Most Cited ICML "individual perspective" Papers

Tandem Transformers for Inference Efficient LLMs

Aishwarya P S, Pranav Nair, Yashas Samaga et al.

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I. Arce, Emiliano Kargieman, G. Richarte et al.

On the Alignment between Fairness and Accuracy: from the Perspective of Adversarial Robustness

Junyi Chai, Taeuk Jang, Jing Gao et al.

Model Immunization from a Condition Number Perspective

Amber Yijia Zheng, Cedar Site Bai, Brian Bullins et al.

One-Pass Feature Evolvable Learning with Theoretical Guarantees

Cun-Yuan Xing, Meng-Zhang Qian, Wu-Yang Chen et al.

Stacey: Promoting Stochastic Steepest Descent via Accelerated $\ell_p$-Smooth Nonconvex Optimization

Xinyu Luo, Cedar Site Bai, Bolian Li et al.

ELMO : Efficiency via Low-precision and Peak Memory Optimization in Large Output Spaces

Jinbin Zhang, Nasib Ullah, Erik Schultheis et al.

Online Learning in Risk Sensitive constrained MDP

Arnob Ghosh, Mehrdad Moharrami

AdaWorld: Learning Adaptable World Models with Latent Actions

Shenyuan Gao, Siyuan Zhou, Yilun Du et al.

Unifying Knowledge from Diverse Datasets to Enhance Spatial-Temporal Modeling: A Granularity-Adaptive Geographical Embedding Approach

Zhigaoyuan Wang, Ying Sun, Hengshu Zhu

Fine-Grained Captioning of Long Videos through Scene Graph Consolidation

Sanghyeok Chu, Seonguk Seo, Bohyung Han

NeuroTree: Hierarchical Functional Brain Pathway Decoding for Mental Health Disorders

Jun-En Ding, Dongsheng Luo, Chenwei Wu et al.

Position: You Can't Manufacture a NeRF

Marta An Kimmel, Mueed Rehman, Yonatan Bisk et al.

Toward a Unified Theory of Gradient Descent under Generalized Smoothness

Alexander Tyurin

Otter: Generating Tests from Issues to Validate SWE Patches

Toufique Ahmed, Jatin Ganhotra, Rangeet Pan et al.

Reinforcement Learning with Random Time Horizons

Enric Borrell, Lorenz Richter, Christof Schuette

Faster Stochastic Optimization with Arbitrary Delays via Adaptive Asynchronous Mini-Batching

Amit Attia, Ofir Gaash, Tomer Koren

Gradient Aligned Regression via Pairwise Losses

Dixian Zhu, Tianbao Yang, Livnat Jerby

HyperIMTS: Hypergraph Neural Network for Irregular Multivariate Time Series Forecasting

Boyuan Li, Yicheng Luo, Zhen Liu et al.

Sample Efficient Demonstration Selection for In-Context Learning

Kiran Purohit, Venktesh V, Sourangshu Bhattacharya et al.

Neural Guided Diffusion Bridges

Gefan Yang, Frank van der Meulen, Stefan Sommer

Hierarchical Reinforcement Learning with Targeted Causal Interventions

Mohammadsadegh Khorasani, Saber Salehkaleybar, Negar Kiyavash et al.

Online Robust Reinforcement Learning Through Monte-Carlo Planning

Tuan Dam, Kishan Panaganti, Brahim Driss et al.

Power Mean Estimation in Stochastic Continuous Monte-Carlo Tree Search

Tuan Dam

Boosting Adversarial Robustness with CLAT: Criticality Leveraged Adversarial Training

Bhavna Gopal, Huanrui Yang, Jingyang Zhang et al.

Geometry Informed Tokenization of Molecules for Language Model Generation

Xiner Li, Limei Wang, Youzhi Luo et al.

Position: The Future of Bayesian Prediction Is Prior-Fitted

Samuel Gabriel Müller, Arik Reuter, Noah Hollmann et al.

Circumventing Backdoor Space via Weight Symmetry

Jie Peng, Hongwei Yang, Jing Zhao et al.

Computing Voting Rules with Improvement Feedback

Evi Micha, Vasilis Varsamis

Concept Reachability in Diffusion Models: Beyond Dataset Constraints

Marta Aparicio Rodriguez, Xenia Miscouridou, Anastasia Borovykh

Delay-DSGN: A Dynamic Spiking Graph Neural Network with Delay Mechanisms for Evolving Graph

Zhiqiang Wang, Jianghao Wen, Jianqing Liang

Spatial Reasoning with Denoising Models

Christopher Wewer, Bartlomiej Pogodzinski, Bernt Schiele et al.

Online Differentially Private Conformal Prediction for Uncertainty Quantification

Janus: Dual-Server Multi-Round Secure Aggregation with Verifiability for Federated Learning

Lang Pu, Jingjing Gu, Chao Lin et al.

Bayesian Basis Function Approximation for Scalable Gaussian Process Priors in Deep Generative Models

Mehmet Yiğit Balık, Maksim Sinelnikov, Priscilla Ong et al.

Contrastive Visual Data Augmentation

Yu Zhou, Bingxuan Li, Mohan Tang et al.

From Logits to Hierarchies: Hierarchical Clustering made Simple

Emanuele Palumbo, Moritz Vandenhirtz, Alain Ryser et al.

FedSSI: Rehearsal-Free Continual Federated Learning with Synergistic Synaptic Intelligence

Yichen Li, Yuying Wang, Haozhao Wang et al.

The Generalized Skew Spectrum of Graphs

Armando Bellante, Martin Plávala, Alessandro Luongo

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives

Elliot Meyerson, Xin Qiu

Upweighting Easy Samples in Fine-Tuning Mitigates Forgetting

Sunny Sanyal, Hayden Prairie, Rudrajit Das et al.

Low-Rank Tensor Transitions (LoRT) for Transferable Tensor Regression

Andong Wang, Yuning Qiu, Zhong Jin et al.

Reflection-Window Decoding: Text Generation with Selective Refinement

Zeyu Tang, Zhenhao Chen, Xiangchen Song et al.

Learning Vision and Language Concepts for Controllable Image Generation

Shaoan Xie, Lingjing Kong, Yujia Zheng et al.

GrokFormer: Graph Fourier Kolmogorov-Arnold Transformers

GUOGUO AI, Guansong Pang, Hezhe Qiao et al.

StealthInk: A Multi-bit and Stealthy Watermark for Large Language Models

Ya Jiang, Chuxiong Wu, Massieh Kordi Boroujeny et al.

Adaptive Exploration for Multi-Reward Multi-Policy Evaluation

Alessio Russo, Aldo Pacchiano

Inverse Optimization via Learning Feasible Regions

Ke Ren, Peyman Mohajerin Esfahani, Angelos Georghiou

GRAIL: Graph Edit Distance and Node Alignment using LLM-Generated Code

Samidha Verma, Arushi Goyal, Ananya Mathur et al.

Multi-Marginal Stochastic Flow Matching for High-Dimensional Snapshot Data at Irregular Time Points

Justin Lee, Behnaz Moradi-Jamei, Heman Shakeri

Preserving AUC Fairness in Learning with Noisy Protected Groups

Mingyang Wu, Li Lin, Wenbin Zhang et al.

Principled Algorithms for Optimizing Generalized Metrics in Binary Classification

Anqi Mao, Mehryar Mohri, Yutao Zhong

Mastering Multiple-Expert Routing: Realizable $H$-Consistency and Strong Guarantees for Learning to Defer

Anqi Mao, Mehryar Mohri, Yutao Zhong

Balancing the Scales: A Theoretical and Algorithmic Framework for Learning from Imbalanced Data

Corinna Cortes, Anqi Mao, Mehryar Mohri et al.

FEAT-KD: Learning Concise Representations for Single and Multi-Target Regression via TabNet Knowledge Distillation

Kei Sen Fong, Mehul Motani

System-Aware Unlearning Algorithms: Use Lesser, Forget Faster

Linda Lu, Ayush Sekhari, Karthik Sridharan

VideoJAM: Joint Appearance-Motion Representations for Enhanced Motion Generation in Video Models

Hila Chefer, Uriel Singer, Amit Zohar et al.

Learning Extrapolative Sequence Transformations from Markov Chains

Sophia Hager, Aleem Khan, Andrew Wang et al.

SketchDNN: Joint Continuous-Discrete Diffusion for CAD Sketch Generation

Sathvik Chereddy, John Femiani

Context Matters: Query-aware Dynamic Long Sequence Modeling of Gigapixel Images

Zhengrui Guo, Qichen Sun, Jiabo MA et al.

Meta-Black-Box-Optimization through Offline Q-function Learning

Zeyuan Ma, Zhiguang Cao, Zhou Jiang et al.

From Theory to Practice: Rethinking Green and Martin Kernels for Unleashing Graph Transformers

Yoon Hyeok Lee, Jaemin Park, Taejin Paik et al.

Provably Efficient Exploration in Inverse Constrained Reinforcement Learning

Bo Yue, Jian Li, Guiliang Liu

Aligning LLMs by Predicting Preferences from User Writing Samples

Stéphane Aroca-Ouellette, Natalie Mackraz, Barry-John Theobald et al.

Maximum Coverage in Turnstile Streams with Applications to Fingerprinting Measures

Alina Ene, Alessandro Epasto, Vahab Mirrokni et al.

Determinant Estimation under Memory Constraints and Neural Scaling Laws

Siavash Ameli, Chris van der Heide, Liam Hodgkinson et al.

Field Matching: an Electrostatic Paradigm to Generate and Transfer Data

Alexander Kolesov, S. Manukhov, Vladimir Palyulin et al.

Position: Current Model Licensing Practices are Dragging Us into a Quagmire of Legal Noncompliance

Moming Duan, Mingzhe Du, Rui Zhao et al.

Improving Multi-Class Calibration through Normalization-Aware Isotonic Techniques

Alon Arad, Saharon Rosset

Categorical Schrödinger Bridge Matching

Grigoriy Ksenofontov, Aleksandr Korotin

Inverse Bridge Matching Distillation

Nikita Gushchin, David Li, Daniil Selikhanovych et al.

Understanding the Emergence of Multimodal Representation Alignment

Megan Tjandrasuwita, Chanakya Ekbote, Liu Ziyin et al.

A Non-isotropic Time Series Diffusion Model with Moving Average Transitions

Chenxi Wang, Linxiao Yang, Zhixian Wang et al.

Conditional Diffusion Model with Nonlinear Data Transformation for Time Series Forecasting

RISHI JINKA, Venkata Sai Mothish Gonugunta, Deepak N. Subramani

Adaptive Partitioning Schemes for Optimistic Optimization

Raja Sunkara, Ardhendu Tripathy

Plan-and-Act: Improving Planning of Agents for Long-Horizon Tasks

Lutfi Erdogan, Hiroki Furuta, Sehoon Kim et al.

VersaPRM: Multi-Domain Process Reward Model via Synthetic Reasoning Data

Thomas Zeng, Shuibai Zhang, Shutong Wu et al.

GTR: A General, Multi-View, and Dynamic Framework for Trajectory Representation Learning

Xiangheng Wang, Ziquan Fang, Chenglong Huang et al.

DataDecide: How to Predict Best Pretraining Data with Small Experiments

Ian Magnusson, Tai Nguyen, Ben Bogin et al.

Semantic Shift Estimation via Dual-Projection and Classifier Reconstruction for Exemplar-Free Class-Incremental Learning

Run He, Di Fang, Yicheng Xu et al.

SAND: One-Shot Feature Selection with Additive Noise Distortion

Pedram Pad, Hadi Hammoud, Mohamad Dia et al.

Unpaired Point Cloud Completion via Unbalanced Optimal Transport

Taekyung Lee, Jaemoo Choi, Jaewoong Choi et al.

Online Curvature-Aware Replay: Leveraging $\mathbf{2^{nd}}$ Order Information for Online Continual Learning

Edoardo Urettini, Antonio Carta

Look Twice Before You Answer: Memory-Space Visual Retracing for Hallucination Mitigation in Multimodal Large Language Models

Xin Zou, Yizhou WANG, Yibo Yan et al.

Guided Search Strategies in Non-Serializable Environments with Applications to Software Engineering Agents

Karina Zainullina, Aleksandr Golubev, Maria Trofimova et al.

Shifting Time: Time-series Forecasting with Khatri-Rao Neural Operators

Srinath Dama, Kevin L Course, Prasanth B Nair

iN2V: Bringing Transductive Node Embeddings to Inductive Graphs

Nicolas Lell, Ansgar Scherp

Understanding Sharpness Dynamics in NN Training with a Minimalist Example: The Effects of Dataset Difficulty, Depth, Stochasticity, and More

Geonhui Yoo, Minhak Song, Chulhee Yun

Provable Benefit of Random Permutations over Uniform Sampling in Stochastic Coordinate Descent

Donghwa Kim, Jaewook Lee, Chulhee Yun

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty

Yeseul Cho, Baekrok Shin, Changmin Kang et al.

AutoCATE: End-to-End, Automated Treatment Effect Estimation

Toon Vanderschueren, Tim Verdonck, Mihaela van der Schaar et al.

Where is the Truth? The Risk of Getting Confounded in a Continual World

Florian Peter Busch, Roshni Ramanna Kamath, Rupert Mitchell et al.

Provable Policy Gradient for Robust Average-Reward MDPs Beyond Rectangularity

Qiuhao Wang, Yuqi Zha, Chin Pang Ho et al.

Categorical Distributional Reinforcement Learning with Kullback-Leibler Divergence: Convergence and Asymptotics

Tyler Kastner, Mark Rowland, Yunhao Tang et al.

What can large language models do for sustainable food?

Anna Thomas, Adam Yee, Andrew Mayne et al.

Sample-Optimal Agnostic Boosting with Unlabeled Data

Udaya Ghai, Karan Singh

Discrete Neural Algorithmic Reasoning

Gleb Rodionov, Liudmila Prokhorenkova

Multi-View Graph Clustering via Node-Guided Contrastive Encoding

Yazhou Ren, Junlong Ke, Zichen Wen et al.

TreeLoRA: Efficient Continual Learning via Layer-Wise LoRAs Guided by a Hierarchical Gradient-Similarity Tree

Yu-Yang Qian, Yuan-Ze Xu, Zhen-Yu Zhang et al.

Hybrid Quantum-Classical Multi-Agent Pathfinding

Thore Gerlach, Loong Kuan Lee, Frederic BARBARESCO et al.

Catoni Contextual Bandits are Robust to Heavy-tailed Rewards

Chenlu Ye, Yujia Jin, Alekh Agarwal et al.

Efficient Multivariate Robust Mean Estimation Under Mean-Shift Contamination

Ilias Diakonikolas, Giannis Iakovidis, Daniel Kane et al.

Revealing Weaknesses in Text Watermarking Through Self-Information Rewrite Attacks

Yixin Cheng, Hongcheng Guo, Yangming Li et al.

An Optimistic Algorithm for online CMDPS with Anytime Adversarial Constraints

Jiahui Zhu, Kihyun Yu, Dabeen Lee et al.

Active Learning for Efficient Discovery of Optimal Combinatorial Perturbations

Jason Qin, Hans-Hermann Wessels, Carlos Fernandez-Granda et al.

KinDEL: DNA-Encoded Library Dataset for Kinase Inhibitors

Benson Chen, Tomasz Danel, Gabriel Dreiman et al.

Understanding and Mitigating Miscalibration in Prompt Tuning for Vision-Language Models

Shuoyuan Wang, Sharon Li, Hongxin Wei

Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks

Maya Bechler-Speicher, Ben Finkelshtein, Fabrizio Frasca et al.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach

Changdae Oh, zhen fang, Shawn Im et al.

Steer LLM Latents for Hallucination Detection

Seongheon Park, Xuefeng Du, Min-Hsuan Yeh et al.

CLARIFY: Contrastive Preference Reinforcement Learning for Untangling Ambiguous Queries

Ni Mu, Hao Hu, Xiao Hu et al.

Towards a Formal Theory of Representational Compositionality

Eric Elmoznino, Thomas Jiralerspong, Yoshua Bengio et al.

Reinforcement Learning with Adaptive Reward Modeling for Expensive-to-Evaluate Systems

Hongyuan Su, Yu Zheng, Yuan Yuan et al.

Cover learning for large-scale topology representation

Luis Scoccola, Uzu Lim, Heather Harrington

Diffusion-based Adversarial Purification from the Perspective of the Frequency Domain

Gaozheng Pei, Ke Ma, Yingfei Sun et al.

Guardians of Image Quality: Benchmarking Defenses Against Adversarial Attacks on Image Quality Metrics

Aleksandr Gushchin, Khaled Abud, Georgii Bychkov et al.

BDC-CLIP: Brownian Distance Covariance for Adapting CLIP to Action Recognition

Fei Long, Xiaoou Li, jiaming Lv et al.

Quadratic Upper Bound for Boosting Robustness

Euijin You, Hyang-Won Lee

Compute or Load KV Cache? Why Not Both?

Shuowei Jin, Xueshen Liu, Qingzhao Zhang et al.

Prediction-Powered Adaptive Shrinkage Estimation

Sida Li, Nikolaos Ignatiadis

Predicting High-precision Depth on Low-Precision Devices Using 2D Hilbert Curves

Mykhailo Uss, Ruslan Yermolenko, Oleksii Shashko et al.

CVE-Bench: A Benchmark for AI Agents’ Ability to Exploit Real-World Web Application Vulnerabilities

Yuxuan Zhu, Antony Kellermann, Dylan Bowman et al.

Backdoor Attacks in Token Selection of Attention Mechanism

Yunjuan Wang, Raman Arora

Differentiable Structure Learning with Ancestral Constraints

Taiyu Ban, Changxin Rong, Xiangyu Wang et al.

MONA: Myopic Optimization with Non-myopic Approval Can Mitigate Multi-step Reward Hacking

Sebastian Farquhar, Vikrant Varma, David Lindner et al.

Explainable Concept Generation through Vision-Language Preference Learning for Understanding Neural Networks' Internal Representations

Aditya Taparia, Som Sagar, Ransalu Senanayake

Independence Tests for Language Models

Sally Zhu, Ahmed Ahmed, Rohith Kuditipudi et al.

QoS-Efficient Serving of Multiple Mixture-of-Expert LLMs Using Partial Runtime Reconfiguration

HamidReza Imani, Jiaxin Peng, Peiman Mohseni et al.

Stability and Generalization Analysis of Decentralized SGD: Sharper Bounds Beyond Lipschitzness and Smoothness

Shuang Zeng, Yunwen Lei

Position: Rethinking LLM Bias Probing Using Lessons from the Social Sciences

Kirsten Morehouse, Siddharth Swaroop, Weiwei Pan

PPDiff: Diffusing in Hybrid Sequence-Structure Space for Protein-Protein Complex Design

Zhenqiao Song, Tianxiao Li, Lei Li et al.

Beyond Log-Concavity and Score Regularity: Improved Convergence Bounds for Score-Based Generative Models in W2-distance

Marta Gentiloni Silveri, Antonio Ocello

Robust Secure Swap: Responsible Face Swap With Persons of Interest Redaction and Provenance Traceability

Yunshu Dai, Jianwei Fei, Fangjun Huang et al.

Stronger Neyman Regret Guarantees for Adaptive Experimental Design

Georgy Noarov, Riccardo Fogliato, Martin A Bertran et al.

When, Where and Why to Average Weights?

Niccolò Ajroldi, Antonio Orvieto, Jonas Geiping

BanditSpec: Adaptive Speculative Decoding via Bandit Algorithms

Yunlong Hou, Fengzhuo Zhang, Cunxiao Du et al.

Vintix: Action Model via In-Context Reinforcement Learning

Andrei Polubarov, Nikita Lyubaykin, Alexander Derevyagin et al.

Minimum Width for Universal Approximation using Squashable Activation Functions

Jonghyun Shin, Namjun Kim, Geonho Hwang et al.

Permutation-Free High-Order Interaction Tests

Zhaolu Liu, Robert Peach, Mauricio Barahona

Multi-Timescale Dynamics Model Bayesian Optimization for Plasma Stabilization in Tokamaks

Rohit Sonker, Alexandre Capone, Andrew Rothstein et al.

On the Learnability of Distribution Classes with Adaptive Adversaries

Tosca Lechner, Alex Bie, Gautam Kamath

Efficient and Privacy-Preserving Soft Prompt Transfer for LLMs

Xun Wang, Jing Xu, Franziska Boenisch et al.

RoSTE: An Efficient Quantization-Aware Supervised Fine-Tuning Approach for Large Language Models

Quan Wei, Chung-Yiu Yau, Hoi To Wai et al.

Towards Attributions of Input Variables in a Coalition

Xinhao Zheng, Huiqi Deng, Quanshi Zhang

B-score: Detecting biases in large language models using response history

An Vo, Mohammad Reza Taesiri, Daeyoung Kim et al.

NTK-DFL: Enhancing Decentralized Federated Learning in Heterogeneous Settings via Neural Tangent Kernel

Gabriel Thompson, Kai Yue, Chau-Wai Wong et al.

R.I.P.: Better Models by Survival of the Fittest Prompts

Ping Yu, Weizhe Yuan, Olga Golovneva et al.

From Kernels to Features: A Multi-Scale Adaptive Theory of Feature Learning

Noa Rubin, Kirsten Fischer, Javed Lindner et al.

Diversified Flow Matching with Translation Identifiability

Sagar Shrestha, Xiao Fu

Data-Driven Selection of Instrumental Variables for Additive Nonlinear, Constant Effects Models

Xichen Guo, Feng Xie, Yan Zeng et al.

The Panaceas for Improving Low-Rank Decomposition in Communication-Efficient Federated Learning

Shiwei Li, Xiandi Luo, Haozhao Wang et al.

Adapting While Learning: Grounding LLMs for Scientific Problems with Tool Usage Adaptation

Bohan Lyu, Yadi Cao, Duncan Watson-Parris et al.

Discovering Spoofing Attempts on Language Model Watermarks

Thibaud Gloaguen, Nikola Jovanović, Robin Staab et al.

Integration-free Kernels for Equivariant Gaussian Process Modelling

Tim Steinert, David Ginsbourger, August Lykke-Møller et al.

Copilot Arena: A Platform for Code LLM Evaluation in the Wild

Wayne Chi, Valerie Chen, Anastasios Angelopoulos et al.

Craftium: Bridging Flexibility and Efficiency for Rich 3D Single- and Multi-Agent Environments

Mikel Malagón, Josu Ceberio, Jose A Lozano

Instance Correlation Graph-based Naive Bayes

Chengyuan Li, Liangxiao Jiang, Wenjun Zhang et al.

Graph Minimum Factor Distance and Its Application to Large-Scale Graph Data Clustering

Jicong Fan

A Cross Modal Knowledge Distillation & Data Augmentation Recipe for Improving Transcriptomics Representations through Morphological Features

Ihab Bendidi, Yassir El Mesbahi, Alisandra Denton et al.

Discovering Physics Laws of Dynamical Systems via Invariant Function Learning

Shurui Gui, Xiner Li, Shuiwang Ji

Human-Aligned Image Models Improve Visual Decoding from the Brain

Nona Rajabi, Antonio Ribeiro, Miguel Vasco et al.

Primal-Dual Neural Algorithmic Reasoning

Yu He, Ellen Vitercik

Test-Time Learning for Large Language Models

Jinwu Hu, Zitian Zhang, Guohao Chen et al.

The Batch Complexity of Bandit Pure Exploration

Adrienne Tuynman, Rémy Degenne

Optimal Decision Tree Pruning Revisited: Algorithms and Complexity

Juha Harviainen, Frank Sommer, Manuel Sorge et al.

ITBench: Evaluating AI Agents across Diverse Real-World IT Automation Tasks

Saurabh Jha, Rohan Arora, Yuji Watanabe et al.

Minerva: A Programmable Memory Test Benchmark for Language Models

Menglin Xia, Victor Ruehle, Saravanakumar Rajmohan et al.

NeuralCohort: Cohort-aware Neural Representation Learning for Healthcare Analytics

Changshuo Liu, Lingze Zeng, Kaiping Zheng et al.

Lean and Mean Adaptive Optimization via Subset-Norm and Subspace-Momentum with Convergence Guarantees

Thien Nguyen, Huy Nguyen

Interaction-Aware Gaussian Weighting for Clustered Federated Learning

Alessandro Licciardi, Davide Leo, Eros Fanì et al.

Private Federated Learning using Preference-Optimized Synthetic Data

Charlie Hou, Mei-Yu Wang, Yige Zhu et al.

EquivaMap: Leveraging LLMs for Automatic Equivalence Checking of Optimization Formulations

Haotian Zhai, Connor Lawless, Ellen Vitercik et al.

Alberta Wells Dataset: Pinpointing Oil and Gas Wells from Satellite Imagery

Pratinav Seth, Michelle Lin, BREFO YAW et al.

AutoAL: Automated Active Learning with Differentiable Query Strategy Search

Yifeng Wang, Xueying Zhan, Siyu Huang

Solving Zero-Sum Convex Markov Games

Fivos Kalogiannis, Emmanouil-Vasileios Vlatakis-Gkaragkounis, Ian Gemp et al.

LIVS: A Pluralistic Alignment Dataset for Inclusive Public Spaces

Rashid Mushkani, Perampalli Shravan Nayak, Hugo Berard et al.

Improved Learning via k-DTW: A Novel Dissimilarity Measure for Curves

Amer Krivosija, Alexander Munteanu, André Nusser et al.

Optimizing Robustness and Accuracy in Mixture of Experts: A Dual-Model Approach

Xu Zhang, Kaidi Xu, Ziqing Hu et al.

A Generic Family of Graphical Models: Diversity, Efficiency, and Heterogeneity

Yufei Huang, Changhu Wang, Junjie Tang et al.

Towards Global-level Mechanistic Interpretability: A Perspective of Modular Circuits of Large Language Models

Yinhan He, Wendy Zheng, Yushun Dong et al.

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis

Christophe Vauthier, Anna Korba, Quentin Mérigot

Density Ratio Estimation with Conditional Probability Paths

Hanlin Yu, Arto Klami, Aapo Hyvarinen et al.

LensLLM: Unveiling Fine-Tuning Dynamics for LLM Selection

Xinyue Zeng, Haohui Wang, Junhong Lin et al.

Generative Social Choice: The Next Generation

Niclas Boehmer, Sara Fish, Ariel Procaccia

UltraTWD: Optimizing Ultrametric Trees for Tree-Wasserstein Distance

Fangchen Yu, Yanzhen Chen, Jiaxing Wei et al.

TabFlex: Scaling Tabular Learning to Millions with Linear Attention

Yuchen Zeng, Tuan Dinh, Wonjun Kang et al.

Not All Wrong is Bad: Using Adversarial Examples for Unlearning

Ali Ebrahimpour-Boroojeny, Hari Sundaram, Varun Chandrasekaran

In-Context Adaptation to Concept Drift for Learned Database Operations

Jiaqi Zhu, Shaofeng Cai, Shen et al.

Self-Supervised Transformers as Iterative Solution Improvers for Constraint Satisfaction

Yudong W Xu, Wenhao Li, Scott Sanner et al.

Efficiently Vectorized MCMC on Modern Accelerators

Hugh Dance, Pierre Glaser, Peter Orbanz et al.

Understanding Complexity in VideoQA via Visual Program Generation

Cristobal Eyzaguirre, Igor Vasiljevic, Achal Dave et al.

Optimization for Neural Operators can Benefit from Width

Pedro Cisneros-Velarde, Bhavesh Shrimali, Arindam Banerjee

Reasoning-as-Logic-Units: Scaling Test-Time Reasoning in Large Language Models Through Logic Unit Alignment

Cheryl Li, Tianyuan Xu, Yiwen Guo

Adversarial Inputs for Linear Algebra Backends

Jonas Möller, Lukas Pirch, Felix Weissberg et al.

Proto Successor Measure: Representing the Behavior Space of an RL Agent

Siddhant Agarwal, Harshit Sikchi, Peter Stone et al.

SKOLR: Structured Koopman Operator Linear RNN for Time-Series Forecasting

Yitian Zhang, Liheng Ma, Antonios Valkanas et al.

Beyond Topological Self-Explainable GNNs: A Formal Explainability Perspective

Steve Azzolin, SAGAR MALHOTRA, Andrea Passerini et al.

Continual Generalized Category Discovery: Learning and Forgetting from a Bayesian Perspective

Hao Dai, Jagmohan Chauhan

Pareto-Optimal Fronts for Benchmarking Symbolic Regression Algorithms

Kei Sen Fong, Mehul Motani

Towards Cost-Effective Reward Guided Text Generation

Ahmad Rashid, Ruotian Wu, Rongqi Fan et al.