Paperjam

#5102 · Ruben Ohana, Michael McCabe, Lucas Meyer, Rudy Morel, Fruzsina Agocs, Miguel Beneitez, Marsha Berger, Blakesly Burkhart, Stuart Dalziel, Drummond Fielding, Daniel Fortunato, Jared Goldberg, Keiya Hirashima, Yan-Fei Jiang, Rich Kerswell, Suryanarayana Maddu, Jonah Miller, Payel Mukhopadhyay, Stefan Nixon, Jeff Shen, Romain Watteaux, Bruno Régaldo-Saint Blancard, Liam Parker, Miles Cranmer, Shirley Ho

Conditional Generative Models are Sufficient to Sample from Any Causal Effect Estimand

#5103 · Md Musfiqur Rahman, Matt Jordan, Murat Kocaoglu

Partial Structure Discovery is Sufficient for No-regret Learning in Causal Bandits

#5104 · Muhammad Qasim Elahi, Mahsa Ghasemi, Murat Kocaoglu

Disentangled Representation Learning in Non-Markovian Causal Systems

#5105 · Adam Li, Yushu Pan, Elias Bareinboim

When to Act and When to Ask: Policy Learning With Deferral Under Hidden Confounding

#5106 · Marah Ghoummaid, Uri Shalit

From Causal to Concept-Based Representation Learning

#5107 · Goutham Rajendran, Simon Buchholz, Bryon Aragam, Bernhard Schölkopf, Pradeep Ravikumar

Unveiling the Potential of Robustness in Selecting Conditional Average Treatment Effect Estimators

#5108 · Yiyan Huang, Cheuk Hang LEUNG, Siyi WANG, YIJUN LI, Qi WU

Identifying General Mechanism Shifts in Linear Causal Representations

#5109 · Tianyu Chen, Kevin Bello, Francesco Locatello, Bryon Aragam, Pradeep Ravikumar

End-To-End Causal Effect Estimation from Unstructured Natural Language Data

#5110 · Nikita Dhawan, Leonardo Cotta, Karen Ullrich, Rahul Krishnan, Chris Maddison

Benchmarking Estimators for Natural Experiments: A Novel Dataset and a Doubly Robust Algorithm

#5200 · R. Teal Witter, Christopher Musco

Constrained Human-AI Cooperation: An Inclusive Embodied Social Intelligence Challenge

#5201 · Weihua Du, Qiushi Lyu, Jiaming Shan, Zhenting Qi, Hongxin Zhang, Sunli Chen, Andi Peng, Tianmin Shu, Kwonjoon Lee, Behzad Dariush, Chuang Gan

OpenDebateEvidence: A Massive-Scale Argument Mining and Summarization Dataset

#5202 · Allen Roush, Yusuf Shabazz, Arvind Balaji, Peter Zhang, Stefano Mezza, Markus Zhang, Sanjay Basu, Sriram Vishwanath, Ravid Shwartz-Ziv

ReXTime: A Benchmark Suite for Reasoning-Across-Time in Videos

#5203 · JR-JEN CHEN, Yu-Chien Liao, Hsi-Che Lin, Yu-Chu Yu, Yen-Chun Chen, Frank Wang

SciCode: A Research Coding Benchmark Curated by Scientists

#5204 · Minyang Tian, Luyu Gao, Shizhuo Zhang, Xinan Chen, Cunwei Fan, Xuefei Guo, Roland Haas, Pan Ji, Kittithat Krongchon, Yao Li, Shengyan Liu, Di Luo, Yutao Ma, HAO TONG, Kha Trinh, Chenyu Tian, Zihan Wang, Bohao Wu, Shengzhu Yin, Minhui Zhu, Kilian Lieret, Yanxin Lu, Genglin Liu, Yufeng Du, Tianhua Tao, Ofir Press, Jamie Callan, Eliu Huerta, Hao Peng

cPAPERS: A Dataset of Situated and Multimodal Interactive Conversations in Scientific Papers

#5205 · Anirudh Sundar, Jin Xu, William Gay, Christopher Richardson, Larry Heck

Sim2Real-Fire: A Multi-modal Simulation Dataset for Forecast and Backtracking of Real-world Forest Fire

#5206 · Yanzhi Li, Keqiu Li, LI GUOHUI, zumin wang, Chanqing Ji, Lubo Wang, Die Zuo, Qing Guo, Feng Zhang, Manyu Wang, Di Lin

Infer Induced Sentiment of Comment Response to Video: A New Task, Dataset and Baseline

#5207 · qi jia, baoyu, Cong Xu, Lu Liu, Liang Jin, Guoguang Du, Zhenhua Guo, Yaqian Zhao, Xuanjing Huang, Rengang Li

Muscles in Time: Learning to Understand Human Motion In-Depth by Simulating Muscle Activations

#5208 · David Schneider, Simon Reiß, Marco Kugler, Alexander Jaus, Kunyu Peng, Susanne Sutschet, M. Saquib Sarfraz, Sven Matthiesen, Rainer Stiefelhagen

Stylebreeder: Exploring and Democratizing Artistic Styles through Text-to-Image Models

#5209 · Matthew Zheng, Enis Simsar, Hidir Yesiltepe, Federico Tombari, Joel Simon, Pinar Yanardag

Few-shot Algorithms for Consistent Neural Decoding (FALCON) Benchmark

#5210 · Brianna Karpowicz, Joel Ye, Chaofei Fan, Pablo Tostado-Marcos, Fabio Rizzoglio, Clayton Washington, Thiago Scodeler, Diogo de Lucena, Samuel Nason-Tomaszewski, Matthew Mender, Xuan Ma, Ezequiel Arneodo, Leigh Hochberg, Cynthia Chestek, Jaimie Henderson, Timothy Gentner, Vikash Gilja, Lee Miller, Adam Rouse, Robert Gaunt, Jennifer Collinger, Chethan Pandarinath

OAM-TCD: A globally diverse dataset of high-resolution tree cover maps

#5211 · Josh Veitch-Michaelis, Andrew Cottam, Daniella Schweizer, Eben Broadbent, David Dao, Ce Zhang, Angelica Almeyda Zambrano, Simeon Max

Towards General Loop Invariant Generation: A Benchmark of Programs with Memory Manipulation

#5300 · Chang Liu, Xiwei Wu, Yuan Feng, Qinxiang Cao, Junchi Yan

Spider2-V: How Far Are Multimodal Agents From Automating Data Science and Engineering Workflows?

#5301 · Ruisheng Cao, Fangyu Lei, Haoyuan Wu, Jixuan Chen, Yeqiao Fu, Hongcheng Gao, Xinzhuang Xiong, Hanchong Zhang, Wenjing Hu, Yuchen Mao, Tianbao Xie, Hongshen Xu, Danyang Zhang, Sida Wang, Ruoxi Sun, Pengcheng Yin, Caiming Xiong, Ansong Ni, Qian Liu, Victor Zhong, Lu Chen, Kai Yu, Tao Yu

Archaeoscape: Bringing Aerial Laser Scanning Archaeology to the Deep Learning Era

#5302 · Yohann PERRON, Vladyslav Sydorov, Adam P. Wijker, Damian Evans, Christophe Pottier, Loic Landrieu

SM3-Text-to-Query: Synthetic Multi-Model Medical Text-to-Query Benchmark

#5303 · Sithursan Sivasubramaniam, Cedric E. Osei-Akoto, Yi Zhang, Kurt Stockinger, Jonathan Fuerst

DACO: Towards Application-Driven and Comprehensive Data Analysis via Code Generation

#5304 · Xueqing Wu, Rui Zheng, Jingzhen Sha, Te-Lin Wu, Hanyu Zhou, Tang Mohan, Kai-Wei Chang, Nanyun Peng, Haoran Huang

The State of Data Curation at NeurIPS: An Assessment of Dataset Development Practices in the Datasets and Benchmarks Track

#5305 · Eshta Bhardwaj, Harshit Gujral, Siyi Wu, Ciara Zogheib, Tegan Maharaj, Christoph Becker

AFBench: A Large-scale Benchmark for Airfoil Design

#5306 · Jian Liu, Jianyu Wu, Hairun Xie, Guoqing zhang, Jing Wang, Liu Wei, Wanli Ouyang, Junjun Jiang, Xianming Liu, SHIXIANG TANG, Miao Zhang

APIGen: Automated PIpeline for Generating Verifiable and Diverse Function-Calling Datasets

#5307 · Zuxin Liu, Thai Hoang, Jianguo Zhang, Ming Zhu, Tian Lan, Shirley kokane, Juntao Tan, Weiran Yao, Zhiwei Liu, Yihao Feng, Rithesh R N, Liangwei Yang, Silvio Savarese, Juan Carlos Niebles, Huan Wang, Shelby Heinecke, Caiming Xiong

When LLMs Meet Cunning Texts: A Fallacy Understanding Benchmark for Large Language Models

#5308 · Yinghui Li, Qingyu Zhou, Yuanzhen Luo, Shirong Ma, Yangning Li, Hai-Tao Zheng, Xuming Hu, Philip S Yu

AMBROSIA: A Benchmark for Parsing Ambiguous Questions into Database Queries

#5309 · Irina Saparina, Mirella Lapata

$\texttt{pfl-research}$: simulation framework for accelerating research in Private Federated Learning

#5310 · Filip Granqvist, Congzheng Song, Áine Cahill, Rogier van Dalen, Martin Pelikan, Yi Sheng Chan, Xiaojun Feng, Natarajan Krishnaswami, Vojta Jina, Mona Chitnis

Off to new Shores: A Dataset & Benchmark for (near-)coastal Flood Inundation Forecasting

#5311 · Brandon Victor, Mathilde Letard, Peter Naylor, Karim Douch, Nicolas Longepe, Zhen He, Patrick Ebel

Pedestrian Trajectory Prediction with Missing Data: Datasets, Imputation, and Benchmarking

#5400 · Pranav Singh Chib, Pravendra Singh

WikiDBs: A Large-Scale Corpus Of Relational Databases From Wikidata

#5401 · Liane Vogel, Jan-Micha Bodensohn, Carsten Binnig

Implicit Zoo: A Large-Scale Dataset of Neural Implicit Functions for 2D Images and 3D Scenes

#5402 · Qi Ma, Danda Pani Paudel, Ender Konukoglu, Luc V Gool

TaskBench: Benchmarking Large Language Models for Task Automation

#5403 · Yongliang Shen, Kaitao Song, Xu Tan, Wenqi Zhang, Kan Ren, Siyu Yuan, Weiming Lu, Dongsheng Li, Yueting Zhuang

Assemblage: Automatic Binary Dataset Construction for Machine Learning

#5404 · Chang Liu, Rebecca Saul, Yihao Sun, Edward Raff, Maya Fuchs, Townsend Southard Pantano, James Holt, Kristopher Micinski

μBench: A Microscopy Benchmark for Vision-Language Understanding

#5405 · Alejandro Lozano, Jeffrey Nirschl, James Burgess, Sanket Rajan Gupte, Yuhui Zhang, Alyssa Unell, Serena Yeung

ViLCo-Bench: VIdeo Language COntinual learning Benchmark

#5406 · Tianqi Tang, Shohreh Deldari, Hao Xue, Celso de Melo, Flora Salim

APEBench: A Benchmark for Autoregressive Neural Emulators of PDEs

#5407 · Felix Koehler, Simon Niedermayr, rüdiger westermann, Nils Thuerey

OpenCDA-Loop: A Closed-loop Benchmarking Platform for End-to-end Evaluation of Cooperative Perception

#5408 · Chia-Ju Chen, Runsheng Xu, Wei Shao, Junshan Zhang, Zhengzhong Tu

MARPLE: A Benchmark for Long-Horizon Inference

#5409 · Emily Jin, Zhuoyi Huang, Jan-Philipp Fraenken, Weiyu Liu, Hannah Cha, Erik Brockbank, Sarah Wu, Ruohan Zhang, Jiajun Wu, Tobias Gerstenberg

MM-WLAuslan: Multi-View Multi-Modal Word-Level Australian Sign Language Recognition Dataset

#5410 · Xin Shen, Heming Du, Hongwei Sheng, Shuyun Wang, Hui Chen, Huiqiang Chen, Zhuojie Wu, Xiaobiao Du, Jiaying Ying, Ruihan Lu, Qingzheng Xu, Xin Yu

User-item fairness tradeoffs in recommendations

#5500 · Sophie Greenwood, Sudalakshmee Chiniah, Nikhil Garg

On Socially Fair Low-Rank Approximation and Column Subset Selection

#5501 · Zhao Song, Ali Vakilian, David Woodruff, Samson Zhou

Multi-Group Proportional Representation in Retrieval

#5502 · Alex Oesterling, Claudio Mayrink Verdun, Alexander Glynn, Carol Long, Lucas Monteiro Paes, Sajani Vithana, Martina Cardone, Flavio Calmon

Prejudice and Volatility: A Statistical Framework for Measuring Social Discrimination in Large Language Models

#5503 · Yiran Liu, Ke Yang, Zehan Qi, Xiao Liu, Yang Yu, Cheng Xiang Zhai

Reproducibility Study of "ITI-GEN: Inclusive Text-to-Image Generation"

#5504 · Daniel Gallo Fernández, Răzvan-Andrei Matișan, Alejandro Monroy, Janusz Partyka

Reproducibility Study: Equal Improvability: A New Fairness Notion Considering the Long-Term Impact

#5505 · Berkay Chakar, Amina Izbassar, Mina Janićijević, Jakub Tomaszewski

Deep Learning in Medical Image Registration: Magic or Mirage?

#5506 · Rohit Jena, Deeksha Sethi, Pratik Chaudhari, James Gee

Cracking the Code of Juxtaposition: Can AI Models Understand the Humorous Contradictions

#5507 · Zhe Hu, Tuo Liang, Jing Li, Yiren Lu, Yunlai Zhou, Yiran Qiao, Jing Ma, Yu Yin

Multivariate Stochastic Dominance via Optimal Transport and Applications to Models Benchmarking

#5508 · Gabriel Rioux, Apoorva Nitsure, Mattia Rigotti, Kristjan Greenewald, Youssef Mroueh

Benchmarking Uncertainty Disentanglement: Specialized Uncertainties for Specialized Tasks

#5509 · Bálint Mucsányi, Michael Kirchhof, Seong Joon Oh

Mercury: A Code Efficiency Benchmark for Code Large Language Models

#5510 · Mingzhe Du, Anh Tuan Luu, Bin Ji, Qian Liu, See-Kiong Ng

Fair GLASSO: Estimating Fair Graphical Models with Unbiased Statistical Behavior

#5600 · Madeline Navarro, Samuel Rey, Andrei Buciulea, Antonio G. Marques, Santiago Segarra

Interpolating Item and User Fairness in Multi-Sided Recommendations

#5601 · Qinyi Chen, Jason Cheuk Nam Liang, Negin Golrezaei, Djallel Bouneffouf

GaussianMarker: Uncertainty-Aware Copyright Protection of 3D Gaussian Splatting

#5602 · Xiufeng Huang, Ruiqi Li, Yiu-ming Cheung, Ka Chun Cheung, Simon See, Renjie Wan

Tight Bounds for Learning RUMs from Small Slates

#5603 · Flavio Chierichetti, Mirko Giacchini, Ravi Kumar, Alessandro Panconesi, Andrew Tomkins

Topological Generalization Bounds for Discrete-Time Stochastic Optimization Algorithms

#5604 · Rayna Andreeva, Benjamin Dupuis, Rik Sarkar, Tolga Birdal, Umut Simsekli

Fast Rates for Bandit PAC Multiclass Classification

#5605 · Liad Erez, Alon Peled-Cohen, Tomer Koren, Yishay Mansour, Shay Moran

Error Analysis of Spherically Constrained Least Squares Reformulation in Solving the Stackelberg Prediction Game

#5606 · Xiyuan Li, Weiwei Liu

Dimension-free deterministic equivalents and scaling laws for random feature regression

#5607 · Leonardo Defilippis, Bruno Loureiro, Theodor Misiakiewicz

Unveil Benign Overfitting for Transformer in Vision: Training Dynamics, Convergence, and Generalization

#5608 · Jiarui Jiang, Wei Huang, Miao Zhang, Taiji Suzuki, Liqiang Nie

Sigmoid Gating is More Sample Efficient than Softmax Gating in Mixture of Experts

#5609 · Huy Nguyen, Nhat Ho, Alessandro Rinaldo

Tolerant Algorithms for Learning with Arbitrary Covariate Shift

#5610 · Surbhi Goel, Abhishek Shetty, Konstantinos Stavropoulos, Arsen Vasilyan

Continual Learning with Global Alignment

#5700 · Xueying Bai, Jinghuan Shang, Yifan Sun, Niranjan Balasubramanian

Adversarially Robust Multi-task Representation Learning

#5701 · Austin Watkins, Thanh Nguyen-Tang, Enayat Ullah, Raman Arora

Sample-Efficient Agnostic Boosting

#5702 · Udaya Ghai, Karan Singh

Optimal Algorithms for Augmented Testing of Discrete Distributions

#5703 · Maryam Aliakbarpour, Piotr Indyk, Ronitt Rubinfeld, Sandeep Silwal

Generalization Bounds via Conditional $f$-Information

#5704 · Ziqiao Wang, Yongyi Mao

Identification of Analytic Nonlinear Dynamical Systems with Non-asymptotic Guarantees

#5705 · Negin Musavi, Ziyao Guo, Geir Dullerud, Yingying Li

Soft ascent-descent as a stable and flexible alternative to flooding

#5706 · Matthew Holland, Kosuke Nakatani

Cardinality-Aware Set Prediction and Top-$k$ Classification

#5707 · Corinna Cortes, Anqi Mao, Christopher Mohri, Mehryar Mohri, Yutao Zhong

Cryptographic Hardness of Score Estimation

#5708 · Min Jae Song

Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithms

#5709 · Dimitri Meunier, Zikai Shen, Mattes Mollenhauer, Arthur Gretton, Zhu Li

Trade-Offs of Diagonal Fisher Information Matrix Estimators

#5710 · Alexander Soen, Ke Sun

Task-recency bias strikes back: Adapting covariances in Exemplar-Free Class Incremental Learning

#5800 · Grzegorz Rypeść, Sebastian Cygert, Tomasz Trzcinski, Bartłomiej Twardowski

Local and Adaptive Mirror Descents in Extensive-Form Games

#5801 · Côme Fiegel, Pierre Ménard, Tadashi Kozuno, Remi Munos, Vianney Perchet, Michal Valko

Gradient Methods for Online DR-Submodular Maximization with Stochastic Long-Term Constraints

#5802 · Guanyu Nie, Vaneet Aggarwal, Christopher Quinn

Optimal Top-Two Method for Best Arm Identification and Fluid Analysis

#5804 · Agniv Bandyopadhyay, Sandeep Juneja, Shubhada Agrawal

Optimal Multi-Fidelity Best-Arm Identification

#5805 · Riccardo Poiani, Rémy Degenne, Emilie Kaufmann, Alberto Maria Metelli, Marcello Restelli

Beyond Primal-Dual Methods in Bandits with Stochastic and Adversarial Constraints

#5806 · Martino Bernasconi, Matteo Castiglioni, Andrea Celli, Federico Fusco

Improved Algorithms for Contextual Dynamic Pricing

#5807 · Matilde Tullii, Solenne Gaucher, Nadav Merlis, Vianney Perchet

Regret Minimization in Stackelberg Games with Side Information

#5808 · Keegan Harris, Steven Wu, Maria-Florina Balcan

Fast Iterative Hard Thresholding Methods with Pruning Gradient Computations

#5809 · Yasutoshi Ida, Sekitoshi Kanai, Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara

Binary Search with Distributional Predictions

#5810 · Michael Dinitz, Sungjin Im, Thomas Lavastida, Ben Moseley, Aidin Niaparast, Sergei Vassilvitskii

Approximately Pareto-optimal Solutions for Bi-Objective k-Clustering

#5900 · Anna Arutyunova, Jan Eube, Heiko Röglin, Melanie Schmidt, Sarah Sturm, Julian Wargalla

Accelerating Matroid Optimization through Fast Imprecise Oracles

#5901 · Franziska Eberle, Felix Hommelsheim, Alexander Lindermayr, Zhenwei Liu, Nicole Megow, Jens Schlöter

John Ellipsoids via Lazy Updates

#5902 · David Woodruff, Taisuke Yasuda

S-SOS: Stochastic Sum-Of-Squares for Parametric Polynomial Optimization

#5903 · Licheng Zhu, Mathias Oster, Yuehaw Khoo

Functional Bilevel Optimization for Machine Learning

#5904 · Ieva Petrulionytė, Julien Mairal, Michael Arbel

Mean-Field Langevin Dynamics for Signed Measures via a Bilevel Approach

#5905 · Guillaume Wang, Alireza Mousavi-Hosseini, Lénaïc Chizat

First-Order Minimax Bilevel Optimization

#5906 · Yifan Yang, Zhaofeng Si, Siwei Lyu, Kaiyi Ji

Unveiling LoRA Intrinsic Ranks via Salience Analysis

#5907 · Wenjun Ke, Jiahao Wang, Peng Wang, Jiajun Liu, Dong Nie, Guozheng Li, Yining Li

Penalty-based Methods for Simple Bilevel Optimization under Hölderian Error Bounds

#5908 · Pengyu Chen, Xu Shi, Rujun Jiang, Jiulin Wang

Weight decay induces low-rank attention layers

#5909 · Seijin Kobayashi, Yassir Akram, Johannes von Oswald

Boundary Decomposition for Nadir Objective Vector Estimation

#5910 · Ruihao Zheng, Zhenkun Wang

Mirror and Preconditioned Gradient Descent in Wasserstein Space

#5911 · Clément Bonet, Théo Uscidda, Adam David, Pierre-Cyril Aubin-Frankowski, Anna Korba

Online Budgeted Matching with General Bids

#6000 · Jianyi Yang, Pengfei Li, Adam Wierman, Shaolei Ren

HardCore Generation: Generating Hard UNSAT Problems for Data Augmentation

#6001 · Joseph Cotnareanu, Zhanguang Zhang, Hui-Ling Zhen, Yingxue Zhang, Mark Coates

Learning-Augmented Dynamic Submodular Maximization

#6002 · Arpit Agarwal, Eric Balkanski

Controlling Continuous Relaxation for Combinatorial Optimization

#6003 · Yuma Ichikawa

Sketching for Distributed Deep Learning: A Sharper Analysis

#6004 · Mayank Shrivastava, Berivan Isik, Qiaobo Li, Sanmi Koyejo, Arindam Banerjee

Randomized Sparse Matrix Compression for Large-Scale Constrained Optimization in Cancer Radiotherapy

#6005 · Shima Adeli, Mojtaba Tefagh, Gourav Jhanwar, Masoud Zarepisheh

Implicit Regularization of Decentralized Gradient Descent for Sparse Regression

#6006 · Tongle Wu, Ying Sun

Shadowheart SGD: Distributed Asynchronous SGD with Optimal Time Complexity Under Arbitrary Computation and Communication Heterogeneity

#6007 · Alexander Tyurin, Marta Pozzi, Ivan Ilin, Peter Richtarik

Resource-Aware Federated Self-Supervised Learning with Global Class Representations

#6008 · Mingyi Li, Xiao Zhang, Qi Wang, Tengfei LIU, Ruofan Wu, Weiqiang Wang, Fuzhen Zhuang, Hui Xiong, Dongxiao Yu

Stabilized Proximal-Point Methods for Federated Optimization

#6009 · Xiaowen Jiang, Anton Rodomanov, Sebastian Stich

Dual Lagrangian Learning for Conic Optimization

#6010 · Mathieu Tanneau, Pascal Van Hentenryck

FERERO: A Flexible Framework for Preference-Guided Multi-Objective Learning

#6011 · Lisha Chen, A Saif, Yanning Shen, Tianyi Chen

Ordered Momentum for Asynchronous SGD

#6012 · Chang-Wei Shi, Yi-Rui Yang, Wu-Jun Li

Instance-Optimal Private Density Estimation in the Wasserstein Distance

#6100 · Vitaly Feldman, Audra McMillan, Satchit Sivakumar, Kunal Talwar

Noise-Aware Differentially Private Regression via Meta-Learning

#6101 · Ossi Räisä, Stratis Markou, Matthew Ashman, Wessel Bruinsma, Marlon Tobaben, Antti Honkela, Richard Turner

Langevin Unlearning: A New Perspective of Noisy Gradient Descent for Machine Unlearning

#6102 · Eli Chien, Haoyu Wang, Ziang Chen, Pan Li

PrivacyLens: Evaluating Privacy Norm Awareness of Language Models in Action

#6103 · Yijia Shao, Tianshi Li, Weiyan Shi, Yanchen Liu, Diyi Yang

A Synthetic Dataset for Personal Attribute Inference

#6104 · Hanna Yukhymenko, Robin Staab, Mark Vero, Martin Vechev

This Too Shall Pass: Removing Stale Observations in Dynamic Bayesian Optimization

#6105 · Anthony Bardou, Patrick Thiran, Giovanni Ranieri

Random Function Descent

#6106 · Felix Benning, Leif Döring

Decentralized Noncooperative Games with Coupled Decision-Dependent Distributions

#6107 · Wenjing YAN, Xuanyu Cao

On Convergence of Adam for Stochastic Optimization under Relaxed Assumptions

#6108 · Yusu Hong, Junhong Lin

Provable Acceleration of Nesterov's Accelerated Gradient for Asymmetric Matrix Factorization and Linear Neural Networks

#6109 · Zhenghao Xu, Yuqing Wang, Tuo Zhao, Rachel Ward, Molei Tao

Gradient-Free Methods for Nonconvex Nonsmooth Stochastic Compositional Optimization

#6110 · Zhuanghua Liu, Luo Luo, Bryan Kian Hsiang Low

Fast Encoder-Based 3D from Casual Videos via Point Track Processing

#6200 · Yoni Kasten, Wuyue Lu, Haggai Maron

DAGER: Exact Gradient Inversion for Large Language Models

#6201 · Ivo Petrov, Dimitar I. Dimitrov, Maximilian Baader, Mark Müller, Martin Vechev

On provable privacy vulnerabilities of graph representations

#6202 · Ruofan Wu, Guanhua Fang, Mingyang Zhang, Qiying Pan, Tengfei LIU, Weiqiang Wang

Continual Counting with Gradual Privacy Expiration

#6203 · Joel Daniel Andersson, Monika Henzinger, Rasmus Pagh, Teresa Anna Steiner, Jalaj Upadhyay

Reconstruction Attacks on Machine Unlearning: Simple Models are Vulnerable

#6204 · Martin Bertran, Shuai Tang, Michael Kearns, Jamie Morgenstern, Aaron Roth, Steven Wu

Efficient and Private Marginal Reconstruction with Local Non-Negativity

#6205 · Brett Mullins, Miguel Fuentes, Yingtai Xiao, Daniel Kifer, Cameron Musco, Daniel Sheldon

How to Solve Contextual Goal-Oriented Problems with Offline Datasets?

#6206 · Ying Fan, Jingling Li, Adith Swaminathan, Aditya Modi, Ching-An Cheng

Deterministic Uncertainty Propagation for Improved Model-Based Offline Reinforcement Learning

#6207 · Abdullah Akgül, Manuel Haussmann, Melih Kandemir

Safe and Efficient: A Primal-Dual Method for Offline Convex CMDPs under Partial Data Coverage

#6208 · Haobo Zhang, Xiyue Peng, Honghao Wei, Xin Liu

Offline Reinforcement Learning with OOD State Correction and OOD Action Suppression

#6209 · Yixiu Mao, Qi Wang, Chen Chen, Yun Qu, Xiangyang Ji

Explaining RL Decisions with Trajectories': A Reproducibility Study

#6210 · Karim Abdel Sadek, Matteo Nulli, Joan Velja, Jort Vincenti

Discovering Creative Behaviors through DUPLEX: Diverse Universal Features for Policy Exploration

#6300 · Borja G. Leon, Francesco Riccio, Kaushik Subramanian, Peter Wurman, Peter Stone

Can Learned Optimization Make Reinforcement Learning Less Difficult?

#6301 · Alexander D. Goldie, Chris Lu, Matthew T Jackson, Shimon Whiteson, Jakob Foerster

Subwords as Skills: Tokenization for Sparse-Reward Reinforcement Learning

#6302 · David Yunis, Justin Jung, Falcon Dai, Matthew Walter

Fast TRAC: A Parameter-Free Optimizer for Lifelong Reinforcement Learning

#6303 · Aneesh Muppidi, Zhiyu Zhang, Heng Yang

Reinforcing LLM Agents via Policy Optimization with Action Decomposition

#6304 · Muning Wen, Ziyu Wan, Jun Wang, Weinan Zhang, Ying Wen

Pre-Trained Multi-Goal Transformers with Prompt Optimization for Efficient Online Adaptation

#6305 · Haoqi Yuan, Yuhui Fu, Feiyang Xie, Zongqing Lu

Spectral-Risk Safe Reinforcement Learning with Convergence Guarantees

#6306 · Dohyeong Kim, Taehyun Cho, Seungyub Han, Hojun Chung, Kyungjae Lee, Songhwai Oh

Diffusion Imitation from Observation

#6307 · Bo-Ruei Huang, Chun-Kai Yang, Chun-Mao Lai, Dai-Jie Wu, Shao-Hua Sun

Reinforcement Learning Gradients as Vitamin for Online Finetuning Decision Transformers

#6308 · Kai Yan, Alex Schwing, Yu-Xiong Wang

e-COP : Episodic Constrained Optimization of Policies

#6309 · Akhil Agnihotri, Rahul Jain, Deepak Ramachandran, Sahil Singla

Efficient Multi-task Reinforcement Learning with Cross-Task Policy Guidance

#6310 · Jinmin He, Kai Li, Yifan Zang, Haobo Fu, Qiang Fu, Junliang Xing, Jian Cheng

Adam on Local Time: Addressing Nonstationarity in RL with Relative Adam Timesteps

#6400 · Benjamin Ellis, Matthew T Jackson, Andrei Lupu, Alexander D. Goldie, Mattie Fellows, Shimon Whiteson, Jakob Foerster

Optimizing Automatic Differentiation with Deep Reinforcement Learning

#6401 · Jamie Lohoff, Emre Neftci

QGFN: Controllable Greediness with Action Values

#6402 · Elaine Lau, Stephen Lu, Ling Pan, Doina Precup, Emmanuel Bengio

Maximum Entropy Reinforcement Learning via Energy-Based Normalizing Flow

#6403 · Chen-Hao Chao, Chien Feng, Wei-Fang Sun, Cheng-Kuang Lee, Simon See, Chun-Yi Lee

Recurrent Reinforcement Learning with Memoroids

#6404 · Steven Morad, Chris Lu, Ryan Kortvelesy, Stephan Liwicki, Jakob Foerster, Amanda Prorok

Efficient Recurrent Off-Policy RL Requires a Context-Encoder-Specific Learning Rate

#6405 · Fan-Ming Luo, Zuolin Tu, Zefang Huang, Yang Yu

Learning Multimodal Behaviors from Scratch with Diffusion Policy Gradient

#6406 · Steven Li, Rickmer Krohn, Tao Chen, Anurag Ajay, Pulkit Agrawal, Georgia Chalvatzaki

Achieving Constant Regret in Linear Markov Decision Processes

#6407 · Weitong Zhang, Zhiyuan Fan, Jiafan He, Quanquan Gu

Learning to Assist Humans without Inferring Rewards

#6408 · Vivek Myers, Evan Ellis, Sergey Levine, Benjamin Eysenbach, Anca Dragan

VLM Agents Generate Their Own Memories: Distilling Experience into Embodied Programs of Thought

#6409 · Gabriel Sarch, Lawrence Jang, Michael Tarr, William Cohen, Kenneth Marino, Katerina Fragkiadaki

AutoManual: Generating Instruction Manuals by LLM Agents via Interactive Environmental Learning

#6410 · Minghao Chen, Yihang Li, Yanting Yang, Shiyu Yu, Binbin Lin, Xiaofei He

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation

#6500 · Arvind Vepa, Zukang Yang, Andrew Choi, Jungseock Joo, Fabien Scalzo, Yizhou Sun

Statistical Multicriteria Benchmarking via the GSD-Front

#6501 · Christoph Jansen, Georg Schollmeyer, Julian Rodemann, Hannah Blocher, Thomas Augustin

Dynamic Model Predictive Shielding for Provably Safe Reinforcement Learning

#6502 · Arko Banerjee, Kia Rahmani, Joydeep Biswas, Isil Dillig

KALM: Knowledgeable Agents by Offline Reinforcement Learning from Large Language Model Rollouts

#6503 · Jing-Cheng Pang, Si-Hang Yang, Kaiyuan Li, Jiaji Zhang, Xiong-Hui Chen, Nan Tang, Yang Yu

Regularizing Hidden States Enables Learning Generalizable Reward Model for LLMs

#6504 · Rui Yang, Ruomeng Ding, Yong Lin, Huan Zhang, Tong Zhang

Contextual Bilevel Reinforcement Learning for Incentive Alignment

#6505 · Vinzenz Thoma, Barna Pásztor, Andreas Krause, Giorgia Ramponi, Yifan Hu

DynaMITE-RL: A Dynamic Model for Improved Temporal Meta-Reinforcement Learning

#6506 · Anthony Liang, Guy Tennenholtz, Chih-wei Hsu, Yinlam Chow, Erdem Bıyık, Craig Boutilier

Overcoming the Sim-to-Real Gap: Leveraging Simulation to Learn to Explore for Real-World RL

#6507 · Andrew Wagenmaker, Kevin Huang, Liyiming Ke, Kevin Jamieson, Abhishek Gupta

Using Unity to Help Solve Reinforcement Learning

#6508 · Connor Brennan, Andrew Williams, Omar G. Younis, Vedant Vyas, Daria Yasafova, Irina Rish

Thought of Search: Planning with Language Models Through The Lens of Efficiency

#6509 · Michael Katz, Harsha Kokel, Kavitha Srinivas, Shirin Sohrabi Araghi

Predicting Future Actions of Reinforcement Learning Agents

#6510 · Stephen Chung, Scott Niekum, David Krueger

Label Alignment Regularization for Distribution Shift

#6600 · Ehsan Imani, Guojun Zhang, Runjia Li, Jun Luo, Pascal Poupart, Philip Torr, Yangchen Pan

Beyond task diversity: provable representation transfer for sequential multitask linear bandits

#6601 · Thang Duong, Zhi Wang, Chicheng Zhang

L-TTA: Lightweight Test-Time Adaptation Using a Versatile Stem Layer

#6602 · Jin Shin, Hyun Kim

Extensive-Form Game Solving via Blackwell Approachability on Treeplexes

#6603 · Darshan Chakrabarti, Julien Grand-Clément, Christian Kroer

No-regret Learning in Harmonic Games: Extrapolation in the Face of Conflicting Interests

#6604 · Davide Legacci, Panayotis Mertikopoulos, Christos Papadimitriou, Georgios Piliouras, Bary Pradelski

MAC Advice for facility location mechanism design

#6605 · Zohar Barak, Anupam Gupta, Inbal Talgam-Cohen

Intrinsic Robustness of Prophet Inequality to Strategic Reward Signaling

#6606 · Wei Tang, Haifeng Xu, Ruimin Zhang, Derek Zhu

Honor Among Bandits: No-Regret Learning for Online Fair Division

#6607 · Ariel Procaccia, Ben Schiffer, Shirley Zhang

Learning Optimal Tax Design in Nonatomic Congestion Games

#6608 · Qiwen Cui, Maryam Fazel, Simon Du

Understanding Model Selection for Learning in Strategic Environments

#6609 · Tinashe Handina, Eric Mazumdar

Randomized Strategic Facility Location with Predictions

#6610 · Eric Balkanski, Vasilis Gkatzelis, Golnoosh Shahkarami

Efficient $\Phi$-Regret Minimization with Low-Degree Swap Deviations in Extensive-Form Games

#6611 · Brian Zhang, Ioannis Anagnostides, Gabriele Farina, Tuomas Sandholm

Accelerating Nash Equilibrium Convergence in Monte Carlo Settings Through Counterfactual Value Based Fictitious Play

#6612 · Qi Ju, Falin Hei, Ting Feng, Dengbing Yi, Zhemei Fang, YunFeng Luo

Local Anti-Concentration Class: Logarithmic Regret for Greedy Linear Contextual Bandit

#6700 · Seok-Jin Kim, Min-hwan Oh

Small steps no more: Global convergence of stochastic gradient bandits for arbitrary learning rates

#6701 · Jincheng Mei, Bo Dai, Alekh Agarwal, Sharan Vaswani, Anant Raj, Csaba Szepesvari, Dale Schuurmans

Provable Partially Observable Reinforcement Learning with Privileged Information

#6702 · Yang Cai, Xiangyu Liu, Argyris Oikonomou, Kaiqing Zhang

Reinforcement Learning with LTL and $\omega$-Regular Objectives via Optimality-Preserving Translation to Average Rewards

#6703 · Xuan Bach Le, Dominik Wagner, Leon Witzman, Alexander Rabinovich, Luke Ong

Foundations of Multivariate Distributional Reinforcement Learning

#6704 · Harley Wiltzer, Jesse Farebrother, Arthur Gretton, Mark Rowland

Risk-sensitive control as inference with Rényi divergence

#6705 · Kaito Ito, Kenji Kashima

Periodic agent-state based Q-learning for POMDPs

#6706 · Amit Sinha, Matthieu Geist, Aditya Mahajan

Beating Adversarial Low-Rank MDPs with Unknown Transition and Bandit Feedback

#6707 · Haolin Liu, Zak Mhammedi, Chen-Yu Wei, Julian Zimmert

Warm-up Free Policy Optimization: Improved Regret in Linear Markov Decision Processes

#6708 · Asaf Cassel, Aviv Rosenberg

An Analysis of Elo Rating Systems via Markov Chains

#6709 · Sam Olesker-Taylor, Luca Zanetti

Accelerating Relative Entropy Coding with Space Partitioning

#6710 · Jiajun He, Gergely Flamich, José Miguel Hernández-Lobato

On the Curses of Future and History in Future-dependent Value Functions for Off-policy Evaluation

#6800 · Yuheng Zhang, Nan Jiang

Statistical Inference for Fairness Auditing

#6801 · John Cherian, Emmanuel Candes

A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits

#6802 · Junghyun Lee, Se-Young Yun, Kwang-Sung Jun

Matrix Denoising with Doubly Heteroscedastic Noise: Fundamental Limits and Optimal Spectral Methods

#6803 · Yihan Zhang, Marco Mondelli

Community Detection Guarantees using Embeddings Learned by Node2Vec

#6804 · Andrew Davison, S. Carlyle Morgan, Owen G. Ward

Assouad, Fano, and Le Cam with Interaction: A Unifying Lower Bound Framework and Characterization for Bandit Learnability

#6805 · Fan Chen, Dylan J Foster, Yanjun Han, Jian Qian, Alexander Rakhlin, Yunbei Xu

On the Robustness of Spectral Algorithms for Semirandom Stochastic Block Models

#6806 · Aditya Bhaskara, Agastya Jha, Michael Kapralov, Naren Manoj, Davide Mazzali, Weronika Wrzos-Kaminska

Learning-Augmented Priority Queues

#6807 · Ziyad Benomar, Christian Coester

Navigable Graphs for High-Dimensional Nearest Neighbor Search: Constructions and Limits

#6808 · Haya Diwan, Jinrui Gou, Cameron Musco, Christopher Musco, Torsten Suel

Aligning Model Properties via Conformal Risk Control

#6809 · William Overman, Jacqueline Vallon, Mohsen Bayati

Bias in Motion: Theoretical Insights into the Dynamics of Bias in SGD Training

#6810 · Anchit Jain, Rozhin Nobahari, Aristide Baratin, Stefano Sarao Mannelli

RouterDC: Query-Based Router by Dual Contrastive Learning for Assembling Large Language Models

#6900 · Shuhao Chen, Weisen Jiang, Baijiong Lin, James Kwok, Yu Zhang

Error Correction Output Codes for Robust Neural Networks against Weight-errors: A Neural Tangent Kernel Point of View

#6901 · Anlan Yu, Shusen Jing, Ning Lyu, Wujie Wen, Zhiyuan Yan

CogVLM: Visual Expert for Pretrained Language Models

#6902 · Weihan Wang, Qingsong Lv, Wenmeng Yu, Wenyi Hong, Ji Qi, Yan Wang, Junhui Ji, Zhuoyi Yang, Lei Zhao, Song XiXuan, Jiazheng Xu, Keqin Chen, Bin Xu, Juanzi Li, Yuxiao Dong, Ming Ding, Jie Tang

Transformers on Markov data: Constant depth suffices

#6903 · Nived Rajaraman, Marco Bondaschi, Ashok Vardhan Makkuva, Kannan Ramchandran, Michael Gastpar

Hierarchical and Density-based Causal Clustering

#6904 · Kwangho Kim, Jisu Kim, Larry Wasserman, Edward Kennedy

Cal-DPO: Calibrated Direct Preference Optimization for Language Model Alignment

#6905 · Teng Xiao, Yige Yuan, Huaisheng Zhu, Mingxiao Li, Vasant Honavar

Recurrent neural networks: vanishing and exploding gradients are not the end of the story

#6906 · Nicolas Zucchet, Antonio Orvieto

Theoretical Foundations of Deep Selective State-Space Models

#6907 · Nicola Muca Cirone, Antonio Orvieto, Benjamin Walker, Cristopher Salvi, Terry Lyons

Can Models Learn Skill Composition from Examples?

#6908 · Haoyu Zhao, Simran Kaur, Dingli Yu, Anirudh Goyal, Sanjeev Arora

ODRL: A Benchmark for Off-Dynamics Reinforcement Learning

#6909 · Jiafei Lyu, Kang Xu, Jiacheng Xu, yan, Jing-Wen Yang, Zongzhang Zhang, Chenjia Bai, Zongqing Lu, Xiu Li

Metrizing Weak Convergence with Maximum Mean Discrepancies

#6910 · Carl-Johann Simon-Gabriel, Alessandro Barp, Bernhard Schölkopf, Lester Mackey

Ensemble Learning for Heterogeneous Large Language Models with Deep Parallel Collaboration

#7000 · Yichong Huang, Xiaocheng Feng, Baohang Li, Yang Xiang, Hui Wang, Ting Liu, Bing Qin

Conformalized Multiple Testing after Data-dependent Selection

#7001 · Xiaoning Wang, Yuyang Huo, Liuhua Peng, Changliang Zou

Autonomous Driving with Spiking Neural Networks

#7002 · Rui-Jie Zhu, Ziqing Wang, Leilani Gilpin, Jason Eshraghian

VLMimic: Vision Language Models are Visual Imitation Learner for Fine-grained Actions

#7003 · Guangyan Chen, Meiling Wang, Te Cui, Yao Mu, Haoyang Lu, Tianxing Zhou, Zicai Peng, Mengxiao Hu, Haizhou Li, Li Yuan, Yi Yang, Yufeng Yue

Uncertainty of Thoughts: Uncertainty-Aware Planning Enhances Information Seeking in LLMs

#7004 · Zhiyuan Hu, Chumin Liu, Xidong Feng, Yilun Zhao, See-Kiong Ng, Anh Tuan Luu, Junxian He, Pang Wei Koh, Bryan Hooi

3D Structure Prediction of Atomic Systems with Flow-based Direct Preference Optimization

#7005 · Rui Jiao, Xiangzhe Kong, Wenbing Huang, Yang Liu

Improving Gloss-free Sign Language Translation by Reducing Representation Density

#7006 · Jinhui Ye, Xing Wang, Wenxiang Jiao, Junwei Liang, Hui Xiong

FACT or Fiction: Can Truthful Mechanisms Eliminate Federated Free Riding?

#7007 · Marco Bornstein, Amrit Singh Bedi, Abdirisak Mohamed, Furong Huang

Cross-Modality Perturbation Synergy Attack for Person Re-identification

#7008 · Yunpeng Gong, Zhun Zhong, Yansong Qu, Zhiming Luo, Rongrong Ji, Min

You Only Look Around: Learning Illumination-Invariant Feature for Low-light Object Detection

#7009 · Mingbo Hong, Shen Cheng, Haibin Huang, Haoqiang Fan, Shuaicheng Liu

AvaTaR: Optimizing LLM Agents for Tool Usage via Contrastive Reasoning

#7010 · Shirley Wu, Shiyu Zhao, Qian Huang, Kexin Huang, Michihiro Yasunaga, Kaidi Cao, Vassilis Ioannidis, Karthik Subbian, Jure Leskovec, James Zou

MemVLT: Vision-Language Tracking with Adaptive Memory-based Prompts

#7100 · Xiaokun Feng, Xuchen Li, Shiyu Hu, Dailing Zhang, wu meiqi, Jing Zhang, Xiaotang Chen, Kaiqi Huang

Schedule Your Edit: A Simple yet Effective Diffusion Noise Schedule for Image Editing

#7101 · Haonan Lin, Yan Chen, Jiahao Wang, Wenbin An, Mengmeng Wang, Feng Tian, Yong Liu, Guang Dai, Jingdong Wang, QianYing Wang

TreeVI: Reparameterizable Tree-structured Variational Inference for Instance-level Correlation Capturing

#7102 · Junxi Xiao, Qinliang Su

Single Image Unlearning: Efficient Machine Unlearning in Multimodal Large Language Models

#7103 · Jiaqi Li, Qianshan Wei, Chuanyi Zhang, Guilin Qi, Miaozeng Du, Yongrui Chen, Sheng Bi, Fan Liu

A Tractable Inference Perspective of Offline RL

#7104 · Xuejie Liu, Anji Liu, Guy Van den Broeck, Yitao Liang

Exocentric-to-Egocentric Video Generation

#7105 · Jia-Wei Liu, Weijia Mao, Zhongcong XU, Jussi Keppo, Mike Zheng Shou

Targeted Sequential Indirect Experiment Design

#7106 · Elisabeth Ailer, Niclas Dern, Jason Hartford, Niki Kilbertus

Diffusion-Inspired Truncated Sampler for Text-Video Retrieval

#7107 · JIAMIAN WANG, Pichao WANG, Dongfang Liu, Qiang Guan, Sohail Dianat, MAJID RABBANI, Raghuveer Rao, Zhiqiang Tao

Mixture of In-Context Experts Enhance LLMs' Long Context Awareness

#7108 · Hongzhan Lin, Ang Lv, yuhan chen, chen zhu, Yang Song, Hengshu Zhu, Rui Yan

Improved Sample Complexity Bounds for Diffusion Model Training

#7109 · Shivam Gupta, Aditya Parulekar, Eric Price, Zhiyang Xun

Data Augmentation with Diffusion for Open-Set Semi-Supervised Learning

#7110 · Seonghyun Ban, Heesan Kong, Kee-Eung Kim

Stochastic Amortization: A Unified Approach to Accelerate Feature and Data Attribution

#7200 · Ian Covert, Chanwoo Kim, Su-In Lee, James Zou, Tatsunori Hashimoto

ChatQA: Surpassing GPT-4 on Conversational QA and RAG

#7201 · Zihan Liu, Wei Ping, Rajarshi Roy, Peng Xu, Chankyu Lee, Mohammad Shoeybi, Bryan Catanzaro

Secret Collusion among AI Agents: Multi-Agent Deception via Steganography

#7202 · Sumeet Motwani, Mikhail Baranchuk, Martin Strohmeier, Vijay Bolina, Philip Torr, Lewis Hammond, Christian Schroeder de Witt

Causal language modeling can elicit search and reasoning capabilities on logic puzzles

#7203 · Kulin Shah, Nishanth Dikkala, Xin Wang, Rina Panigrahy

Rethinking 3D Convolution in $\ell_p$-norm Space

#7204 · Li Zhang, Yan Zhong, Jianan Wang, Zhe Min, RujingWang, Liu Liu

Time-Reversal Provides Unsupervised Feedback to LLMs

#7205 · Yerram Varun, Rahul Madhavan, Sravanti Addepalli, Arun Suggala, Karthikeyan Shanmugam, Prateek Jain

Cost-efficient Knowledge-based Question Answering with Large Language Models

#7206 · Junnan Dong, Qinggang Zhang, Chuang Zhou, Hao Chen, Daochen Zha, Xiao Huang

Monomial Matrix Group Equivariant Neural Functional Networks

#7207 · Hoang Tran, Thieu Vo, Tho Huu, An Nguyen The, Tan Nguyen

Explaining Datasets in Words: Statistical Models with Natural Language Parameters

#7208 · Ruiqi Zhong, Heng Wang, Dan Klein, Jacob Steinhardt

RoPINN: Region Optimized Physics-Informed Neural Networks

#7209 · Haixu Wu, Huakun Luo, Yuezhou Ma, Jianmin Wang, Mingsheng Long

DDK: Distilling Domain Knowledge for Efficient Large Language Models

#7210 · Jiaheng Liu, Chenchen Zhang, Jinyang Guo, Yuanxing Zhang, Haoran Que, Ken Deng, ZhiqiBai zhiqi, Jie Liu, Ge Zhang, JiakaiWang, Yanan Wu, Congnan Liu, Jiamang Wang, Lin Qu, Wenbo Su, Bo Zheng

Quantitative Convergences of Lie Group Momentum Optimizers

#7304 · Lingkai Kong, Molei Tao

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random

#7305 · Gautam Chandrasekaran, Vasilis Kontonis, Konstantinos Stavropoulos, Kevin Tian

Do Multimodal Foundation Models Understand Enterprise Workflows? A Benchmark for Business Process Management Tasks

#7306 · Michael Wornow, Avanika Narayan, Ben Viggiano, Ishan Khare, Tathagat Verma, Tibor Thompson, Miguel Hernandez, Sudharsan Sundar, Chloe Trujillo, Krrish Chawla, Rongfei Lu, Justin Shen, Divya Nagaraj, Joshua Martinez, Vardhan Agrawal, Althea Hudson, Nigam Shah, Christopher Ré

Towards Exact Gradient-based Training on Analog In-memory Computing

#7307 · Zhaoxian Wu, Tayfun Gokmen, Malte Rasch, Tianyi Chen

MoGenTS: Motion Generation based on Spatial-Temporal Joint Modeling

#7308 · Weihao Yuan, Yisheng HE, Weichao Shen, Yuan Dong, Xiaodong Gu, Zilong Dong, Liefeng Bo, Qixing Huang

Color-Oriented Redundancy Reduction in Dataset Distillation

#7309 · Bowen Yuan, Zijian Wang, Mahsa Baktashmotlagh, Yadan Luo, Zi Huang