Google at ICML 2026

A General Framework for Dynamic Consistent Submodular Maximization
Paul Dütting, Federico Fusco, Silvio Lattanzi, Ashkan Norouzi-Fard, Ola Svensson, Morteza Zadimoghaddam

A KL-Regularization Framework for Learning to Plan With Adaptive Priors
Álvaro Serra-Gomez, Daniel Jarne Ornia, Dhruva Tirumala, Thomas Moerland

A Model of Errors in Transformers
Suvrat Raju, Praneeth Netrapalli

A Positive Case for Faithfulness: LLM Self-Explanations Help Predict Model Behavior
Harry Mayne, Justin Singh Kang, Dewi Gould, Kannan Ramchandran, Adam Mahdi, Noah Y. Siegel

A Theoretical Framework for Modular Learning of Robust Generative Models
Corinna Cortes, Mehryar Mohri, Yutao Zhong

ACTG-ARL: Differentially Private Conditional Text Generation With RL-Boosted Control
Yuzheng Hu, Ryan McKenna, Da Yu, Shanshan Wu, Han Zhao, Zheng Xu, Peter Kairouz

Adaptively Robust Resettable Streaming
Edith Cohen, Elena Gribelyuk, Jelani Nelson, Uri Stemmer

Allocating Variance to Maximize Expectation
Renato Purita Paes Leme, Clifford Stein, Yifeng Teng, Pratik Worah

Alterbute: Editing Intrinsic Attributes Of Objects in Images
Tal Reiss, Daniel Winter, Matan Cohen, Alex Rav-Acha, Yael Pritch, Ariel Shamir, Yedid Hoshen

ATLAS: Learning to Optimally Memorize the Context at Test Time
Ali Behrouz, Zeman Li, Praneeth Kacham, Majid Daliri, Yuan Deng, Peilin Zhong, Meisam Razaviyayn, Vahab Mirrokni

AutoNumerics-Zero: Automated Discovery Of State-of-the-Art Mathematical Functions
Esteban Real, Mirko Rossini, Connal de Souza, Manav Garg, Moritz Firsching, Quoc V. Le, Yao Chen, Akhil Verghese, Ekin Dogus Cubuk*, David H. Park*

Autoregressive Language Models Are Secretly Energy-Based Models: Insights Into The Lookahead Capabilities Of Next-Token Prediction
Mathieu Blondel, Michaël E. Sander, Germain Vivier-Ardisson, Tianlin Liu, Vincent Roulet

Balancing Plasticity And Stability With Fast And Slow Successor Features
Raymond Chua, Doina Precup, Blake Richards

Best Of Both Worlds: Multimodal Reasoning And Generation Via Unified Discrete Flow Matching
Onkar Susladkar, Tushar Prakash, Gayatri Deshmukh, Kiet Nguyen, Jiaxun Zhang, Adheesh Juvekar, Tianshu Bao, Lin Chai, Sparsh Mittal, Inderjit Dhillon, Ismini Lourentzou

Beyond Binary: Continuous State Optimization With Graph-Structured Objectives
Corinna Cortes, Yishay Mansour, Mehryar Mohri

Bio-Inspired Self-Supervised Learning For Wrist-Worn Accelerometer Data
Prithviraj Tarale, Kiet Chu, Abhishek Varghese, Kai-Chun Liu, Maxwell A. Xu, Mohit Iyyer, Sunghoon I. Lee

Can Large Language Models Generalize Procedures Across Representations?
Fangru Lin, Valentin Hofmann, Xingchen Wan, Weixing Wang, Zifeng Ding, Anthony G. Cohn, Janet B. Pierrehumbert

CANDI: Hybrid Discrete-Continuous Diffusion Models
Patrick Pynadath, Jiaxin Shi, Ruqi Zhang*

CAST: Modeling Visual State Transitions For Consistent Video Retrieval
Yanqing Li, Yingcheng Liu, Fanghong Dong, Budianto Budianto, Cihang Xie, Yan Jiao*

CausalArmor: Efficient Indirect Prompt Injection Guardrails Via Causal Attribution
Minbeom Kim, Mihir Parmar, Phillip Wallis, Lesly Miculicich, Kyomin Jung, Krishnamurthy Dj Dvijotham, Long T. Le, Tomas Pfister

Clustering In Deep Stochastic Transformers
Lev Fedorov, Michaël E. Sander, Romuald Elie, Pierre Marion, Mathieu Laurière

Co-RedTeam: Orchestrated Security Discovery and Exploitation With LLM Agents
Pengfei He, Ash Fox, Lesly Miculicich, Stefan Friedli, Daniel Fabian, Burak Gokturk, Jiliang Tang, Chen-Yu Lee, Tomas Pfister, Long T. Le*

Compact Conformal Subgraphs
Sreenivas Gollapud, Kostas Kollias, Kamesh Munagala, Aravindan Vijayaraghavan

Computationally-Efficient Graph Modeling With Refined Graph Random Features
Krzysztof Choromanski, Avinava Dubey, Arijit Sehanobish, Isaac Reid

Data Selection For Fine-tuning Vision Language Models Via Cross Modal Alignment Trajectories
Nilay Naharas, Dang Nguyen, Neslihan Bulut, MohammadHossein Bateni, Vahab Mirrokni, Baharan Mirzasoleiman

Deep Incentive Design With Differentiable Equilibrium Blocks
Vinzenz Thoma, Georgios Piliouras, Luke Marris*

Deep Sequence Models Tend To Memorize Geometrically; It Is Unclear Why
Shahriar Noroozizadeh, Vaishnavh Nagarajan, Elan Rosenfeld, Sanjiv Kumar*

Diffusion Controller: Framework, Algorithms And Parameterization
Tong Yang, Moonkyung Ryu, Chih-Wei Hsu, Guy Tennenholtz, Yuejie Chi, Craig Boutilier, Bo Dai

Discovering Differences in Strategic Behavior Between Humans and LLMs
Caroline Wang, Daniel Kasenberg, Kimberly Stachenfeld, Pablo Samuel Castro

Dissecting Multimodal In-Context Learning: Modality Asymmetries and Circuit Dynamics in Modern Transformers
Yiran Huang, Karsten Roth, Quentin Bouniot, Wenjia Xu, Zeynep Akata

Distribution-Calibrated Inference Time Compute for Thinking LLM-as-a-Judge
Hamid Dadkhahi, Firas Trabelsi, Parker Riley, Juraj Juraska, Mehdi Mirzazadeh

Distributional Alignment Games for Answer-Level Fine-Tuning
Mehryar Mohri, Jon Schneider, Yifan Wu

Dynamic High-Dimensional Facility Location With Low Recourse
Sayan Bhattacharya, Martín Costa, Silvio Lattanzi, Jakub Łącki, Nikos Parotsidis

DynaTok: Token-Based 4D Reconstruction From Partial Point Clouds
Weirong Chen, Keisuke Tateno, Hidenobu Matsuki, Michael Niemeyer, Daniel Cremers, Federico Tombari

ECO: Quantized Training Without Full-Precision Master Weights
Mahdi Nikdan, Amir Zandieh, Dan Alistarh, Vahab Mirrokni

Effective Reasoning Chains Reduce Intrinsic Dimensionality
Archiki Prasad, Mandar Joshi, Kenton Lee, Mohit Bansal, Peter Shaw*

Efficient, Property-Aligned Fan-Out Retrieval Via RL-Compiled Diffusion
Pengcheng Jiang, Judith Yue Li, Moonkyung Ryu, R. Lily Hu, Kun Su, Zhong Yi Wan, Liam Hebert, Hao Peng, Jiawei Han, Dima Kuzmin, Craig Boutilier*

Empty Shelves Or Lost Keys? Recall Is The Bottleneck For Parametric Factuality
Nitay Calderon, Eyal Ben-David, Zorik Gekhman, Eran Ofek, Gal Yona

Extracting Alignment Data In Open Models
Federico Barbero, Xiangming Gu, Christopher A. Choquette Choo*, Chawin Sitawarin, Matthew Jagielski*, Itay Yona*, Petar Veličković, Ilia Shumailov*, Jamie Hayes*

Fantastic Reasoning Behaviors And Where To Find Them: Unsupervised Discovery Of The Reasoning Process
Zhenyu Zhang, Shujian Zhang, John Lambert, Wenxuan Zhou, Zhangyang Wang, Mingqing Chen, Andrew Hard, Rajiv Mathews, Lun Wang*

Flat Minima And Generalization: Insights From Stochastic Convex Optimization
Matan Schliserman, Shira Vansover-Hager, Tomer Koren

Formalizing Learning From Language Feedback With Provable Guarantees
Wanqiao Xu, Allen Nie, Ruijie Zheng, Aditya Modi, Adith Swaminathan, Ching-An Cheng

From Memorization To Parameter Interference: How Overtraining Experts Harms Model Merging
Stefan Horoi, Guy Wolf, Eugene Belilovsky, Gintare Karolina Dziugaite

FUSE: Ensembling Verifiers With Zero Labeled Data
Joonhyuk Lee, Virginia Ma, Sarah Zhao, Yash Nair, Asher Spector, Regev Cohen, Emmanuel Candès

Generation Is Required For Data-Efficient Perception
Jack Brady, Bernhard Schölkopf, Thomas Kipf, Simon Buchholz, Wieland Brendel

Hallucinations Undermine Trust; Metacognition Is A Way Forward
Gal Yona, Mor Geva, Yossi Matias

HEARTS: Benchmarking LLM Reasoning On Health Time Series
Sirui Li, Shuhan Xiao, Mihir Joshi, Ahmed Metwally, Daniel McDuff, Wei Wang, Yuzhe Yang

How Do LLMs Compute Verbal Confidence?
Dharshan Kumaran, Arthur Conmy, Federico Barbero, Simon Osindero, Viorica Patraucean, Petar Veličković

Improved Bounds For Reward-Agnostic And Reward-Free Exploration
Oran Ridel, Alon Cohen

Interpretability And Generalization Bounds For Learning Spatial Physics
Alejandro F. Queiruga, Theo Gutman-Solo, Shuai Jiang

Keeping A Secret Requires A Good Memory: Space Lower-Bounds For Private Algorithms
Alessandro Epasto, Xin Lyu, Pasin Manurangsi

LAPRAS: Learning-Augmented PRivate Answering For Linear Query Streams
Pranay Mundra, Adam Sealfon, Ziteng Sun, Quanquan C. Liu

LaRI: Layered Ray Intersections For Single-view 3D Geometric Reasoning
Rui Li, Biao Zhang, Zhenyu Li, Federico Tombari, Peter Wonka

LazyAttention: Efficient Retrieval-Augmented Generation With Deferred Positional Encoding
Haocheng Xia, Mihir Pamnani, Hanxi Fang, Supawit Chockchowwat, Yongjoo Park

Learning Dynamics Of Zeroth-Order Optimization: A Kernel Perspective
Zhe Li, Bicheng Ying, Zidong Liu, Haibo Yang

Learning Hamiltonian Flow Maps: Mean Flow Consistency For Large-Timestep Molecular Dynamics
Winfried Ripken, Michael Plainer, Gregor Lied, J. Thorben Frank, Oliver T. Unke, Stefan Chmiela, Frank Noé, Klaus-Robert Müeller

Learning Rate Annealing Improves Tuning Robustness In Stochastic Optimization
Amit Attia, Tomer Koren

Linear-Core Surrogates: Smooth Loss Functions With Linear Rates For Classification And Structured Prediction
Mehryar Mohri, Yutao Zhong

Long-Context Modeling With Dynamic Hierarchical Sparse Attention For Memory-Constrained LLM Inference
Siheng Xiong, Joe Zou, Faramarz Fekri, Yae Jee Cho*

LUCID: Attention With Preconditioned Representations
Sai Surya Duvvuri, Nirmal Patel, Nilesh Gupta*, Inderjit S. Dhillon*

MARS: Modular Agent With Reflective Search For Automated AI Research
Jiefeng Chen, Bhavana Dalvi Mishra, Jaehyun Nam, Rui Meng, Tomas Pfister, Jinsung Yoon

Memory Caching: RNNs With Growing Memory
Ali Behrouz, Zeman Li, Yuan Deng, Peilin Zhong, Meisam Razaviyayn, Vahab Mirrokni

Mind The Gap: Structure-Aware Consistency In Preference Learning
Mehryar Mohri, Yutao Zhong

Mobility-Embedded POIs: Learning What A Place Is And How It Is Used From Human Movement
Maria Despoina Siampou, Shushman Choudhury, Shang-Ling Hsu, Neha Arora, Cyrus Shahabi

Multi-Objective Preference Optimization: Improving Human Alignment Of Generative Models
Akhil Agnihotri, Rahul Jain, Deepak Ramachandran, Zheng Wen

Near-Optimal Regret for Policy Optimization in Contextual MDPs With General Offline Function Approximation
Orin Levy, Aviv Rosenberg, Alon Cohen, Yishay Mansour

Networked Information Aggregation For Binary Classification
MohammadHossein Bateni, Zahra Hadizadeh, MohammadTaghi Hajiaghayi, Mahdi JafariRaviz, Shayan Taherijam

Next-Token Prediction and Regret Minimization
Mehryar Mohri, Clayton Sanford, Jon Schneider, Kiran Vodrahalli, Yifan Wu

On the Coordination of Value-Maximizing Bidders
Yanru Guan, Jiahao Zhang, Zhe Feng, Tao Lin

On the Generalization Gap in Self-Evolving Language Model Reasoning
Zhenting Qi, Susanna Maria Baby, Stefanie Anna Baby, Kan Yuan, Andrew Tomkins, Tu Vu, Da-Cheng Juan, Cyrus Rashtchian

OpenSage: Self-Programming Agent Generation Engine
Hongwei Li, Zhun Wang, Qinrun Dai, Yuzhou Nie, Jinjun Peng, Ruitong Liu, Jingyang Zhang, Kaijie Zhu, Jingxuan He, Lun Wang, Yangruibo Ding, Yueqi Chen, Wenbo Guo, Dawn Song

OpenTSLM: Time-Series Language Models For Reasoning Over Multivariate Medical Text- And Time-Series Data
Patrick Langer, Thomas Kaar, Max Rosenblattl, Maxwell A. Xu, Winnie Chow, Martin Maritsch, Robert Jakob, Ning Wang, Juncheng Liu, Aradhana Verma, Brian Han, Daniel Seung Kim, Henry Chubb, Scott Ceresnak, Aydin Zahedivash, Alexander Tarlochan Singh Sandhu, Fatima Rodriguez, Daniel McDuff, Elgar Fleisch, Oliver Aalami, Filipe Barata, Paul Schmiedmayer

Optimal Learning From Label Proportions With General Loss Functions
Lorne Applebaum, Travis Dick, Claudio Gentile, Haim Kaplan, Tomer Koren

Optimal Regret For Policy Optimization In Contextual Bandits
Orin Levy, Yishay Mansour

Optimal Stopping in Latent Diffusion Models
Yu-Han Wu, Quentin Berthet, Gérard Biau, Claire Boyer, Romuald Elie, Pierre Marion

Optimized Deferral For Imbalanced Settings
Corinna Cortes, Anqi Mao, Mehryar Mohri, Yutao Zhong

Outrunning LLM Cutoffs: A Live Kernel Crash Resolution Benchmark For All
Chenxi Huang, Alex Mathai, Feiyang Yu, Aleksandr Nogikh, Petros Maniatis, Franjo Ivančić, Eugene Wu, Kostis Kaffes, Junfeng Yang, Baishakhi Ray

PaperBanana: Automating Academic Illustration For AI Scientists (see blog post)
Dawei Zhu, Rui Meng, Yale Song, Xiyu Wei, Sujian Li, Tomas Pfister, Jinsung Yoon*

ParEVO: Synthesizing Code For Irregular Data: High-Performance Parallelism Through Agentic Evolution
Liu Yang, Zeyu Nie, Andrew Liu, Felix Zou, Deniz Altınbüken, Amir Yazdanbakhsh, Quanquan C. Liu

Per-Example Gradients: A New Frontier For Understanding And Improving Optimizers
Vincent Roulet, Atish Agarwala

PhaseCoder: Microphone Geometry-Agnostic Spatial Audio Understanding For Multimodal LLMs
Artem Dementyev, Wazeer Zulfikar, Sinan Hersek, Pascal Getreuer, Anurag Kumar, Vivek Kumar*

PLANTAIN: Plan-Answer Interleaved Reasoning
Anthony Liang, Jonathan Berant, Adam Fisch, Abhimanyu Goyal, Kalpesh Krishna, Jacob Eisenstein

POLCA: Stochastic Generative Optimization With LLM
Xuanfei Ren, Allen Nie, Tengyang Xie, Ching-An Cheng

Private Learning With Public Feature Conditioning
Shuli Jiang, Walid Krichene*, Nicolas Mayoraz*

Privately Fine-Tuned LLMs Preserve Temporal Dynamics In Tabular Data
Lucas Rosenblatt, Peihan Liu, Ryan McKenna, Natalia Ponomareva

ProEval: Proactive Failure Discovery And Efficient Performance Estimation For Generative AI Evaluation
Yizheng Huang, Wenjun Zeng, Aditi Kumaresan, Zi Wang

Quantifying The Salience Of Geo-Cultural Values For Pluralistic Alignment
Arkadiy Saakyan, Charvi Rastogi, Lora Aroyo*

QuArch: A Benchmark For Evaluating LLM Reasoning In Computer Architecture
Shvetank Prakash, Andrew Cheng, Arya Tschand, Mark Mazumder, Varun Gohil, Jeffrey Ma, Jason Yik, Zishen Wan, Jessica Quaye, Elisavet Lydia Alvanaki, Avinash Kumar, Chandrashis Mazumdar, Tuhin Khare, Alexander Ingare, Ikechukwu Uchendu, Radhika Ghosal, Abhishek Tyagi, Chenyu Wang, Andrea Mattia Garavagno, Sarah Gu, Alice Guo, Grace Hur, Luca Carloni, Tushar Krishna, Ankita Nayak, Amir Yazdanbakhsh, Vijay Janapa Reddi

Rapid Poison: Practical Poisoning Attacks Against The Rapid Response Framework
David Huang, Jaewon Chang, Avidan Shah, Prateek Mittal, Chawin Sitawarin

REAL: Regression-Aware Reinforcement Learning For LLM-as-a-Judge
Yasi Zhang, Tianyu Chen, Mingyuan Zhou, Oscar Leong, Ying Nian Wu, Michal Lukasik

Regression Language Models For Code
Yash Akhauri, Xingyou Song, Arissa Wongpanich, Bryan Lewandowski, Mohamed S. Abdelfattah

Reinforcement Learning With Discrete Diffusion Policies For Combinatorial Action Spaces
Haitong Ma, Ofir Nabati, Aviv Rosenberg, Bo Dai, Oran Lang, Craig Boutilier, Na Li, Shie Mannor, Lior Shani, Guy Tenneholtz

RePIRL: Learn PRM With Inverse RL For LLM Reasoning
Xian Wu, Kaijie Zhu, Ying Zhang, Lun Wang, Wenbo Guo

Representational Similarity And Model Behavior In Multi-Agent Interaction
Yujin Potter, Seun Eisape, Shiyang Lai, Alexander Huth, James Evans, Been Kim, Jacob Eisenstein, Dawn Song, Alane Suhr

Resilient Coresets And Clustering
Mohammadhossein Bateni, Silvio Lattanzi, Morteza Moneimzadeh, Ashkan Norouzi-Fard

Rethinking Generative Image Pretraining: How Far Are We From Scaling Up Next-Pixel Prediction?
Xinchen Yan, Chen Liang, Lijun Yu, Adams Wei Yu, Yifeng Lu, Quoc V. Le*

Rethinking Multimodal Time-Series Forecasting Evaluation
Haoxin Liu, Yichen Zhou, Rajat Sen, B. Aditya Prakash, Abhimanyu Das

Retriever Portfolios: A Principled Approach to Adaptive RAG
Miltiadis Stouras, Vincent Cohen-Addad, Silvio Lattanzi, Ola Svensson

Risk-Averse And Optimistic Advertiser Incentive Compatibility In Auto-bidding
Christopher Liaw, Wennan Zhu

Rotary Position Encodings For Graphs
Isaac Reid, Arijit Sehanobish, Cederik Höfs, Bruno Mlodozeniec, Leonhard Vulpius, Federico Barbero, Adrian Weller, Krzysztof Choromanski, Richard E. Turner, Petar Veličković

Sampled Hard Labels From Sparse Targets Mislead Rotation Invariant Algorithms
Avrajit Ghosh, Bin Yu, Manfred K. Warmuth, Peter Bartlett

Scaling Inference-Time Computation Via Opponent Simulation: Enabling Online Strategic Adaptation In Repeated Negotiation
Xiangyu Liu, Di Wang, Zhe Feng, Aranyak Mehta

Self-Supervised Dynamical System Representations For Physiological Time-Series
Yenho Chen, Maxwell A. Xu, James M. Rehg, Christopher J. Rozell

SG2Loc: Sequential Visual Localization On 3D Scene Graphs
Nicole Damblon, Olga Vysotska, Federico Tombari, Marc Pollefeys, Daniel Barath

Shifting The Breaking Point Of Flow Matching For Multi-Instance Editing
Carmine Zaccagnino, Fabio Quattrini, Enis Simsar, Marta Tintoré Gazulla, Rita Cucchiara, Alessio Tonioni, Silvia Cascianelli

Solipsistic Superintelligence Is Unlikely to Be Cooperative
Rakshit S. Trivedi, Natasha Jaques, Logan Cross, Alexander Vezhnevets, Joel Z. Leibo

Spectrally-Guided Diffusion Noise Schedules
Carlos Esteves, Ameesh Makadia

Stable Deep Reinforcement Learning Via Isotropic Gaussian Representations
Ali Saheb Pasand, Johan Obando-Ceron, Aaron Courville, Pouya Bashivan, Pablo Samuel Castro

Step-Resolved Data Attribution For Looped Transformers
Georgios Kaissis, David Mildenberger, Juan Felipe Gomez, Martin J. Menten, Eleni Triantafillou

Stochastic Linear Bandits With Parameter Noise
Daniel Ezer, Alon Peled-Cohen, Yishay Mansour

SURF: Separation Via Unsupervised Remixing Flow
Henry Li, Robin Scheibler, Efthymios Tzinis, Matt Shannon, Arnaud Doucet, John R. Hershey

SWE-fficiency: Can Language Models Optimize Real-World Repositories On Real Workloads?
Jeffrey J. Ma, Milad Hashemi, Amir Yazdanbakhsh, Kevin Swersky, Ofir Press, Enhui Li, Vijay Janapa Reddi, Parthasarathy Ranganathan

SWING: Unlocking Implicit Graph Representations For Graph Random Features
Alessandro Manenti, Avinava Dubey, Arijit Sehanobish, Cesare Alippi, Krzysztof Choromanski

Symmetries In Language Statistics Shape The Geometry Of Model Representations
Dhruva Karkada, Daniel Korchinski, Andres Nava, Matthieu Wyart, Yasaman Bahri*

Temper-Then-Tilt: Principled Unlearning For Generative Models Through Tempering And Classifier Guidance
Jacob L. Block, Mehryar Mohri, Aryan Mokhtari, Sanjay Shakkottai*

Test-Time Anchoring For Discrete Diffusion Posterior Sampling
Litu Rout, Andreas Lugmayr, Yasamin Jafarian, Srivatsan Varadharajan, Constantine Caramanis, Sanjay Shakkottai, Ira Kemelmacher-Shlizerman

TFRBench: A Reasoning Benchmark For Evaluating Forecasting Systems
Md Atik Ahamed, Mihir Parmar, Palash Goyal, Yiwen Song, Long T. Le, Qiang Cheng, Chun-Liang Li, Hamid Palangi, Jinsung Yoon, Tomas Pfister

The ACUTE Protocol: Operationalizing Language Model Activations For Better Calibration, Utility, And Trust
Nishant Subramani, Palash Goyal, Yiwen Song, Mani Malek, Yuan Xue, Tomas Pfister, Hamid Palangi

The Art Of Interrogation: Consistency Amplifies Factuality In Spatial Reasoning
Théo Uscidda, Marta Tintore Gazulla, Maks Ovsjanikov, Federico Tombari, Leonidas Guibas*

The Efficiency Gap In Byte Modeling
Celine Le, Jing Nathan Yan, Chen Liang, Jiaxin Shi*, Yin Zhang, Jeremiah Liu*, Pengcheng Yin, Fernando Pereira, Ed Chi, Derek Cheng, Alexander M. Rush, Ruoxi Wang*

Theoretical Perspectives On Data Quality And Synergistic Effects In Pre- And Post-Training Reasoning Models
Adel Javanmard, Baharan Mirzasoleiman, Vahab Mirrokni

Think Deep, Not Just Long: Measuring LLM Reasoning Effort Via Deep-Thinking Tokens
Wei-Lin Chen, Liqian Peng, Tian Tan, Chao Zhao, Blake Jianhang Chen, Ziqian Lin, Alec Go, Yu Meng

Uncovering Competency Gaps In Large Language Models And Their Benchmarks
Maty Bohacek, Nino Scherrer, Nicholas Dufour, Thomas Leung, Christoph Bregler, Stephanie C. Y. Chan

Unlearning With Asymmetric Sources: Improved Unlearning-Utility Trade-off With Public Data
Ahmed Mehdi Inane, Vincent Quirion, Gintare Karolina Dziugaite, Ioannis Mitliagkas

Variational Learning For Insertion-Based Generation
Yangtian Zhang, Zhe Wang, Arthur Gretton, Rex Ying, David van Dijk, Michalis K. Titsias, Jiaxin Shi**

Vibe Checker: Aligning Code Evaluation With Human Preference
Ming Zhong, Xiang Zhou, Ting-Yun Chang, Qingze Wang, Nan Xu, Xiance Si, Dan Garrette, Shyam Upadhyay, Jeremiah Liu, Jiawei Han, Benoit Schillings, Jiao Sun*

You Don’t Need All That Attention: Surgical Memorization Mitigation In Text-to-Image Diffusion Models
Kairan Zhao, Eleni Triantafillou, Peter Triantafillou

Position: The AI Imperative: Scaling High-Quality Peer Review In Machine Learning
Qiyao Wei, Samuel Holt, Jing Yang, Markus Wulfmeier, Mihaela van der Schaar*
Oral: Wed, Jul 8 | 10:15AM — 10:30AM, Grand Ballroom 101-105 (Oral 3E Peer Review & Mechanism Design)
Poster: Wed, Jul 8 | 2:30PM — 4:15PM, Hall A (Poster Session 4, #3303)

Position: Comprehensive AI Governance Requires Addressing Non-Model Capability Gains
Arthur Goemans, Dan Altman, Noemi Dreksler, Jonas Freund, Milan Gandhi, Zhengdong Wang, Sarah Cogan, Sebastien Krier, Demetra Brady, Lewis Ho, Allan Dafoe
Wed, Jul 8 | 2:30PM — 4:15PM, Hall A (Poster Session 4, #2911)

Position: Trustworthy AI Suffers From Invariance Conflicts And Causality Is The Solution
Ruta Binkyte, Ivaxi Sheth, Zhijing Jin, Mohammad Havaei, Bernhard Schölkopf, Mario Fritz
Wed, Jul 8 | 5:00PM — 6:45PM, Hall A (Poster Session 5, #4206)

Position: Explainability Research Must Prioritize Foundations Over Ad-hoc Methods
Michal Moshkovitz, Suraj Srinivas, Lesia Semenova, Nave Frost, Cyrus Rashtchian, Valentyn Boreiko, Shichang Zhang, Himabindu Lakkaraju, Cynthia Rudin, Jennifer Wortman Vaughan
Tue, Jul 7 | 2:00PM — 3:45PM, Hall A (Poster Session 2, #3204)

Position: Interpretability Can Be Actionable
Fazl Barez, Tal Haklay, Isabelle Lee, Marius Mosbach, Anja Reusch, Naomi Saphra, Byron Wallace, Sarah Wiegreffe, Eric Wong, Ian Tenney, Mor Geva
Tue, Jul 7 | 2:00PM — 3:45PM, Hall A (Poster Session 2, #3206)

Position: LLMs Can't Jump
Tom Zahavy
Thu, Jul 9 | 5:00PM — 6:45PM, Hall A (Poster Session 8, #3707)

Tue, Jul 7 | 10:30AM — 12:15PM, Hall A (Poster Session 1, #1814)
Reasoning-Driven Synthetic Data Generation And Evaluation
Tim R. Davidson, Benoit Seguin, Enrico Bacis, Cesar Ilharco, Hamza Harkous

Wed, Jul 8 | 2:30PM — 4:15PM, Hall A (Poster Session 4, #313)
Optimizing Return Distributions With Distributional Dynamic Programming
Bernardo Ávila Pires, Mark Rowland, Diana Borsa, Zhaohan Daniel Guo, Khimya Khetarpal, André Barreto, David Abel, Rémi Munos, Will Dabney*

Thu, Jul 9 | 10:30AM — 12:15PM, Hall A (Poster Session 6, #3305)
Decoding Safety Feedback From Diverse Raters: A Data-driven Lens On Responsiveness To Severity
Pushkar Mishra, Charvi Rastogi, Stephen R. Pfohl, Alicia Parrish, Tian Huey Teh, Roma Patel, Mark Diaz, Ding Wang, Michela Paganini, Vinodkumar Prabhakaran, Lora Aroyo, Verena Rieser

Thu, Jul 9 | 2:30PM — 4:15PM, Hall A (Poster Session 7, #3106)
Preserving Expert-Level Privacy In Offline Reinforcement Learning
Navodita Sharma, Vishnu Vinod, Abhradeep Thakurta, Alekh Agarwal, Borja Balle, Christoph Dann, Aravindan Raghuveer

Fri, Jul 10 | 8:00AM — 5:00PM, Room 327
Continual Adaptation At Scale: Towards Sustainable AI
Speakers: Razvan Pascanu, Stephanie Chan, Naman Goyal, Jenny Ni
Organizers: Ghada Sokar, Gintare Karolina Dziugaite

Fri, Jul 10 | 8:00AM — 5:00PM, Room 308
Graph Foundation Models: A New Era for Graph Machine Learning
Speaker: Michael Galkin
Organizer: Ben Finkelshtein

Fri, Jul 10 | 8:00AM — 5:00PM, Hall C
Mechanistic Interpretability
Organizers: Neel Nanda, Stefan Heimersheim, J Rosser

Fri, Jul 10 | 8:00AM — 5:00PM, Grand Ballroom 101 - 102
RLxF: Reinforcement Learning from World Feedback
Speaker: Roberta Raileanu
Organizers: Richard Song, Shane Gu

Fri, Jul 10 | 8:00AM — 5:00PM, ASEM Ballroom 201
SCALE: Scalable Learning and Optimization for Efficient Multimodal AI Agents
Speaker: Jiao Sun

Fri, Jul 10 | 8:00AM — 5:00PM, Grand Ballroom 103
Trustworthy AI for Good
Speakers: Joel Leibo, Jenny Ni, Naman Goyal
Panelist: Milind Tambe
Organizer: Milind Tambe

Fri, Jul 10 | 8:00AM — 5:00PM, Room 403
Weight-Space Symmetries: From Foundations to Practical Applications
Speakers: Gintare Karolina Dziugaite, Sidak Pal Singh

Fri, Jul 10 | 8:20AM — 5:00PM, Auditorium
AI as a Tool For Mathematics, Computer Science, and Machine Learning
Speaker: Sergei Gukov

Fri, Jul 10 | 8:20AM — 5:00PM, Room 318
Foundations of Deep Generative Models: Understanding Memorization, Generalization, and Reasoning
Organizer: Valentin De Bortoli

Fri, Jul 10 | 8:25AM — 5:00PM, ASEM Ballroom 202
Learning to Listen: Machine Learning for Audio
Speakers: Tara Sainath, Heiga Zen
Organizers: Sander Dieleman, Chris Donahue

Fri, Jul 10 | 8:35AM — 5:00PM, Hall D2
Generative and Agentic AI for Biology
Organizer: Minkai Xu

Fri, Jul 10 | 8:45AM — 5:00PM, Room 317
Technical AI Governance Research
Advisory Committee: Gillian Hadfield

Fri, Jul 10 | 9:00AM — 5:00PM, Room 307
Culture X AI: Evaluating AI as a Cultural Technology
Speakers: Rida Qadri, Joel Z. Leibo
Organizer: Canfer Akbulut

Fri, Jul 10 | 9:00AM — 5:30PM, Room E5 - E6
Epistemic Intelligence in Machine Learning: Learning Under Unknown Unknowns for Real-World Impact
Organizer: Arnaud Doucet

Sat, Jul 11 | 8:00AM — 5:30PM, Room 402
AI for Physics
Speaker: Michael Brenner
Organizer: Eun-Ah Kim

Sat, Jul 11 | 8:00AM — 5:00PM, Hall C
AI For Science: AI Scientists — Tools, Co-authors, or Founders?
Speakers: Ramine Tinati, Ray Jiang
Panelist: Ramine Tinati

Sat, Jul 11 | 8:00AM — 5:00PM, ASEM Ballroom 201
Efficient Multimodal Question Answering
Speakers: Naman Goyal, Jenny Ni

Sat, Jul 11 | 8:00AM — 5:00PM, Grand Ballroom 104-105
Forecasting as a New Frontier Of Intelligence
Speaker: Seth Blumberg
Organizer: Haifeng Xu

Sat, Jul 11 | 8:00AM — 5:00PM, Room 308
Philosophy Meets Machine Learning: What Counts as Trustworthy?
Speaker: Been Kim

Sat, Jul 11 | 8:00AM — 5:00PM, Room E1 - E4
Statistical Frameworks for Uncertainty in Agentic Systems
Speaker: Adam Fisch

Sat, Jul 11 | 8:25AM — 5:00PM, Auditorium
Compositional Learning: Safety, Interpretability, and Agents
Speaker: Noémi Éltető

Sat, Jul 11 | 8:30AM — 5:00PM, Room 317
Multi-Modal Foundation Models and Large Language Models for Life Sciences
Speaker: Žiga Avsec

Sat, Jul 11 | 8:30AM — 5:00PM, Hall D2
Structured Data for Health
Organizers: Maxwell Xu, Girish Narayanswamy

Sat, Jul 11 | 8:55AM — 5:00PM, Room E5 - E6
The Impact of Memorization on Trustworthy Foundation Models
Speaker: Thomas Steinke
Organizer: Kamalika Chaudhuri

Sat, Jul 11 | 9:00AM — 5:00PM, Grand Ballroom 103
Foundation Models for Structured Data
Speaker: Abhimanyu Das
Organizers: Arjun Ashok, Rajat Sen

Sat, Jul 11 | 9:00AM — 5:00PM, Room 318
Hypothesis Testing
Speaker: Arthur Gretton

Sat, Jul 11 | 9:15AM — 5:00PM, Room 403
Pluralistic Alignment
Speaker: Atoosa Kasirzadeh
Panelists: Jenny Ni, Naman Goyal