Most Cited ICML "pseudo motion generation" Papers

Adaptive Data Collection for Robust Learning Across Multiple Distributions

Chengbo Zang, Mehmet Turkcan, Gil Zussman et al.

The Best of Both Worlds: Bridging Quality and Diversity in Data Selection with Bipartite Graph

Minghao Wu, Thuy-Trang Vu, Lizhen Qu et al.

The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products

YuQing Xie, Ameya Daigavane, Mit Kotak et al.

ViTally Consistent: Scaling Biological Representation Learning for Cell Microscopy

Kian Kenyon-Dean, Zitong Jerry Wang, John Urbanik et al.

Flow Matching for Few-Trial Neural Adaptation with Stable Latent Dynamics

Puli Wang, Yu Qi, Yueming Wang et al.

SafeAuto: Knowledge-Enhanced Safe Autonomous Driving with Multimodal Foundation Models

Jiawei Zhang, Xuan Yang, Taiqi Wang et al.

Nemotron-CORTEXA: Enhancing LLM Agents for Software Engineering Tasks via Improved Localization and Solution Diversity

Atefeh Sohrabizadeh, Jialin Song, Mingjie Liu et al.

One Wave To Explain Them All: A Unifying Perspective On Feature Attribution

Gabriel Kasmi, Amandine Brunetto, Thomas Fel et al.

TopoTune: A Framework for Generalized Combinatorial Complex Neural Networks

Mathilde Papillon, Guillermo Bernardez, Claudio Battiloro et al.

Leveraging Sparsity for Sample-Efficient Preference Learning: A Theoretical Perspective

Yunzhen Yao, Lie He, Michael Gastpar

Whitened CLIP as a Likelihood Surrogate of Images and Captions

Roy Betser, Meir Yossef Levi, Guy Gilboa

EncryptedLLM: Privacy-Preserving Large Language Model Inference via GPU-Accelerated Fully Homomorphic Encryption

Leo de Castro, Daniel Escudero, Adya Agrawal et al.

On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training

Chen Liu, Zhichao Huang, Mathieu Salzmann et al.

Universal Neural Optimal Transport

Jonathan Geuter, Gregor Kornhardt, Ingimar Tomasson et al.

Geometric Resampling in Nearly Linear Time for Follow-the-Perturbed-Leader with Best-of-Both-Worlds Guarantee in Bandit Problems

Botao Chen, Jongyeong Lee, Junya Honda

Synthetic Text Generation for Training Large Language Models via Gradient Matching

Dang Nguyen, Zeman Li, MohammadHossein Bateni et al.

An analytic theory of creativity in convolutional diffusion models

Mason Kamb, Surya Ganguli

Measuring In-Context Computation Complexity via Hidden State Prediction

Vincent Herrmann, Róbert Csordás, Jürgen Schmidhuber

Teaching Transformers Causal Reasoning through Axiomatic Training

Aniket Vashishtha, Abhinav Kumar, Atharva Pandey et al.

Training Deep Learning Models with Norm-Constrained LMOs

Thomas Pethick, Wanyun Xie, Kimon Antonakopoulos et al.

MOGIC: Metadata-infused Oracle Guidance for Improved Extreme Classification

Suchith Chidananda Prabhu, Bhavyajeet Singh, Anshul Mittal et al.

CAT Merging: A Training-Free Approach for Resolving Conflicts in Model Merging

Wenju Sun, Qingyong Li, Yangliao Geng et al.

SCENT: Robust Spatiotemporal Learning for Continuous Scientific Data via Scalable Conditioned Neural Fields

David K Park, Xihaier Luo, Guang Zhao et al.

FedBEns: One-Shot Federated Learning based on Bayesian Ensemble

Jacopo Talpini, Marco Savi, Giovanni Neglia

Efficient Curvature-Aware Hypergradient Approximation for Bilevel Optimization

Youran Dong, Junfeng Yang, Wei Yao et al.

POQD: Performance-Oriented Query Decomposer for Multi-vector retrieval

Yaoyang Liu, Junlin Li, Yinjun Wu et al.

Dynamic Similarity Graph Construction with Kernel Density Estimation

Steinar Laenen, Peter Macgregor, He Sun

The Brain's Bitter Lesson: Scaling Speech Decoding With Self-Supervised Learning

Dulhan Jayalath, Gilad Landau, Brendan Shillingford et al.

Federated Learning for Feature Generalization with Convex Constraints

Dongwon Kim, Donghee Kim, Sung Kuk Shyn et al.

Outsourced Diffusion Sampling: Efficient Posterior Inference in Latent Spaces of Generative Models

Siddarth Venkatraman, Mohsin Hasan, Minsu Kim et al.

CEGA: A Cost-Effective Approach for Graph-Based Model Extraction and Acquisition

Zebin Wang, Menghan Lin, Bolin Shen et al.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention for Long-Context LLM Serving

Yeonju Ro, Zhenyu Zhang, Souvik Kundu et al.

DIS-CO: Discovering Copyrighted Content in VLMs Training Data

André Duarte, Xuandong Zhao, Arlindo Oliveira et al.

BalancEdit: Dynamically Balancing the Generality-Locality Trade-off in Multi-modal Model Editing

Dongliang Guo, Mengxuan Hu, Zihan Guan et al.

WikiBigEdit: Understanding the Limits of Lifelong Knowledge Editing in LLMs

Lukas Thede, Karsten Roth, Matthias Bethge et al.

Simplicity Bias and Optimization Threshold in Two-Layer ReLU Networks

Etienne Boursier, Nicolas Flammarion

Toward Data-centric Directed Graph Learning: An Entropy-driven Approach

Xunkai Li, Zhengyu Wu, Kaichi Yu et al.

TIMING: Temporality-Aware Integrated Gradients for Time Series Explanation

Hyeongwon Jang, Changhun Kim, Eunho Yang

Provably Near-Optimal Federated Ensemble Distillation with Negligible Overhead

Won-Jun Jang, Hyeon-Seo Park, Si-Hyeon Lee

Voronoi-grid-based Pareto Front Learning and Its Application to Collaborative Federated Learning

Mengmeng Chen, Xiaohu Wu, QIQI LIU et al.

Time-Aware World Model for Adaptive Prediction and Control

Anh Nhu, Sanghyun Son, Ming Lin

Minimalist Concept Erasure in Generative Models

Yang Zhang, Er Jin, Yanfei Dong et al.

Improved Coresets for Vertical Federated Learning: Regularized Linear and Logistic Regressions

Supratim Shit, Gurmehak chadha, Surendra kumar et al.

Action-Constrained Imitation Learning

Chia-Han Yeh, Tse-Sheng Nan, Risto Vuorio et al.

Highly Compressed Tokenizer Can Generate Without Training

Lukas Lao Beyer, Tianhong Li, Xinlei Chen et al.

Improved Algorithm for Deep Active Learning under Imbalance via Optimal Separation

Shyam Nuggehalli, Jifan Zhang, Lalit Jain et al.

ZebraLogic: On the Scaling Limits of LLMs for Logical Reasoning

Yuchen Lin, Ronan Le Bras, Kyle Richardson et al.

Strong and Weak Identifiability of Optimization-based Causal Discovery in Non-linear Additive Noise Models

Mingjia Li, Hong Qian, Tian-Zuo Wang et al.

Resolving Lexical Bias in Model Editing

Hammad Rizwan, Domenic Rosati, Ga Wu et al.

Nearly Optimal Sample Complexity for Learning with Label Proportions

Robert Busa-Fekete, Travis Dick, Claudio Gentile et al.

Scalable Private Partition Selection via Adaptive Weighting

Justin Chen, Vincent Cohen-Addad, Alessandro Epasto et al.

FlashTP: Fused, Sparsity-Aware Tensor Product for Machine Learning Interatomic Potentials

Seung Lee, Hojoon Kim, Yutack Park et al.

GSM-$\infty$: How Do your LLMs Behave over Infinitely Increasing Reasoning Complexity and Context Length?

Yang Zhou, Hongyi Liu, Zhuoming Chen et al.

On the Local Complexity of Linear Regions in Deep ReLU Networks

Niket Patel, Guido Montufar

Safely Learning Optimal Auctions: A Testable Learning Framework for Mechanism Design

Vikram Kher, Manolis Zampetakis

PertEval-scFM: Benchmarking Single-Cell Foundation Models for Perturbation Effect Prediction

Aaron Wenteler, Martina Occhetta, Nikhil Branson et al.

Perceptual-GS: Scene-adaptive Perceptual Densification for Gaussian Splatting

Hongbi ZHOU, Zhangkai NI

The Canary’s Echo: Auditing Privacy Risks of LLM-Generated Synthetic Text

Matthieu Meeus, Lukas Wutschitz, Santiago Zanella-Beguelin et al.

Scaling Trends in Language Model Robustness

Nikolaus Howe, Ian McKenzie, Oskar Hollinsworth et al.

Double-Filter: Efficient Fine-tuning of Pre-trained Vision-Language Models via Patch&Layer Filtering

Yaoqin He, Junchen Fu, Kaiwen Zheng et al.

Predictive Data Selection: The Data That Predicts Is the Data That Teaches

KaShun SHUM, Yuzhen Huang, Hongjian Zou et al.

Graph-Based Algorithms for Diverse Similarity Search

Piyush Anand, Piotr Indyk, Ravishankar Krishnaswamy et al.

BoxLM: Unifying Structures and Semantics of Medical Concepts for Diagnosis Prediction in Healthcare

Yanchao Tan, Hang Lv, Yunfei Zhan et al.

Avoiding Leakage Poisoning: Concept Interventions Under Distribution Shifts

Mateo Espinosa Zarlenga, Gabriele Dominici, Pietro Barbiero et al.

Position: AI Competitions Provide the Gold Standard for Empirical Rigor in GenAI Evaluation

D. Sculley, William Cukierski, Phil Culliton et al.

The Power of Random Features and the Limits of Distribution-Free Gradient Descent

Ari Karchmer, Eran Malach

scSSL-Bench: Benchmarking Self-Supervised Learning for Single-Cell Data

Olga Ovcharenko, Florian Barkmann, Philip Toma et al.

SEFE: Superficial and Essential Forgetting Eliminator for Multimodal Continual Instruction Tuning

Jinpeng Chen, Runmin Cong, Yuzhi Zhao et al.

MemFreezing: A Novel Adversarial Attack on Temporal Graph Neural Networks under Limited Future Knowledge

Yue Dai, Liang Liu, Xulong Tang et al.

Large Language Model-driven Large Neighborhood Search for Large-Scale MILP Problems

Huigen Ye, Hua Xu, An Yan et al.

Statistical and Computational Guarantees of Kernel Max-Sliced Wasserstein Distances

Jie Wang, March Boedihardjo, Yao Xie

I Think, Therefore I Diffuse: Enabling Multimodal In-Context Reasoning in Diffusion Models

Zhenxing Mi, Kuan-Chieh Wang, Guocheng Qian et al.

Unnatural Languages Are Not Bugs but Features for LLMs

Keyu Duan, Yiran Zhao, Zhili Feng et al.

TokenSwift: Lossless Acceleration of Ultra Long Sequence Generation

Tong Wu, Junzhe Shen, Zixia Jia et al.

Robot-Gated Interactive Imitation Learning with Adaptive Intervention Mechanism

Haoyuan Cai, Zhenghao Peng, Bolei Zhou

Efficient First-Order Optimization on the Pareto Set for Multi-Objective Learning under Preference Guidance

Lisha Chen, Quan Xiao, Ellen Fukuda et al.

Quantum Algorithms for Finite-horizon Markov Decision Processes

Bin Luo, Yuwen Huang, Jonathan Allcock et al.

Dynamical Modeling of Behaviorally Relevant Spatiotemporal Patterns in Neural Imaging Data

Mohammad Hosseini, Maryam Shanechi

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation

Piyush Lalitkumar Tiwary, Kinjawl Bhattacharyya, Prathosh AP

Does learning the right latent variables necessarily improve in-context learning?

Sarthak Mittal, Eric Elmoznino, Léo Gagnon et al.

Feedforward Few-shot Species Range Estimation

Christian Lange, Max Hamilton, Elijah Cole et al.

AI for Global Climate Cooperation: Modeling Global Climate Negotiations, Agreements, and Long-Term Cooperation in RICE-N

Tianyu Zhang, Andrew Williams, Phillip Wozny et al.

TopInG: Topologically Interpretable Graph Learning via Persistent Rationale Filtration

Cheng Xin, Fan Xu, Xin Ding et al.

GMAIL: Generative Modality Alignment for generated Image Learning

Shentong Mo, Sukmin Yun

Position: Medical Large Language Model Benchmarks Should Prioritize Construct Validity

Ahmed Alaa, Thomas Hartvigsen, Niloufar Golchini et al.

Proposer-Agent-Evaluator (PAE): Autonomous Skill Discovery For Foundation Model Internet Agents

Yifei Zhou, Qianlan Yang, Kaixiang Lin et al.

Hgformer: Hyperbolic Graph Transformer for Collaborative Filtering

Yang Xin, Xingrun Li, Heng Chang et al.

BRIDGE: Bootstrapping Text to Control Time-Series Generation via Multi-Agent Iterative Optimization and Diffusion Modeling

Hao Li, Yu-Hao Huang, Chang Xu et al.

Balancing Interference and Correlation in Spatial Experimental Designs: A Causal Graph Cut Approach

Jin Zhu, Jingyi Li, Hongyi Zhou et al.

A Reasoning-Based Approach to Cryptic Crossword Clue Solving

Martin Andrews, Sam Witteveen

Fully Dynamic Euclidean Bi-Chromatic Matching in Sublinear Update Time

Gramoz Goranci, Peter Kiss, Neel Patel et al.

What Makes In-context Learning Effective for Mathematical Reasoning

Jiayu Liu, Zhenya Huang, Chaokun Wang et al.

Global-Local Dirichlet Processes for Clustering Grouped Data in the Presence of Group-Specific Idiosyncratic Variables

Arhit Chakrabarti, Yang Ni, Debdeep Pati et al.

TimeDART: A Diffusion Autoregressive Transformer for Self-Supervised Time Series Representation

Daoyu Wang, Mingyue Cheng, Zhiding Liu et al.

Knowledge-Guided Wasserstein Distributionally Robust Optimization

Zitao Wang, Ziyuan Wang, Molei Liu et al.

Hessian Geometry of Latent Space in Generative Models

Alexander Lobashev, Dmitry Guskov, Maria Larchenko et al.

Online Sparsification of Bipartite-Like Clusters in Graphs

Joyentanuj Das, Suranjan De, He Sun

Efficient Graph Continual Learning via Lightweight Graph Neural Tangent Kernels-based Dataset Distillation

Rihong Qiu, Xinke Jiang, Yuchen Fang et al.

DCTdiff: Intriguing Properties of Image Generative Modeling in the DCT Space

Mang Ning, Mingxiao Li, Jianlin Su et al.

Regression for the Mean: Auto-Evaluation and Inference with Few Labels through Post-hoc Regression

Benjamin Eyre, David Madras

FastCAV: Efficient Computation of Concept Activation Vectors for Explaining Deep Neural Networks

Laines Schmalwasser, Niklas Penzel, Joachim Denzler et al.

Learning Single Index Models with Diffusion Priors

Anqi Tang, Youming Chen, Shuchen Xue et al.

Neural Encoding and Decoding at Scale

Yizi Zhang, Yanchen Wang, Mehdi Azabou et al.

Wyckoff Transformer: Generation of Symmetric Crystals

Nikita Kazeev, Wei Nong, Ignat Romanov et al.

Generalization Analysis for Supervised Contrastive Representation Learning under Non-IID Settings

Minh Hieu Nong, Antoine Ledent

Sampling from Binary Quadratic Distributions via Stochastic Localization

Chenguang Wang, Kaiyuan Cui, Weichen Zhao et al.

Reidentify: Context-Aware Identity Generation for Contextual Multi-Agent Reinforcement Learning

Zhiwei XU, Kun Hu, Xin Xin et al.

Online Detection of LLM-Generated Texts via Sequential Hypothesis Testing by Betting

Can Chen, Jun-Kun Wang

Putnam-AXIOM: A Functional & Static Benchmark for Measuring Higher Level Mathematical Reasoning in LLMs

Aryan Gulati, Brando Miranda, Eric Chen et al.

Avoiding spurious sharpness minimization broadens applicability of SAM

Sidak Pal Singh, Hossein Mobahi, Atish Agarwala et al.

Recommendations with Sparse Comparison Data: Provably Fast Convergence for Nonconvex Matrix Factorization

Suryanarayana Sankagiri, Jalal Etesami, Matthias Grossglauser

Canonical Rank Adaptation: An Efficient Fine-Tuning Strategy for Vision Transformers

Lokesh Veeramacheneni, Moritz Wolter, Hilde Kuehne et al.

Hierarchical Planning for Complex Tasks with Knowledge Graph-RAG and Symbolic Verification

Flavio Petruzzellis, Cristina Cornelio, Pietro Lió

How to Train Your Multi-Exit Model? Analyzing the Impact of Training Strategies

Piotr Kubaty, Bartosz Wójcik, Bartłomiej Krzepkowski et al.

VTGaussian-SLAM: RGBD SLAM for Large Scale Scenes with Splatting View-Tied 3D Gaussians

Pengchong Hu, Zhizhong Han

Ladder-Residual: Parallelism-Aware Architecture for Accelerating Large Model Inference with Communication Overlapping

Muru Zhang, Mayank Mishra, Zhongzhu Zhou et al.

Convergence of Consistency Model with Multistep Sampling under General Data Assumptions

Yiding Chen, Yiyi Zhang, Owen Oertell et al.

Mahalanobis++: Improving OOD Detection via Feature Normalization

Maximilian Müller, Matthias Hein

Audio Flamingo 2: An Audio-Language Model with Long-Audio Understanding and Expert Reasoning Abilities

Sreyan Ghosh, Zhifeng Kong, Sonal Kumar et al.

Mitigating Object Hallucination in Large Vision-Language Models via Image-Grounded Guidance

Linxi Zhao, Yihe Deng, Weitong Zhang et al.

Rethinking Confidence Scores and Thresholds in Pseudolabeling-based SSL

Harit Vishwakarma, Yi Chen, Satya Sai Srinath Namburi GNVV et al.

What Makes a Good Feedforward Computational Graph?

Alex Vitvitskyi, João Madeira Araujo, Marc Lackenby et al.

Hi Robot: Open-Ended Instruction Following with Hierarchical Vision-Language-Action Models

Lucy Xiaoyang Shi, brian ichter, Michael Equi et al.

Adapting to Linear Separable Subsets with Large-Margin in Differentially Private Learning

Erchi Wang, Yuqing Zhu, Yu-Xiang Wang

FAB-PPI: Frequentist, Assisted by Bayes, Prediction-Powered Inference

Stefano Cortinovis, Francois Caron

Optimizing Noise Distributions for Differential Privacy

Atefeh Gilani, Felipe Gomez, Shahab Asoodeh et al.

Training Diffusion-based Generative Models with Limited Data

Zhaoyu Zhang, Yang Hua, Guanxiong Sun et al.

Benefits of Early Stopping in Gradient Descent for Overparameterized Logistic Regression

Jingfeng Wu, Peter Bartlett, Matus Telgarsky et al.

Clipped SGD Algorithms for Performative Prediction: Tight Bounds for Stochastic Bias and Remedies

Qiang Li, Michal Yemini, Hoi To Wai

Consensus Is All You Get: The Role of Attention in Transformers

Alvaro Rodriguez Abella, João Pedro Silvestre, Paulo Tabuada

Gradient Descent Converges Arbitrarily Fast for Logistic Regression via Large and Adaptive Stepsizes

Ruiqi Zhang, Jingfeng Wu, Peter Bartlett

OrcaLoca: An LLM Agent Framework for Software Issue Localization

Zhongming Yu, Hejia Zhang, Yujie Zhao et al.

Mixed-curvature decision trees and random forests

Philippe Chlenski, Quentin Chu, Raiyan Khan et al.

An Adaptive Orthogonal Convolution Scheme for Efficient and Flexible CNN Architectures

Thibaut Boissin, Franck Mamalet, Thomas Fel et al.

Scalable Model Merging with Progressive Layer-wise Distillation

Jing Xu, Jiazheng Li, Jingzhao Zhang

Learning Distribution-wise Control in Representation Space for Language Models

Deng, Ruidi Chang, Hanjie Chen

Exploring Criteria of Loss Reweighting to Enhance LLM Unlearning

Puning Yang, Qizhou Wang, Zhuo Huang et al.

EditLord: Learning Code Transformation Rules for Code Editing

Weichen Li, Albert Jan, Baishakhi Ray et al.

AffectGPT: A New Dataset, Model, and Benchmark for Emotion Understanding with Multimodal Large Language Models

Zheng Lian, Haoyu Chen, Lan Chen et al.

Fluctuations of the largest eigenvalues of transformed spiked Wigner matrices

Aro Lee, Ji Oon Lee

Covered Forest: Fine-grained generalization analysis of graph neural networks

Antonis Vasileiou, Ben Finkelshtein, Floris Geerts et al.

Robust Noise Attenuation via Adaptive Pooling of Transformer Outputs

Greyson Brothers

Breaking Barriers: Combinatorial Algorithms for Non-Monotone Submodular Maximization with Sublinear Adaptivity and $1/e$ Approximation

Yixin Chen, Wenjing Chen, Alan Kuhnle

NextCoder: Robust Adaptation of Code LMs to Diverse Code Edits

Tushar Aggarwal, Swayam Singh, Abhijeet Awasthi et al.

MMInference: Accelerating Pre-filling for Long-Context Visual Language Models via Modality-Aware Permutation Sparse Attention

Yucheng Li, Huiqiang Jiang, Chengruidong Zhang et al.

Conformal Prediction as Bayesian Quadrature

Jake Snell, Thomas Griffiths

A General Graph Spectral Wavelet Convolution via Chebyshev Order Decomposition

Nian Liu, Xiaoxin He, Thomas Laurent et al.

Improving the Statistical Efficiency of Cross-Conformal Prediction

DTZO: Distributed Trilevel Zeroth Order Learning with Provable Non-Asymptotic Convergence

Yang Jiao, Kai Yang, Chengtao Jian

Hierarchical Equivariant Policy via Frame Transfer

Haibo Zhao, Dian Wang, Yizhe Zhu et al.

The Number of Trials Matters in Infinite-Horizon General-Utility Markov Decision Processes

Pedro Santos, Alberto Sardinha, Francisco S. Melo

Dynamical phases of short-term memory mechanisms in RNNs

Bariscan Kurtkaya, Fatih Dinc, Mert Yuksekgonul et al.

The Berkeley Function Calling Leaderboard (BFCL): From Tool Use to Agentic Evaluation of Large Language Models

Shishir G. Patil, Huanzhi Mao, Fanjia Yan et al.

Improved Regret Analysis in Gaussian Process Bandits: Optimality for Noiseless Reward, RKHS norm, and Non-Stationary Variance

Shogo Iwazaki, Shion Takeno

Eliciting Language Model Behaviors with Investigator Agents

Xiang Li, Neil Chowdhury, Daniel Johnson et al.

Policy Gradient with Tree Expansion

Gal Dalal, Assaf Hallak, Gugan Chandrashekhar Mallika Thoppe et al.

SGD Jittering: A Training Strategy for Robust and Accurate Model-Based Architectures

Peimeng Guan, Mark Davenport

Double Machine Learning for Causal Inference under Shared-State Interference

Chris Hays, Manish Raghavan

SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse Autoencoders

Bartosz Cywiński, Kamil Deja

Explaining, Fast and Slow: Abstraction and Refinement of Provable Explanations

Shahaf Bassan, Yizhak Elboher, Tobias Ladner et al.

Adaptive Elicitation of Latent Information Using Natural Language

Jimmy Wang, Tom Zollo, Richard Zemel et al.

Goal-Space Planning with Subgoal Models

Chunlok Lo, Kevin Roice, Parham Mohammad Panahi et al.

RULEBREAKERS: Challenging LLMs at the Crossroads between Formal Logic and Human-like Reasoning

Jason Chan, Robert Gaizauskas, Zhixue Zhao

SparseLoRA: Accelerating LLM Fine-Tuning with Contextual Sparsity

Samir Khaki, Xiuyu Li, Junxian Guo et al.

Diversity By Design: Leveraging Distribution Matching for Offline Model-Based Optimization

Michael S Yao, James Gee, Osbert Bastani

Efficient Molecular Conformer Generation with SO(3)-Averaged Flow Matching and Reflow

Zhonglin Cao, Mario Geiger, Allan Costa et al.

Survival Analysis via Density Estimation

Hiroki Yanagisawa, Shunta Akiyama

Hybrid Batch Normalisation: Resolving the Dilemma of Batch Normalisation in Federated Learning

Hongyao Chen, Tianyang Xu, Xiaojun Wu et al.

Tilted Sharpness-Aware Minimization

Tian Li, Tianyi Zhou, Jeff Bilmes

LARM: Large Auto-Regressive Model for Long-Horizon Embodied Intelligence

Zhuoling Li, Xiaogang Xu, Zhenhua Xu et al.

DynaMind: Reasoning over Abstract Video Dynamics for Embodied Decision-Making

Ziru Wang, Mengmeng Wang, Jade Dai et al.

Graph4MM: Weaving Multimodal Learning with Structural Information

Xuying Ning, Dongqi Fu, Tianxin Wei et al.

Investigating the Overlooked Hessian Structure: From CNNs to LLMs

Qian-Yuan Tang, Yufei Gu, Yunfeng Cai et al.

Dimension-Independent Rates for Structured Neural Density Estimation

Vandermeulen, Wai Ming Tai, Bryon Aragam

Counterfactual Graphical Models: Constraints and Inference

Juan Correa, Elias Bareinboim

Solving Probabilistic Verification Problems of Neural Networks using Branch and Bound

David Boetius, Stefan Leue, Tobias Sutter

Sortformer: A Novel Approach for Permutation-Resolved Speaker Supervision in Speech-to-Text Systems

Taejin Park, Ivan Medennikov, Kunal Dhawan et al.

Position: Evaluating Generative AI Systems Is a Social Science Measurement Challenge

Hanna Wallach, Meera Desai, A. Feder Cooper et al.

Position: AI Agents Need Authenticated Delegation

Tobin South, Samuele Marro, Thomas Hardjono et al.

Position: Societal Impacts Research Requires Benchmarks for Creative Composition Tasks

Judy Hanwen Shen

Position: Certified Robustness Does Not (Yet) Imply Model Security

Andrew C. Cullen, Paul MONTAGUE, Sarah Erfani et al.

Position: Political Neutrality in AI Is Impossible — But Here Is How to Approximate It

Jillian Fisher, Ruth Elisabeth Appel, Chan Young Park et al.

Physics-Informed DeepONets for drift-diffusion on metric graphs: simulation and parameter identification

Jan Blechschmidt, Tom-Christian Riemer, Max Winkler et al.

Machine Learning meets Algebraic Combinatorics: A Suite of Datasets Capturing Research-level Conjecturing Ability in Pure Mathematics

Herman Chau, Helen Jenne, Davis Brown et al.

Position: Future Research and Challenges Remain Towards AI for Software Engineering

Alex Gu, Naman Jain, Wen-Ding Li et al.

Deliberation in Latent Space via Differentiable Cache Augmentation

Luyang Liu, Jonas Pfeiffer, Jiaxing Wu et al.

Position: AI Safety Must Embrace an Antifragile Perspective

Ming Jin, Hyunin Lee

Machines and Mathematical Mutations: Using GNNs to Characterize Quiver Mutation Classes

Jesse He, Helen Jenne, Herman Chau et al.

Position: We Can’t Understand AI Using our Existing Vocabulary

John Hewitt, Robert Geirhos, Been Kim

Position: LLM Social Simulations Are a Promising Research Method

Jacy Anthis, Ryan Liu, Sean Richardson et al.

Trajectory World Models for Heterogeneous Environments

Shaofeng Yin, Jialong Wu, Siqiao Huang et al.

Position: Beyond Assistance – Reimagining LLMs as Ethical and Adaptive Co-Creators in Mental Health Care

Abeer Badawi, Md Tahmid Rahman Laskar, Jimmy Huang et al.

Position: Democratic AI is Possible. The Democracy Levels Framework Shows How It Might Work.

Aviv Ovadya, Kyle Redman, Luke Thorburn et al.

Training Flexible Models of Genetic Variant Effects from Functional Annotations using Accelerated Linear Algebra

Alan Amin, Andres Potapczynski, Andrew Wilson

Reliable Algorithm Selection for Machine Learning-Guided Design

Clara Fannjiang, Ji Won Park

On Fine-Grained Distinct Element Estimation

Ilias Diakonikolas, Daniel Kane, Jasper Lee et al.

Learning-Augmented Hierarchical Clustering

Vladimir Braverman, Jon C. Ergun, Chen Wang et al.

Low-distortion and GPU-compatible Tree Embeddings in Hyperbolic Space

Max van Spengler, Pascal Mettes

DEFAME: Dynamic Evidence-based FAct-checking with Multimodal Experts

Tobias Braun, Mark Rothermel, Marcus Rohrbach et al.

Accelerating PDE-Constrained Optimization by the Derivative of Neural Operators

Ze Cheng, Zhuoyu Li, Wang Xiaoqiang et al.