Google at NeurIPS 2025

A Implies B: Circuit Analysis in LLMs for Propositional Logical Reasoning
Guan Zhe Hong*, Nishanth Dikkala, Enming Luo, Cyrus Rashtchian, Xin Wang, Rina Panigrahy

Affine-Invariant Global Non-Asymptotic Convergence Analysis of BFGS Under Self-Concordance
Qiujiang Jin, Aryan Mokhtari

Agnostic Learning Under Targeted Poisoning: Optimal Rates and the Role of Randomness
Bogdan Chornomaz, Yonatan Koren, Shay Moran, Tom Waknine

An Analysis of Causal Effect Estimation Using Outcome Invariant Data Augmentation
Uzair Akbar, Niki Kilbertus, Hao Shen, Krikamol Muandet, Bo Dai

Communication-Efficient Language Model Training Scales Reliably and Robustly: Scaling Laws for DiLoCo
Zachary Charles, Gabriel Teston, Lucio Dery, Keith Rush, Nova Fallen, Zachary Garrett, Arthur Szlam, Arthur Douillard

Depth-Width Tradeoffs for Transformers on Graph Tasks
Gilad Yehudai, Clayton Sanford, Maya Bechler-Speicher, Orr Fischer, Ran Gilad-Bachrach, Amir Globerson

Dimension-Adapted Momentum Outscales SGD
Damien Ferbach, Katie Everett, Gauthier Gidel, Elliot Paquette, Courtney Paquette

Fast Training of Large Kernel Models with Delayed Projections
Amirhesam Abedsoltan, Siyuan Ma*, Parthe Pandit, Mikhail Belkin

Generalized Top-𝓀 Mallows Model for Ranked Choices
Shahrzad Haddadan, Sara Ahmadian

LODGE: Level-of-Detail Large-Scale Gaussian Splatting with Efficient Rendering
Jonas Kulhanek, Marie-Julie Rakotosaona, Fabian Manhardt, Christina Tsalicoglou, Michael Niemeyer, Torsten Sattler, Songyou Peng, Federico Tombari

Object-Centric 3D Motion Field for Robot Learning from Human Videos
Zhao-Heng Yin, Sherry Yang, Pieter Abbeel

On Agnostic PAC Learning in the Small Error Regime
Julian Asilis, Mikael Møller Høgsgaard, Grigoris Velegkas

On Traceability in ℓp Stochastic Convex Optimization
Sasha Voitovych, Mahdi Haghifam, Idan Attias, Gintare Karolina Dziugaite, Roi Livni, Daniel M. Roy

OpenWorldSAM: Extending SAM2 for Universal Image Segmentation with Language Prompts
Shiting Xiao, Rishabh Kabra, Yuhang Li, Donghyun Lee, João Carreira, Priyadarshini Panda

Pass@K Policy Optimization: Solving Harder Reinforcement Learning Problems
Christian Walder, Deep Karkhanis

PiKE: Adaptive Data Mixing for Large-Scale Multi-Task Learning Under Low Gradient Conflicts
Zeman Li*, Yuan Deng, Peilin Zhong, Meisam Razaviyayn, Vahab Mirrokni

Plasticity as the Mirror of Empowerment
David Abel, Michael Bowling, André Barreto, Will Dabney, Shi Dong, Steven Hansen, Anna Harutyunyan, Khimya Khetarpal, Clare Lyle, Razvan Pascanu, Georgios Piliouras, Doina Precup, Jonathan Richens, Mark Rowland, Tom Schaul, Satinder Singh

Private Hyperparameter Tuning with Ex-Post Guarantee
Badih Ghazi, Pritish Kamath, Alexander Knop, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang

Private Set Union with Multiple Contributions
Travis Dick, Haim Kaplan, Alex Kulesza, Uri Stemmer, Ziteng Sun, Ananda Theertha Suresh

Progressive Inference-Time Annealing of Diffusion Models for Sampling from Boltzmann Densities
Tara Akhound-Sadegh, Jungyoon Lee, Avishek Joey Bose, Valentin De Bortoli, Arnaud Doucet, Michael M. Bronstein, Dominique Beaini, Siamak Ravanbakhsh, Kirill Neklyudov, Alexander Tong

Quantization-Free Autoregressive Action Transformer
Ziyad Sheebaelhamd, Michael Tschannen, Michael Muehlebach, Claire Vernade

Reconstruction and Secrecy Under Approximate Distance Queries
Shay Moran, Elizaveta Nesterova

Regret Bounds for Adversarial Contextual Bandits with General Function Approximation and Delayed Feedback
Orin Levy, Liad Erez, Alon Cohen, Yishay Mansour

ROGR: Relightable 3D Objects Using Generative Relighting
Jiapeng Tang, Matthew Lavine, Dor Verbin, Stephan J. Garbin, Matthias Nießner, Ricardo Martin Brualla, Pratul P. Srinivasan, Philipp Henzler

Stable Gradients for Stable Learning at Scale in Deep Reinforcement Learning
Roger Creus Castanyer, Johan Obando-Ceron, Lu Li, Pierre-Luc Bacon, Glen Berseth, Aaron Courville,
Pablo Samuel Castro

Streaming Attention Approximation via Discrepancy Theory
Ekaterina Kochetkova, Kshiteej Sheth, Insu Han, Amir Zandieh, Michael Kapralov

The World Is Bigger: A Computationally-Embedded Perspective on the Big World Hypothesis
Alex Lewandowski, Aditya A. Ramesh, Edan Meyer, Dale Schuurmans, Marlos C. Machado

Universal Sequence Preconditioning
Annie Marsden, Elad Hazan

3DLLM-Mem: Long-Term Spatial-Temporal Memory for Embodied 3D Large Language Model
Wenbo Hu, Yining Hong, Yanjun Wang, Leison Gao, Zibu Wei, Xingcheng Yao, Nanyun Peng, Yonatan Bitton, Idan Szpektor, Kai-Wei Chang

3D-Prover: Diversity Driven Theorem Proving With Determinantal Point Processes
Sean Lamont, Christian Walder, Amir Dezfouli, Paul Montague, Michael Norrish

A Unified Approach to Submodular Maximization Under Noise
Kshipra Bhawalkar, Yang Cai, Zhe Feng, Christopher Liaw, Tao Lin*

Additive Models Explained: A Computational Complexity Approach
Shahaf Bassan, Michal Moshkovitz, Guy Katz

AI Debate Aids Assessment of Controversial Claims
Salman Rahman, Sheriff Issaka, Ashima Suvarna, Genglin Liu, James Shiffer, Jaeyoung Lee, Md Rizwan Parvez, Hamid Palangi, Shi Feng, Nanyun Peng, Yejin Choi, Julian Michael, Liwei Jiang, Saadia Gabriel

AI-Generated Video Detection via Perceptual Straightening
Christian Internò, Robert Geirhos, Markus Olhofer, Sunny Liu, Barbara Hammer, David Klindt

Analyzing Similarity Metrics for Data Selection for Language Model Pretraining
Dylan Sam*, Ayan Chakrabarti, Afshin Rostamizadeh, Srikumar Ramalingam, Gui Citovsky, Sanjiv Kumar

An Ellipsoid Algorithm for Online Convex Optimization
Zakaria Mhammedi

Beyond Least Squares: Uniform Approximation and the Hidden Cost of Misspecification
Davide Maran, Csaba Szepesvári

BioReason: Incentivizing Multimodal Biological Reasoning within a DNA-LLM Model
Adibvafa Fallahpour, Andrew Magnuson, Purav Gupta, Shihao Ma, Jack Naimer, Arnav Shah, Haonan Duan, Omar Ibrahim, Hani Goodarzi, Chris J. Maddison, Bo Wang

Bridging Sign and Spoken Languages: Pseudo Gloss Generation for Sign Language Translation
Jianyuan Guo*, Peike Li, Trevor Cohn

Closed-Form Training Dynamics Reveal Learned Features and Linear Structure in Word2Vec-Like Models
Dhruva Karkada, James B. Simon, Yasaman Bahri, Michael R. DeWeese

Consistently Simulating Human Personas with Multi-Turn Reinforcement Learning
Marwa Abdulhai, Ryan Cheng, Donovan Clay, Tim Althoff, Sergey Levine, Natasha Jaques

Constructing an Optimal Behavior Basis for the Option Keyboard
Lucas N. Alegre, Ana L. C. Bazzan, André Barreto, Bruno C. da Silva

Contextual Dynamic Pricing with Heterogeneous Buyers
Thodoris Lykouris, Sloan Nietert, Princewill Okoroafor, Chara Podimata, Julian Zimmert

Data-Adaptive Exposure Thresholds Under Network Interference
Vydhourie Thiyageswaran, Tyler H. McCormick, Jennifer Brennan

DataRater: Meta-Learned Dataset Curation
Dan A. Calian, Gregory Farquhar, Iurii Kemaev, Luisa M. Zintgraf, Matteo Hessel, Jeremy Shar, Junhyuk Oh, András György, Tom Schaul, Jeffrey Dean, Hado van Hasselt, David Silver

Differentially Private Bilevel Optimization: Efficient Algorithms with Near-Optimal Rates
Andrew Lowy, Daogao Liu

Dimension-free Score Matching and Time Bootstrapping for Diffusion Models
Syamantak Kumar*, Dheeraj Nagaraj, Purnamrita Sarkar

EA3D: Online Open-World 3D Object Extraction from Streaming Videos
Xiaoyu Zhou, Jingqi Wang, Yuang Jia, Yongtao Wang, Deqing Sun, Ming-Hsuan Yang

Efficient Adaptive Federated Optimization
Su Hyeong Lee, Sidharth Sharma, Manzil Zaheer, Tian Li

Efficient Data Selection at Scale via Influence Distillation
Mahdi Nikdan*, Vincent Cohen-Addad, Dan Alistarh, Vahab Mirrokni

Efficient Spectral Control of Partially Observed Linear Dynamical Systems
Anand Brahmbhatt, Gon Buzaglo, Sofiia Druchyna, Elad Hazan

Efficiently Verifiable Proofs of Data Attribution
Ari Karchmer, Martin Pawelcyzk, Seth Neel

Emergent Temporal Correspondences from Video Diffusion Transformers
Jisu Nam, Soowon Son, Dahyun Chung, Jiyoung Kim, Siyoon Jin, Junhwa Hur, Seungryong Kim

Enhancing Personalized Multi-Turn Dialogue with\nCuriosity Reward
Yanming Wan*, Jiaxing Wu, Marwa Abdulhai, Lior Shani, Natasha Jaques

Escaping Collapse: The Strength of Weak Data for Large Language Model Training
Kareem Amin, Sara Babakniya, Alex Bie, Weiwei Kong, Umar Syed, Sergei Vassilvitskii

EUGens: Efficient, Unified, and General Dense Layers
Sang Min Kim, Byeongchan Kim, Arijit Sehanobish, Somnath Basu Roy Chowdhury, Rahul Kidambi, Dongseok Shim, Avinava Dubey, Snigdha Chaturvedi, Min-hwan Oh, Krzysztof Choromanski

Exact and Linear Convergence for Federated Learning Under Arbitrary Client Participation Is Attainable
Bicheng Ying, Zhe Li, HaiboYag

Exploring Diffusion Transformer Designs via Grafting
Keshigeyan Chandrasegaran, Michael Poli, Daniel Y. Fu, Dongjun Kim, Lea M. Hadzic, Manling Li, Agrim Gupta, Stefano Massaroli, Azalia Mirhoseini, Juan Carlos Niebles, Stefano Ermon, Li Fei-Fei

Exploring the Limits of Strong Membership Inference Attacks on Large Language Models
Jamie Hayes, Ilia Shumailov, Christopher A. Choquette-Choo, Matthew Jagielski, Georgios Kaissis, Milad Nasr, Meenatchi Sundaram Muthu Selva Annamalai, Niloofar Mireshghallah, Igor Shilov, Matthieu Meeus, Yves-Alexandre de Montjoye, Katherine Lee, Franziska Boenisch, Adam Dziedzic, A. Feder Cooper

Fast Attention Mechanisms: A Tale of Parallelism
Jingwen Liu, Hantao Yu, Clayton Sanford, Alexandr Andoni, Daniel Hsu

Fast Last-Iterate Convergence of SGD in the Smooth Interpolation Regime
Amit Attia, Matan Schliserman, Uri Sherman, Tomer Koren

Fine-Grained Preference Optimization Improves Spatial Reasoning in VLMs
Yifan Shen, Yuanzhe Liu, Jingyuan Zhu, Xu Cao, Xiaofeng Zhang, Yixiao He, Wenming Ye, James M. Rehg, Ismini Lourentzou

Force Prompting: Video Generation Models Can Learn and Generalize Physics-based Control Signals
Nate Gillman, Charles Herrmann, Michael Freeman, Daksh Aggarwal, Evan Luo, Deqing Sun, Chen Sun

From Contextual Combinatorial Semi-Bandits to Bandit List Classification: Improved Sample Complexity with Sparse Rewards
Liad Erez, Tomer Koren

From Dormant to Deleted: Tamper-Resistant Unlearning Through Weight-Space Regularization
Shoaib Ahmed Siddiqui, Adrian Weller, David Krueger, Gintare Karolina Dziugaite, Michael C. Mozer, Eleni Triantafillou

From Style to Facts: Mapping the Boundaries of Knowledge Injection with Finetuning
Eric Zhao, Pranjal Awasthi, Nika Haghtalab

GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation
Sohyun Lee, Yeho Gwon, Lukas Hoyer, Suha Kwak

Gatekeeper: Improving Model Cascades Through Confidence Tuning
Stephan Rabanser*, Nathalie Rauschmayr, Achin Kulshrestha, Petra Poklukar, Wittawat Jitkrittum, Sean Augenstein, Congchao Wang, Federico Tombari

Generating Creative Chess Puzzles
Xidong Feng, Vivek Veeriah, Marcus Chiam, Michael Dennis, Ryan Pachauri, Thomas Tumiel, Federico Barbero*, Johan Obando-Ceron*, Jiaxin Shi, Satinder Singh, Shaobo Hou, Nenad Tomašev, Tom Zahavy

GIST: Greedy Independent Set Thresholding for Max-Min Diversification with Submodular Utility
Matthew Fahrbach, Srikumar Ramalingam, Morteza Zadimoghaddam, Sara Ahmadian, Gui Citovsky, Giulia DeSalvo

Heterogeneous Swarms: Jointly Optimizing Model Roles and Weights for Multi-LLM Systems
Shangbin Feng*, Zifeng Wang, Palash Goyal, Yike Wang, Weijia Shi, Huang Xia, Hamid Palangi, Luke Zettlemoyer, Yulia Tsvetkov, Chen-Yu Lee, Tomas Pfister

Hierarchical Retrieval: The Geometry and a Pretrain-Finetune Recipe
Chong You, Rajesh Jayaram, Ananda Theertha Suresh, Robin Nittka, Felix Yu, Sanjiv Kumar

High-Dimensional Calibration from Swap Regret
Maxwell Fishelson, Noah Golowich, Mehryar Mohri, Jon Schneider

HoliGS: Holistic Gaussian Splatting for Embodied View Synthesis
Xiaoyuan Wang, Yizhou Zhao, Botao Ye, Xiaojun Shan, Weijie Lyu, Lu Qi, Kelvin C.K. Chan, Yinxiao Li, Ming-Hsuan Yang

Hybrid Latent Reasoning via Reinforcement Learning
Zhenrui Yue, Bowen Jin, Huimin Zeng, Honglei Zhuang, Zhen Qin, Jinsung Yoon, Lanyu Shang, Jiawei Han, Dong Wang

IllumiCraft: Unified Geometry and Illumination Diffusion for Controllable Video Generation
Yuanze Lin, Yi-Wen Chen, Yi-Hsuan Tsai, Ronald Clark, Ming-Hsuan Yang

Improved Balanced Classification with Theoretically Grounded Loss Functions
Corinna Cortes, Mehryar Mohri, Yutao Zhong

Improved Best-of-Both-Worlds Regret for Bandits with Delayed Feedback
Ofir Schlisselberg, Tal Lancewicki, Peter Auer, Yishay Mansour

Improved Scaling Laws in Linear Regression via Data Reuse
Licong Lin, Jingfeng Wu, Peter L. Bartlett

Individual Regret in Cooperative Stochastic Multi-Armed Bandits
Idan Barnea, Tal Lancewicki, Yishay Mansour

Informed Correctors for Discrete Diffusion Models
Yixiu Zhao, Jiaxin Shi, Feng Chen, Shaul Druckmann, Lester Mackey, Scott Linderman

InvisibleInk: High-Utility and Low-Cost Text Generation with Differential Privacy
Vishnu Vinod, Krishna Pillutla, Abhradeep Thakurta

Isotropic Noise in Stochastic and Quantum Convex Optimization
Annie Marsden, Liam O'Carroll, Aaron Sidford, Chenyi Zhang

Kernel Density Steering: Inference-Time Scaling via Mode Seeking for Image Restoration
Yuyang Hu*, Kangfu Mei, Mojtaba Sahraee-Ardakan, Ulugbek S. Kamilov, Peyman Milanfar, Mauricio Delbracio

Learning Efficient Fuse-and-Refine for Feed-Forward 3D Gaussian Splatting
Yiming Wang, Lucy Chai, Xuan Luo, Michael Niemeyer, Manuel Lagunas, Stephen Lombardi, Siyu Tang, Tiancheng Sun

Large Stepsizes Accelerate Gradient Descent for Regularized Logistic Regression
Jingfeng Wu, Pierre Marion, Peter L. Bartlett

Learning Long Range Dependencies Through Time Reversal Symmetry Breaking
Guillaume Pourcel, Maxence Ernoult

Learning Neural Exposure Fields for View Synthesis
Michael Niemeyer, Fabian Manhardt, Marie-Julie Rakotosaona, Michael Oechsle, Christina Tsalicoglou, Keisuke Tateno, Jonathan T. Barron, Federico Tombari

Length Generalization via Auxiliary Tasks
Pranjal Awasthi, Anupam Gupta, Ravi Kumar

LocDiff: Identifying Locations on Earth by Diffusing in the Hilbert Space
Zhangyu Wang, Zeping Liu, Jielu Zhang, Zhongliang Zhou, Qian Cao, Nemin Wu, Lan Mu, Yang Song, Yiqun Xie, Ni Lao, Gengchen Mai

Machine Unlearning Under Overparameterization
Jacob L. Block, Aryan Mokhtari, Sanjay Shakkottai

Marginal-Nonuniform PAC Learnability
Steve Hanneke, Shay Moran, Maximilian Thiessen

Martingale Posterior Neural Networks for Fast Sequential Decision Making
Gerardo Duran-Martin, Leandro Sánchez-Betancourt, Álvaro Cartea, Kevin Murphy

Matryoshka Pilot: Learning to Drive Black-Box LLMs with LLMs
Changhao Li, Yuchen Zhuang, Rushi Qiang, Haotian Sun, Hanjun Dai, Chao Zhang, Bo Dai

Mechanism Design via the Interim Relaxation
Kshipra Bhawalkar, Marios Mertzanidis, Divyarthi Mohan, Alexandros Psomas

Mind the GAP! The Challenges of Scale in Pixel-Based Deep Reinforcement Learning (see blog post)
Ghada Sokar, Pablo Samuel Castro

Mixture-of-Recursions: Learning Dynamic Recursive Depths for Adaptive Token-Level Computation
Sangmin Bae, Yujin Kim, Reza Bayat, Sungnyun Kim, Jiyoun Ha, Tal Schuster, Adam Fisch, Hrayr Harutyunyan, Ziwei Ji, Aaron Courville, Se-Young Yun

MLE-STAR: Machine Learning Engineering Agent via Search and Targeted Refinement (see blog post)
Jaehyun Nam*, Jinsung Yoon, Jiefeng Chen, Jinwoo Shin, Sercan Ö. Arik, Tomas Pfister

Multiclass Loss Geometry Matters for Generalization of Gradient Descent in Separable Classification
Matan Schliserman, Tomer Koren

Nearly-Linear Time and Massively Parallel Algorithms for 𝓀-anonymity
Kevin Aydin, Honghao Lin*, David P. Woodruff, Peilin Zhong

Nested Learning: The Illusion of Deep Learning Architectures (see blog post)
Ali Behrouz, Meisam Razaviyayn, Peilin Zhong, Vahab Mirrokni

No-Regret Online Autobidding Algorithms in First-Price Auctions
Yilin Li, Yuan Deng, Wei Tang, Hanrui Zhang

Noise Hypernetworks: Amortizing Test-Time Compute in Diffusion Models
Luca Eyring, Shyamgopal Karthik, Alexey Dosovitskiy, Nataniel Ruiz, Zeynep Akata

Non-stationary Bandit Convex Optimization: A Comprehensive Study
Xiaoqi Liu, Dorian Baudry, Julian Zimmert, Patrick Rebeschini, Arya Akhavan

Object-X: Learning to Reconstruct Multi-Modal 3D Object Representations
Gaia Di Lorenzo, Federico Tombari, Marc Pollefeys, Daniel Barath

On the Complexity of Finding Stationary Points in Nonconvex Simple Bilevel Optimization
Jincheng Cao, Ruichen Jiang, Erfan Yazdandoost Hamedani, Aryan Mokhtari

On the Emergence of Linear Analogies in Word Embeddings
Daniel J. Korchinski, Dhruva Karkada, Yasaman Bahri, Matthieu Wyart

On Union-Closedness of Language Generation
Steve Hanneke, Anay Mehrotra, Amin Karbasi, Grigoris Velegkas

Optimal Mistake Bounds for Transductive Online Learning
Zachary Chase, Steve Hanneke, Shay Moran, Jonathan Shafer

Optimal Rates in Continual Linear Regression via Increasing Regularization
Ran Levinstein, Amit Attia, Matan Schliserman, Uri Sherman, Tomer Koren, Daniel Soudry, Itay Evron

Path-Specific Effects for Pulse-Oximetry Guided Decisions in Critical Care
Kevin Zhang, Yonghan Jung, Divyat Mahajan, Karthikeyan Shanmugam, Shalmali Joshi

Predictive Coding Enhances Meta-RL to Achieve Interpretable Bayes-Optimal Belief Representation Under Partial Observability
Po-Chen Kuo, Han Hou, Will Dabney, Edgar Y. Walker

Principled Model Routing for Unknown Mixtures of Source Domains
Christoph Dann, Yishay Mansour, Teodor V. Marinov, Mehryar Mohri

Privacy Reasoning in Ambiguous Contexts
Ren Yi, Octavian Suciu, Adrià Gascón, Sarah Meiklejohn, Eugene Bagdasarian, Marco Gruteser

Private Geometric Median in Nearly-Linear Time
Syamantak Kumar, Daogao Liu, Kevin Tian, Chutong Yang

Probably Approximately Precision and Recall Learning
Lee Cohen, Yishay Mansour, Shay Moran, Han Shao

ProDyG: Progressive Dynamic Scene Reconstruction via Gaussian Splatting from Monocular Videos
Shi Chen, Erik Sandström, Sandro Lombardi, Siyuan Li, Martin R. Oswald

Provable Meta-Learning with Low-Rank Adaptations
Jacob L. Block, Sundararajan Srinivasan, Liam Collins, Aryan Mokhtari, Sanjay Shakkottai

Quantifying Cross-Modality Memorization in Vision-Language Models
Yuxin Wen*, Yangsibo Huang, Tom Goldstein, Ravi Kumar, Badih Ghazi, Chiyuan Zhang

RAT: Bridging RNN Efficiency and Attention Accuracy via Chunk-Based Sequence Modeling
Xiuying Wei, Anunay Yadav, Razvan Pascanu, Caglar Gulcehre

Recursive Inference Scaling: A Winning Path to Scalable Inference in Language and Multimodal Systems
Ibrahim Alabdulmohsin, Xiaohua Zhai

REINFORCE Converges to Optimal Policies with Any Learning Rate
Samuel Robertson, Thang D. Chu, Bo Dai, Dale Schuurmans, Csaba Szepesvári, Jincheng Mei

Reinforcement Learning with Backtracking Feedback
Bilgehan Sel*, Vaishakh Keshava (GDM), Phillip Wallis, Lukas Rutishauser, Ming Jin, Dingcheng Li

Rendering-Aware Reinforcement Learning for Vector Graphics Generation
Juan A. Rodriguez, Haotian Zhang, Abhay Puri, Aarash Feizi, Rishav Pramanik, Pascal Wichmann, Arnab Mondal, Mohammad Reza Samsami, Rabiul Awal, Perouz Taslakian, Spandana Gella, Sai Rajeswar, David Vazquez, Christopher Pal, Marco Pedersoli

Replicable Online Pricing
Kiarash Banihashem, MohammadHossein Bateni, Hossein Esfandiari, Samira Goudarzi, MohammadTaghi Hajiaghayi

Robust and Diverse Multi-Agent Learning via Rational Policy Gradient
Niklas Lauffer, Ameesh Shah, Micah Carroll, Sanjit A. Seshia, Stuart Russell, Michael Dennis

Robust Contextual Pricing
Anupam Gupta, Guru Guruganesh, Renato Paes Leme, Jon Schneider

Robust LLM Alignment via Distributionally Robust Direct Preference Optimization
Zaiyan Xu, Sushil Vemuri, Kishan Panaganti, Dileep Kalathil, Rahul Jain, Deepak Ramachandran

ROGR: Relightable 3D Objects Using Generative Relighting
Jiapeng Tang, Matthew Lavine, Dor Verbin, Stephan J. Garbin, Matthias Nießner, Ricardo Martin Brualla, Pratul P. Srinivasan, Philipp Henzler

Sampling 3D Molecular Conformers with Diffusion Transformers
J. Thorben Frank, Winfried Ripken, Gregor Lied, Klaus Robert Müller, Oliver T. Unke, Stefan Chmiela

Scalable In-context Ranking with Generative Models
Nilesh Gupta, Chong You, Srinadh Bhojanapalli, Sanjiv Kumar, Inderjit Dhillon, Felix Yu

Scaling Embedding Layers in Language Models
Da Yu, Edith Cohen, Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Daogao Liu, Chiyuan Zhang

Scaling Image Geo-Localization to Continent Level
Philipp Lindenberger*, Paul-Edouard Sarlin, Jan Hosang, Marc Pollefeys, Simon Lynen, Eduard Trulls

Self-Boost via Optimal Retraining: An Analysis via Approximate Message Passing
Adel Javanmard, Rudrajit Das, Alessandro Epasto, Vahab Mirrokni

Self-Improving Embodied Foundation Models
Seyed Kamyar Seyed Ghasemipour*, Ayzaan Wahid, Jonathan Tompson, Pannag Sanketi, Igor Mordatch

SensorLM: Learning the Language of Wearable Sensors (see blog post)
Yuwei Zhang, Kumar Ayush, Siyuan Qiao, A. Ali Heydari, Girish Narayanswamy*, Maxwell A. Xu*, Ahmed A. Metwally, Shawn Xu, Jake Garrison, Xuhai Xu, Tim Althoff, Yun Liu, Pushmeet Kohli, Jiening Zhan, Mark Malhotra, Shwetak Patel, Cecilia Mascolo, Xin Liu, Daniel McDuff, Yuzhe Yang

Sequentially Auditing Differential Privacy
Tomás González, Mateo Dulce Rubio, Aaditya Ramdas, Mónica Ribero

Spark Transformer: Reactivating Sparsity in\nTransformer FFN and Attention
Chong You, Kan Wu*, Zhipeng Jia*, Lin Chen, Srinadh Bhojanapalli, Jiaxian Guo, Utku Evci, Jan Wassenberg, Praneeth Netrapalli, Jeremiah J. Willcock, Suvinay Subramanian, Felix Chern, Alek Andreev, Shreya Pathak, Felix Yu, Prateek Jain, Henry M. Levy, David E. Culler, Sanjiv Kumar

Sparse Gaussian Processes: Structured Approximations and Power-EP Revisited
Thang D. Bui, Michalis K. Titsias

SpectraLDS: Provable Distillation for Linear Dynamical Systems
Devan Shah, Shlomo Fortgang, Sofiia Druchyna, Elad Hazan

SPRINT: Enabling Interleaved Planning and Parallelized Execution in Reasoning Models
Emil Biju, Shayan Talaei, Zhemin Huang, Mohammadreza Pourreza, Azalia Mirhoseini, Amin Saberi

Stable Cinemetrics : Structured Taxonomy and Evaluation for Professional Video Generation
Agneet Chatterjee, Rahim Entezari, Maksym Zhuravinskyi, Max Lapin, Reshinth Adithyan, Amit Raj, Chitta Baral, Yezhou Yang, Varun Jampani

SWE-SQL: Illuminating LLM Pathways to Solve User SQL Issues in Real-World Applications
Jinyang Li, Xiaolong Li, Ge Qu, Per Jacobsson, Bowen Qin, Binyuan Hui, Shuzheng Si, Nan Huo, Xiaohan Xu, Yue Zhang, Ziwei Tang, Yuanshuai Li, Florensia Widjaja, Xintong Zhu, Feige Zhou, Yongfeng Huang, Yannis Papakonstantinou, Fatma Ozcan, Chenhao Ma, Reynold Cheng

Synthesize Privacy-Preserving High-Resolution Images via Private Textual Intermediaries
Haoxiang Wang, Zinan Lin, Da Yu, Huishuai Zhang

Temporal Chain of Thought: Long-Video Understanding by Thinking in Frames
Anurag Arnab, Ahmet Iscen, Mathilde Caron, Alireza Fathi, Cordelia Schmid

The Cost of Compression: Tight Quadratic Black-Box Attacks on Sketches for ℓ2 Norm Estimation
Sara Ahmadian, Edith Cohen, Uri Stemmer

The Emergence of Sparse Attention: Impact of Data Distribution and Benefits of Repetition
Nicolas Zucchet, Francesco D'Angelo, Andrew Lampinen, Stephanie Chan

Tight Bounds for Answering Adaptively Chosen Concentrated Queries
Emma Rapoport, Edith Cohen, Uri Stemmer

Titans: Learning to Memorize at Test Time
Ali Behrouz, Peilin Zhong, Vahab Mirrokni

Tracing the Representation Geometry of Language Models from Pretraining to Post-Training
Melody Zixuan Li, Kumar Krishna Agrawal, Arna Ghosh, Komal Kumar Teru, Adam Santoro, Guillaume Lajoie, Blake A. Richards

Training-Free Online Video Step Grounding
Luca Zanella, Massimiliano Mancini, Yiming Wang, Alessio Tonioni, Elisa Ricci

UMAMI: Unifying Masked Autoregressive Models and Deterministic Rendering for View Synthesis
Tung Le, Tuan Pham, Tung Nguyen, Deying Kong, Xiaohui Xie, Stephan Mandt

Uncovering a Universal Abstract Algorithm for Modular Addition in Neural Networks
Gavin McCracken, Gabriela Moisescu-Pareja, Vincent Létourneau, Doina Precup, Jonathan Love

Understanding Challenges to the Interpretation of\nDisaggregated Evaluations of Algorithmic Fairness
Stephen R. Pfohl, Natalie Harris, Chirag Nagpal, David Madras, Vishwali Mhasawade, Olawale Salaudeen, Awa Dieng, Shannon Sequeira, Santiago Arciniegas, Lillian Sung, Nnamdi Ezeanochie, Heather Cole-Lewis, Katherine Heller, Sanmi Koyejo, Alexander D'Amour

Understanding Outer Optimizers in Local SGD:\nLearning Rates, Momentum, and Acceleration
Ahmed Khaled*, Satyen Kale*, Arthur Douillard, Chi Jin, Rob Fergus, Manzil Zaheer*

Unifying Re-Identification, Attribute Inference, and Data Reconstruction Risks in Differential Privacy
Bogdan Kulynych, Juan Felipe Gomez, Georgios Kaissis, Jamie Hayes, Borja Balle, Flavio P. Calmon, Jean Louis Raisaro

Universal Sequence Preconditioning
Annie Marsden, Elad Hazan

VESSA: Video-based objEct-centric Self-Supervised Adaptation for Visual Foundation Models
Jesimon Barreto, Carlos Caetano, André Araujo, William Robson Schwartz

When Do Transformers Outperform Feedforward and Recurrent Networks? A Statistical Perspective
Alireza Mousavi-Hosseini, Clayton Sanford, Denny Wu, Murat A. Erdogdu

Zero-Shot Performance Prediction for Probabilistic Scaling Laws
Viktoria Schram, Markus Hiller, Daniel Beck, Trevor Cohn

Robo2VLM: Improving Visual Question Answering Using Large-Scale Robot Manipulation Data
Kaiyuan Chen, Shuangyu Xie, Zehan Ma, Pannag R. Sanketi, Ken Goldberg

Whose View of Safety? A Deep DIVE Dataset for Pluralistic Alignment of Text-to-Image Models
Charvi Rastogi, Tian Huey Teh, Pushkar Mishra, Roma Patel, Ding Wang, Mark Díaz, Alicia Parrish,
Aida Mostafazadeh Davani, Zoe Ashwood, Michela Paganini, Vinodkumar Prabhakaran, Verena Rieser, Lora Aroyo

Evaluating Generalization Capabilities of LLM-Based Agents in Mixed-Motive Scenarios Using Concordia
Chandler Smith, Marwa Abdulhai, Manfred Diaz, Marko Tesic, Rakshit S. Trivedi, Alexander Sasha Vezhnevets, Lewis Hammond, Jesse Clifton, Minsuk Chang, Edgar A. Duéñez-Guzmán, John P. Agapiou, Jayd Matyas, Danny Karmon, Dylan Hadfield-Menell, Natasha Jaques, Tim Baarslag, Jose Hernandez-Orallo, Joel Z. Leibo

GC4NC: A Benchmark Framework for Graph Condensation on Node Classification with New Insights
Shengbo Gong, Juntong Ni, Noveen Sachdeva, Carl Yang, Wei Jin

HouseLayout3D: A Benchmark and Training-free Baseline for 3D Layout Estimation in the Wild
A. Feder Cooper, Christopher A. Choquette-Choo, Miranda Bogen, Kevin Klyman, Matthew Jagielski, Katja Filippova, Ken Ziyu Liu, Alexandra Chouldechova, Jamie Hayes, Yangsibo Huang, Eleni Triantafillou, Peter Kairouz, Nicole Mitchell, Niloofar Mireshghallah, Abigail Z. Jacobs, James Grimmelmann, Vitaly Shmatikov, Christopher De Sa, Ilia Shumailov, Andreas Terzis, Solon Barocas, Jennifer Wortman Vaughan, Danah Boyd, Yejin Choi, Sanmi Koyejo, Fernando Delgado, Percy Liang, Daniel E. Ho, Pamela Samuelson, Miles Brundage, David Bau, Seth Neel, Hanna Wallach, Amy B. Cyphert, Mark A. Lemley, Nicolas Papernot, Katherine Lee

Massive Sound Embedding Benchmark (MSEB)
Georg Heigold, Ehsan Variani, Tom Bagby, Cyril Allauzen, Ji Ma, Shankar Kumar, Michael Riley

Meta-World+: An Improved, Standardized, RL Benchmark
Reginald McLean, Evangelos Chatzaroulas, Luc McCutcheon, Frank Röder, Zhanpeng He, Tianhe Yu, Ryan Julian, K.R. Zentner, Jordan Terry, Isaac Woungang, Nariman Farsad, Pablo Samuel Castro

NAVIX: Scaling MiniGrid Environments with JAX
Eduardo Pignatelli, Jarek Liesen, Robert Tjarko Lange, Chris Lu, Pablo Samuel Castro, Laura Toni

RADAR: Benchmarking Language Models on Imperfect Tabular Data
Ken Gu*, Zhihan Zhang, Kate Lin, Yuwei Zhang, Akshay Paruchuri, Hong Yu, Mehran Kazemi, Kumar Ayush, A. Ali Heydari, Maxwell A. Xu, Girish Narayanswamy, Yun Liu, Ming-Zher Poh, Yuzhe Yang, Mark Malhotra, Shwetak Patel, Hamid Palangi, Xuhai Xu, Daniel McDuff, Tim Althoff, Xin Liu

Risk Management for Mitigating Benchmark Failure Modes: BenchRisk
Sean McGregor, Victor Lu, Vassil Tashev, Armstrong Foundjem, Aishwarya Ramasethu, Mahdi Kazemi, Chris Knotz, Kongtao Chen, Alicia Parrish, Anka Reuel, Heather Frase

QuestBench: Can LLMs Ask the Right Question to Acquire Information in Reasoning Tasks?
Belinda Z. Li*, Been Kim, Zi Wang

Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy and Research
A. Feder Cooper, Christopher A. Choquette-Choo, Miranda Bogen, Kevin Klyman, Matthew Jagielski, Katja Filippova, Ken Ziyu Liu, Alexandra Chouldechova, Jamie Hayes, Yangsibo Huang, Eleni Triantafillou, Peter Kairouz, Nicole Mitchell, Niloofar Mireshghallah, Abigail Z. Jacobs, James Grimmelmann, Vitaly Shmatikov, Christopher De Sa, Ilia Shumailov, Andreas Terzis, Solon Barocas, Jennifer Wortman Vaughan, Danah Boyd, Yejin Choi, Sanmi Koyejo, Fernando Delgado, Percy Liang, Daniel E. Ho, Pamela Samuelson, Miles Brundage, David Bau, Seth Neel, Hanna Wallach, Amy B. Cyphert, Mark A. Lemley, Nicolas Papernot, Katherine Lee

Understanding Prompt Tuning and In-Context Learning via Meta-Learning
Tim Genewein, Li Kevin Wenliang, Jordi Grau-Moya, Anian Ruoss, Laurent Orseau, Marcus Hutter

Capturing Individual Human Preferences with Reward Features
André Barreto, Vincent Dumoulin, Yiran Mao, Mark Rowland, Nicolas Perez-Nieves, Bobak Shahriari, Yann Dauphin, Doina Precup, Hugo Larochelle

Dynamic Diffusion Schrödinger Bridge in Astrophysical Observational Inversions
Ye Zhu, Duo Xu, Zhiwei Deng, Jonathan C. Tan, Olga Russakovsky