ICML Papers
5,975 papers found • Page 8 of 120
Beyond Entropy: Region Confidence Proxy for Wild Test-Time Adaptation
Zixuan Hu, Yichun Hu, Xiaotong Li et al.
Beyond Induction Heads: In-Context Meta Learning Induces Multi-Phase Circuit Emergence
Gouki Minegishi, Hiroki Furuta, Shohei Taniguchi et al.
Beyond Log-Concavity and Score Regularity: Improved Convergence Bounds for Score-Based Generative Models in W2-distance
Marta Gentiloni Silveri, Antonio Ocello
Beyond Low-rank Decomposition: A Shortcut Approach for Efficient On-Device Learning
Le-Trung Nguyen, Aël Quélennec, Van-Tam Nguyen et al.
Beyond Matryoshka: Revisiting Sparse Coding for Adaptive Representation
Tiansheng Wen, Yifei Wang, Zequn Zeng et al.
Beyond Message Passing: Neural Graph Pattern Machine
Zehong Wang, Zheyuan Zhang, Tianyi MA et al.
Beyond Minimax Rates in Group Distributionally Robust Optimization via a Novel Notion of Sparsity
Quan Nguyen, Nishant Mehta, Cristóbal Guzmán
Beyond One-Hot Labels: Semantic Mixing for Model Calibration
Haoyang Luo, Linwei Tao, Minjing Dong et al.
Beyond Self-Interest: How Group Strategies Reshape Content Creation in Recommendation Platforms?
Yaolong Yu, Fan Yao, Sinno Jialin Pan
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs
Jie Hu, Yi-Ting Ma, Do-Young Eun
Beyond Sensor Data: Foundation Models of Behavioral Data from Wearables Improve Health Predictions
Eray Erturk, Fahad Kamran, Salar Abbaspourazad et al.
Beyond Task-Specific Reasoning: A Unified Conditional Generative Framework for Abstract Visual Reasoning
Fan Shi, Bin Li, Xiangyang Xue
Beyond the Permutation Symmetry of Transformers: The Role of Rotation for Model Fusion
Binchi Zhang, Zaiyi Zheng, Zhengzhang Chen et al.
Beyond The Rainbow: High Performance Deep Reinforcement Learning on a Desktop PC
Tyler Clark, Mark Towers, Christine Evers et al.
Beyond Topological Self-Explainable GNNs: A Formal Explainability Perspective
Steve Azzolin, SAGAR MALHOTRA, Andrea Passerini et al.
Beyond Zero Initialization: Investigating the Impact of Non-Zero Initialization on LoRA Fine-Tuning Dynamics
Shiwei Li, Xiandi Luo, Xing Tang et al.
BiAssemble: Learning Collaborative Affordance for Bimanual Geometric Assembly
Yan Shen, Ruihai Wu, Yubin Ke et al.
Bifurcate then Alienate: Incomplete Multi-view Clustering via Coupled Distribution Learning with Linear Overhead
Shengju Yu, Yiu-ming Cheung, Siwei Wang et al.
BILBO: BILevel Bayesian Optimization
Ruth Wan Theng Chew, Quoc Phong Nguyen, Bryan Kian Hsiang Low
BiMaCoSR: Binary One-Step Diffusion Model Leveraging Flexible Matrix Compression for Real Super-Resolution
Kai Liu, Kaicheng Yang, Zheng Chen et al.
BiMark: Unbiased Multilayer Watermarking for Large Language Models
Xiaoyan Feng, He Zhang, Yanjun Zhang et al.
Binary Hypothesis Testing for Softmax Models and Leverage Score Models
Yuzhou Gu, Zhao Song, Junze Yin
BinauralFlow: A Causal and Streamable Approach for High-Quality Binaural Speech Synthesis with Flow Matching Models
Susan Liang, Dejan Markovic, Israel D. Gebru et al.
Bipartite Ranking From Multiple Labels: On Loss Versus Label Aggregation
Michal Lukasik, Lin Chen, Harikrishna Narasimhan et al.
Bi-perspective Splitting Defense: Achieving Clean-Seed-Free Backdoor Security
Yangyang Shen, Xiao Tan, Dian Shen et al.
Bivariate Causal Discovery with Proxy Variables: Integral Solving and Beyond
Yong Wu, Yanwei Fu, Shouyan Wang et al.
Black-Box Adversarial Attacks on LLM-Based Code Completion
Slobodan Jenko, Niels Mündler, Jingxuan He et al.
Blink of an eye: a simple theory for feature localization in generative models
Marvin Li, Aayush Karan, Sitan Chen
BlockDialect: Block-wise Fine-grained Mixed Format Quantization for Energy-Efficient LLM Inference
Wonsuk Jang, Thierry Tambe
BoA: Attention-aware Post-training Quantization without Backpropagation
Junhan Kim, Ho-young Kim, Eulrang Cho et al.
Bongard in Wonderland: Visual Puzzles that Still Make AI Go Mad?
Antonia Wüst, Tim Woydt, Lukas Helff et al.
BOOD: Boundary-based Out-Of-Distribution Data Generation
Qilin Liao, Shuo Yang, Bo Zhao et al.
Boost-and-Skip: A Simple Guidance-Free Diffusion for Minority Generation
Soobin Um, Beomsu Kim, Jong Chul YE
Boosting Adversarial Robustness with CLAT: Criticality Leveraged Adversarial Training
Bhavna Gopal, Huanrui Yang, Jingyang Zhang et al.
Boosting Masked ECG-Text Auto-Encoders as Discriminative Learners
Hung Manh Pham, Aaqib Saeed, Dong Ma
Boosting Multi-Domain Fine-Tuning of Large Language Models through Evolving Interactions between Samples
Xize Liang, Lin Yang, Jie Wang et al.
Boosting Protein Graph Representations through Static-Dynamic Fusion
Pengkang Guo, Bruno Correia, Pierre Vandergheynst et al.
Boosting Virtual Agent Learning and Reasoning: A Step-Wise, Multi-Dimensional, and Generalist Reward Model with Benchmark
Bingchen Miao, Yang Wu, Minghe Gao et al.
Bootstrapping Self-Improvement of Language Model Programs for Zero-Shot Schema Matching
Nabeel Seedat, Mihaela van der Schaar
BOPO: Neural Combinatorial Optimization via Best-anchored and Objective-guided Preference Optimization
Zijun Liao, Jinbiao Chen, Debing Wang et al.
Bounded Rationality for LLMs: Satisficing Alignment at Inference-Time
Mohamad Chehade, Soumya Suvra Ghosal, Souradip Chakraborty et al.
BounDr.E: Predicting Drug-likeness via Biomedical Knowledge Alignment and EM-like One-Class Boundary Optimization
Dongmin Bang, Inyoung Sung, Yinhua Piao et al.
BoxLM: Unifying Structures and Semantics of Medical Concepts for Diagnosis Prediction in Healthcare
Yanchao Tan, Hang Lv, Yunfei Zhan et al.
Branches: Efficiently Seeking Optimal Sparse Decision Trees via AO*
Ayman Chaouki, Jesse Read, Albert Bifet
Breaking Barriers: Combinatorial Algorithms for Non-Monotone Submodular Maximization with Sublinear Adaptivity and $1/e$ Approximation
Yixin Chen, Wenjing Chen, Alan Kuhnle
Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting
Zhining Liu, Ze Yang, Xiao Lin et al.
Breaking the $n^{1.5}$ Additive Error Barrier for Private and Efficient Graph Sparsification via Private Expander Decomposition
Anders Aamand, Justin Chen, Mina Dalirrooyfard et al.
Breaking the Barrier of Hard Samples: A Data-Centric Approach to Synthetic Data for Medical Tasks
Maynara de Souza, Cleber Zanchettin
Breaking the Curse of Multiagency in Robust Multi-Agent Reinforcement Learning
Laixi Shi, Jingchu Gai, Eric Mazumdar et al.
Breaking the Quadratic Barrier: Robust Cardinality Sketches for Adaptive Queries
Edith Cohen, Mihir Singhal, Uri Stemmer