexandre Laterre

Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing

#6601 · Ye Tian, Baolin Peng, Linfeng Song, Lifeng Jin, Dian Yu, Lei Han, Haitao Mi, Dong Yu

Latent Plan Transformer for Trajectory Abstraction: Planning as Latent Space Inference

#6602 · Deqian Kong, Dehong Xu, Minglu Zhao, Bo Pang, Jianwen Xie, Andrew Lizarraga, Yuhao Huang, Sirui Xie, Ying Nian Wu

On the Complexity of Teaching a Family of Linear Behavior Cloning Learners

#6603 · Shubham Bharti, Stephen Wright, Adish Singla, Jerry Zhu

The Importance of Online Data: Understanding Preference Fine-tuning via Coverage

#6604 · Yuda Song, Gokul Swamy, Aarti Singh, J. Bagnell, Wen Sun

RA-PbRL: Provably Efficient Risk-Aware Preference-Based Reinforcement Learning

#6605 · Yujie Zhao, Jose Aguilar Escamilla, Weyl Lu, Huazheng Wang

Robot Policy Learning with Temporal Optimal Transport Reward

#6606 · Yuwei Fu, Haichao Zhang, Di Wu, Wei Xu, Benoit Boulet

LLM-based Skill Diffusion for Zero-shot Policy Adaptation

#6607 · Woo Kyung Kim, Youngseok Lee, Jooyoung Kim, Honguk Woo

Stepwise Alignment for Constrained Language Model Policy Optimization

#6608 · Akifumi Wachi, Thien Tran, Rei Sato, Takumi Tanabe, Youhei Akimoto

Regularized Conditional Diffusion Model for Multi-Task Preference Alignment

#6609 · Xudong Yu, Chenjia Bai, Haoran He, Changhong Wang, Xuelong Li

Beyond Optimism: Exploration With Partially Observable Rewards

#6610 · Simone Parisi, Alireza Kazemipour, Michael Bowling

Verified Safe Reinforcement Learning for Neural Network Dynamic Models

#6611 · Junlin Wu, Huan Zhang, Yevgeniy Vorobeychik

Is Score Matching Suitable for Estimating Point Processes?

#6612 · Haoqun Cao, Zizhuo Meng, Tianjun Ke, Feng Zhou

Ad Auctions for LLMs via Retrieval Augmented Generation

#6700 · MohammadTaghi Hajiaghayi, Sébastien Lahaie, Keivan Rezaei, Suho Shin

Quantum algorithm for large-scale market equilibrium computation

#6701 · Po-Wei Huang, Patrick Rebentrost

Cross-Device Collaborative Test-Time Adaptation

#6702 · Guohao Chen, Shuaicheng Niu, Deyu Chen, Shuhai Zhang, Changsheng Li, Yuanqing Li, Mingkui Tan

Continuous Temporal Domain Generalization

#6703 · Zekun CAI, Guangji Bai, Renhe Jiang, Xuan Song, Liang Zhao

Sketchy Moment Matching: Toward Fast and Provable Data Selection for Finetuning

#6704 · Yijun Dong, Viet Hoang Phan, Xiang Pan, Qi Lei

Preference Learning of Latent Decision Utilities with a Human-like Model of Preferential Choice

#6705 · Sebastiaan De Peuter, Shibei Zhu, Yujia Guo, Andrew Howes, Samuel Kaski

Evidential Mixture Machines: Deciphering Multi-Label Correlations for Active Learning Sensitivity

#6706 · Dayou Yu, Minghao Li, Weishi Shi, Qi Yu

Clustering with Non-adaptive Subset Queries

#6707 · Hadley Black, Euiwoong Lee, Arya Mazumdar, Barna Saha

Partially Observable Cost-Aware Active-Learning with Large Language Models

#6708 · Nicolás Astorga, Tennison Liu, Nabeel Seedat, Mihaela van der Schaar

On the Convergence of Loss and Uncertainty-based Active Learning Algorithms

#6709 · Daniel Haimovich, Dima Karamshuk, Fridolin Linder, Niek Tax, Milan Vojnovic

Learnability Matters: Active Learning for Video Captioning

#6710 · Yiqian Zhang, Buyu Liu, Jun Bao, Qiang Huang, Min Zhang, Jun Yu

Online Bayesian Persuasion Without a Clue

#6800 · Francesco Bacchiocchi, Matteo Bollini, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti

Multi-Winner Reconfiguration

#6801 · Jiehua Chen, Christian Hatschka, Sofia Simola

Conformalized Credal Set Predictors

#6802 · Alireza Javanmardi, David Stutz, Eyke Hüllermeier

Multi-Agent Coordination via Multi-Level Communication

#6803 · Gang Ding, Zeyuan Liu, Zhirui Fang, Kefan Su, Liwen Zhu, Zongqing Lu

Policy Optimization for Robust Average Reward MDPs

#6804 · Zhongchang Sun, Sihong He, Fei Miao, Shaofeng Zou

Offline Multitask Representation Learning for Reinforcement Learning

#6805 · Haque Ishfaq, Thanh Nguyen-Tang, Songtao Feng, Raman Arora, Mengdi Wang, Ming Yin, Doina Precup

Sub-optimal Experts mitigate Ambiguity in Inverse Reinforcement Learning

#6806 · Riccardo Poiani, Curti Gabriele, Alberto Maria Metelli, Marcello Restelli

Bisimulation Metrics are Optimal Transport Distances, and Can be Computed Efficiently

#6807 · Sergio Calo, Anders Jonsson, Gergely Neu, Ludovic Schwartz, Javier Segovia-Aguas

Taming "data-hungry" reinforcement learning? Stability in continuous state-action spaces

#6808 · Yaqi Duan, Martin Wainwright

The Value of Reward Lookahead in Reinforcement Learning

#6809 · Nadav Merlis, Dorian Baudry, Vianney Perchet

Randomized algorithms and PAC bounds for inverse reinforcement learning in continuous spaces

#6810 · Angeliki Kamoutsi, Peter Schmitt-Förster, Tobias Sutter, Volkan Cevher, John Lygeros

CoFie: Learning Compact Neural Surface Representations with Coordinate Fields

#6900 · Hanwen Jiang, Haitao Yang, Georgios Pavlakos, Qixing Huang

Visual CoT: Advancing Multi-Modal Language Models with a Comprehensive Dataset and Benchmark for Chain-of-Thought Reasoning

#6901 · Hao Shao, Shengju Qian, Han Xiao, Guanglu Song, ZHUOFAN ZONG, Letian Wang, Yu Liu, Hongsheng Li

A Careful Examination of Large Language Model Performance on Grade School Arithmetic

#6902 · Hugh Zhang, Jeff Da, Dean Lee, Vaughn Robinson, Catherine Wu, William Song, Tiffany Zhao, Pranav Raja, Charlotte Zhuang, Dylan Slack, Qin Lyu, Sean Hendryx, Russell Kaplan, Michele Lunati, Summer Yue

Text to Blind Motion

#6903 · Hee Jae Kim, Kathakoli Sengupta, Masaki Kuribayashi, Hernisa Kacorri, Eshed Ohn-Bar

GS-Blur: A 3D Scene-Based Dataset for Realistic Image Deblurring

#6904 · Dongwoo Lee, JoonKyu Park, Kyoung Mu Lee

Euclidean distance compression via deep random features

#6905 · Brett Leroux, Luis Rademacher

Achieving Optimal Clustering in Gaussian Mixture Models with Anisotropic Covariance Structures

#6906 · Xin Chen, Anderson Ye Zhang

Breaking the curse of dimensionality in structured density estimation

#6907 · Robert Vandermeulen, Wai Ming Tai, Bryon Aragam

Coherence-free Entrywise Estimation of Eigenvectors in Low-rank Signal-plus-noise Matrix Models

#6908 · Hao Yan, Keith Levin

Deterministic Policies for Constrained Reinforcement Learning in Polynomial Time

#6909 · Jeremy McMahan

Kernel-Based Function Approximation for Average Reward Reinforcement Learning: An Optimist No-Regret Algorithm

#6910 · Sattar Vakili, Julia Olkhovskaya

AdaNovo: Towards Robust \emph{De Novo} Peptide Sequencing in Proteomics against Data Biases

#7000 · Jun Xia, Shaorong Chen, Jingbo Zhou, Shan Xiaojun, Wenjie Du, Zhangyang Gao, Cheng Tan, Bozhen Hu, Jiangbin Zheng, Stan Z. Li

Instance-adaptive Zero-shot Chain-of-Thought Prompting

#7001 · Xiaosong Yuan, Chen Shen, Shaotian Yan, Xiaofeng Zhang, Liang Xie, Wenxiao Wang, Renchu Guan, Ying Wang, Jieping Ye

Motion Graph Unleashed: A Novel Approach to Video Prediction

#7002 · Yiqi Zhong, Luming Liang, Bohan Tang, Ilya Zharkov, Ulrich Neumann

ROIDICE: Offline Return on Investment Maximization for Efficient Decision Making

#7003 · Woosung Kim, Hayeong Lee, Jongmin Lee, Byung-Jun Lee

Vidu4D: Single Generated Video to High-Fidelity 4D Reconstruction with Dynamic Gaussian Surfels

#7004 · Yikai Wang, Xinzhou Wang, Zilong Chen, Zhengyi Wang, Fuchun Sun, Jun Zhu

Efficient Minimum Bayes Risk Decoding using Low-Rank Matrix Completion Algorithms

#7005 · Firas Trabelsi, David Vilar, Mara Finkelstein, Markus Freitag

Boosting Alignment for Post-Unlearning Text-to-Image Generative Models

#7006 · Myeongseob Ko, Henry Li, Zhun Wang, Jonathan Patsenker, Jiachen (Tianhao) Wang, Qinbin Li, Ming Jin, Dawn Song, Ruoxi Jia

Fast Graph Sharpness-Aware Minimization for Enhancing and Accelerating Few-Shot Node Classification

#7007 · Yihong Luo, Yuhan Chen, Siya Qiu, Yiwei Wang, Chen Zhang, Yan Zhou, Xiaochun Cao, Jing Tang

Large Language Models-guided Dynamic Adaptation for Temporal Knowledge Graph Reasoning

#7008 · Jiapu Wang, Sun Kai, LINHAO LUO, Wei Wei, Yongli Hu, Alan Wee-Chung Liew, Shirui Pan, Baocai Yin

TAPTRv2: Attention-based Position Update Improves Tracking Any Point

#7009 · Hongyang Li, Hao Zhang, Shilong Liu, Zhaoyang Zeng, Feng Li, Bohan Li, Tianhe Ren, Lei Zhang

Federated Natural Policy Gradient and Actor Critic Methods for Multi-task Reinforcement Learning

#7010 · Tong Yang, Shicong Cen, Yuting Wei, Yuxin Chen, Yuejie Chi

RegExplainer: Generating Explanations for Graph Neural Networks in Regression Tasks

#7100 · Jiaxing Zhang, Zhuomin Chen, hao mei, Longchao Da, Dongsheng Luo, Hua Wei

Can Simple Averaging Defeat Modern Watermarks?

#7101 · Pei Yang, Hai Ci, Yiren Song, Mike Zheng Shou

Derivative-enhanced Deep Operator Network

#7102 · Yuan Qiu, Nolan Bridges, Peng Chen

Variational Flow Matching for Graph Generation

#7103 · Floor Eijkelboom, Grigory Bartosh, Christian Andersson Naesseth, Max Welling, Jan-Willem van de Meent

SpeechAlign: Aligning Speech Generation to Human Preferences

#7104 · Dong Zhang, Zhaowei Li, Shimin Li, Xin Zhang, Pengyu Wang, Yaqian Zhou, Xipeng Qiu

Reparameterized Multi-Resolution Convolutions for Long Sequence Modelling

#7105 · Jake Cunningham, Giorgio Giannone, Mingtian Zhang, Marc Deisenroth

Sharpness-Aware Minimization Activates the Interactive Teaching's Understanding and Optimization

#7106 · Mingwei Xu, Xiaofeng Cao, Ivor Tsang

Connecting Joint-Embedding Predictive Architecture with Contrastive Self-supervised Learning

#7107 · Shentong Mo, Peter Tong

Rethinking Decoders for Transformer-based Semantic Segmentation: Compression is All You Need

#7108 · Qishuai Wen, Chun-Guang Li

LCM: Locally Constrained Compact Point Cloud Model for Masked Point Modeling

#7109 · Yaohua Zha, Naiqi Li, Yanzi Wang, Tao Dai, Hang Guo, Bin Chen, Zhi Wang, Zhihao Ouyang, Shu-Tao Xia

SpGesture: Source-Free Domain-adaptive sEMG-based Gesture Recognition with Jaccard Attentive Spiking Neural Network

#7110 · Weiyu Guo, Ying Sun, Yijie Xu, Ziyue Qiao, Yongkui Yang, Hui Xiong

Non-Stationary Learning of Neural Networks with Automatic Soft Parameter Reset

#7200 · Alexandre Galashov, Michalis Titsias, András György, Clare Lyle, Razvan Pascanu, Yee Whye Teh, Maneesh Sahani

SimVG: A Simple Framework for Visual Grounding with Decoupled Multi-modal Fusion

#7201 · Ming Dai, Lingfeng Yang, Yihao Xu, Zhenhua Feng, Wankou Yang

PaGoDA: Progressive Growing of a One-Step Generator from a Low-Resolution Diffusion Teacher

#7202 · Dongjun Kim, Chieh-Hsin Lai, Wei-Hsiang Liao, Yuhta Takida, Naoki Murata, Toshimitsu Uesaka, Yuki Mitsufuji, Stefano Ermon

Scaling Retrieval-Based Language Models with a Trillion-Token Datastore

#7203 · Rulin Shao, Jacqueline He, Akari Asai, Weijia Shi, Tim Dettmers, Sewon Min, Luke Zettlemoyer, Pang Wei Koh

ShowMaker: Creating High-Fidelity 2D Human Video via Fine-Grained Diffusion Modeling

#7204 · Quanwei Yang, Jiazhi Guan, Kaisiyuan Wang, Lingyun Yu, Wenqing Chu, Hang Zhou, ZhiQiang Feng, Haocheng Feng, Errui Ding, Jingdong Wang, Hongtao Xie

Generalization Error Bounds for Two-stage Recommender Systems with Tree Structure

#7205 · Jin Zhang, Ze Liu, Defu Lian, Enhong Chen

Implicit Curriculum in Procgen Made Explicit

#7206 · Zhenxiong Tan, Kaixin Wang, Xinchao Wang

Wings: Learning Multimodal LLMs without Text-only Forgetting

#7207 · Yi-Kai Zhang, Shiyin Lu, Yang Li, YanQing Ma, Qingguo Chen, Zhao Xu, Weihua Luo, Kaifu Zhang, De-Chuan Zhan, Han-Jia Ye

One-Step Diffusion Distillation through Score Implicit Matching

#7208 · Weijian Luo, Zemin Huang, Zhengyang Geng, J. Zico Kolter, Guo-Jun Qi

Make-An-Agent: A Generalizable Policy Network Generator with Behavior-Prompted Diffusion

#7209 · Yongyuan Liang, Tingqiang Xu, Kaizhe Hu, Guangqi Jiang, Furong Huang, Huazhe Xu

Artificial Generational Intelligence: Cultural Accumulation in Reinforcement Learning

#7210 · Jonathan Cook, Chris Lu, Edward Hughes, Joel Leibo, Jakob Foerster

Consistency Purification: Effective and Efficient Diffusion Purification towards Certified Robustness

#7300 · Yiquan Li, Zhongzhu Chen, Kun Jin, Jiongxiao Wang, Jiachen Lei, Bo Li, Chaowei Xiao

DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

#7301 · Hao Bai, Yifei Zhou, Jiayi Pan, Mert Cemri, Alane Suhr, Sergey Levine, Aviral Kumar

Optimal Algorithms for Online Convex Optimization with Adversarial Constraints

#7302 · Abhishek Sinha, Rahul Vaze

Implicitly Guided Design with PropEn: Match your Data to Follow the Gradient

#7303 · Nataša Tagasovska, Vladimir Gligorijevic, Kyunghyun Cho, Andreas Loukas

PhyloGen: Language Model-Enhanced Phylogenetic Inference via Graph Structure Generation

#7304 · ChenRui Duan, Zelin Zang, Siyuan Li, Yongjie Xu, Stan Z. Li

Diffusion Actor-Critic with Entropy Regulator

#7305 · Yinuo Wang, Likun Wang, Yuxuan Jiang, Wenjun Zou, Tong Liu, Xujie Song, Wenxuan Wang, Liming Xiao, Jiang Wu, Jingliang Duan, Shengbo Li

Proving Theorems Recursively

#7306 · Haiming Wang, Huajian Xin, Zhengying Liu, Wenda Li, Yinya Huang, Jianqiao Lu, Zhicheng Yang, Jing Tang, Jian Yin, Zhenguo Li, Xiaodan Liang

Simplified and Generalized Masked Diffusion for Discrete Data

#7307 · Jiaxin Shi, Kehang Han, Zhe Wang, Arnaud Doucet, Michalis Titsias

Iterative Methods via Locally Evolving Set Process

#7308 · Baojian Zhou, Yifan Sun, Reza Babanezhad Harikandeh, Xingzhi Guo, Deqing Yang, Yanghua Xiao

AdaFlow: Imitation Learning with Variance-Adaptive Flow-Based Policies

#7309 · Xixi Hu, Qiang Liu, Xingchao Liu, Bo Liu