ICML Poster Papers
5,104 papers found • Page 5 of 103
A Square Peg in a Square Hole: Meta-Expert for Long-Tailed Semi-Supervised Learning
Yaxin Hou, Yuheng Jia
Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models
Kejia Chen, Jiawen Zhang, Jiacong Hu et al.
AssistanceZero: Scalably Solving Assistance Games
Cassidy Laidlaw, Eli Bronstein, Timothy Guo et al.
A Stronger Mixture of Low-Rank Experts for Fine-Tuning Foundation Models
Mengyang Sun, Yihao Wang, Tao Feng et al.
A Sub-Problem Quantum Alternating Operator Ansatz for Correlation Clustering
Lucas Fabian Naumann, Jannik Irmai, Bjoern Andres
Asymmetric Decision-Making in Online Knowledge Distillation: Unifying Consensus and Divergence
zhaowei chen, Borui Zhao, Yuchen Ge et al.
AsymRnR: Video Diffusion Transformers Acceleration with Asymmetric Reduction and Restoration
Wenhao SUN, Rong-Cheng Tu, Jingyi Liao et al.
ATA: Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning
Artavazd Maranjyan, El Mehdi Saad, Peter Richtarik et al.
A Tale of Two Structures: Do LLMs Capture the Fractal Complexity of Language?
Ibrahim Alabdulmohsin, Andreas Steiner
A Theoretical Framework For Overfitting In Energy-based Modeling
Giovanni Catania, Aurélien Decelle, Cyril Furtlehner et al.
A Theoretical Justification for Asymmetric Actor-Critic Algorithms
Gaspard Lambrechts, Damien Ernst, Aditya Mahajan
A Theoretical Study of (Hyper) Self-Attention through the Lens of Interactions: Representation, Training, Generalization
Muhammed Ustaomeroglu, Guannan Qu
A Theory for Conditional Generative Modeling on Multiple Data Sources
Rongzhen Wang, Yan Zhang, Chenyu Zheng et al.
AtlasD: Automatic Local Symmetry Discovery
Manu Bhat, Jonghyun Park, Jianke Yang et al.
A Trichotomy for List Transductive Online Learning
Steve Hanneke, Amirreza Shaeiri
Attention-Level Speculation
Jack Cai, Ammar Vora, Randolph Zhang et al.
Attention Mechanisms Perspective: Exploring LLM Processing of Graph-Structured Data
Guan Zhong, Likang Wu, Hongke Zhao et al.
Attention-Only Transformers via Unrolled Subspace Denoising
Peng Wang, Yifu Lu, Yaodong Yu et al.
Attributes Shape the Embedding Space of Face Recognition Models
Pierrick Leroy, Antonio Mastropietro, Marco Nurisso et al.
A Two-Stage Learning-to-Defer Approach for Multi-Task Learning
Yannis Montreuil, Shu Heng Yeo, Axel Carlier et al.
Audio Flamingo 2: An Audio-Language Model with Long-Audio Understanding and Expert Reasoning Abilities
Sreyan Ghosh, Zhifeng Kong, Sonal Kumar et al.
Auditing Prompt Caching in Language Model APIs
Chenchen Gu, Xiang Li, Rohith Kuditipudi et al.
A Unified Approach to Routing and Cascading for LLMs
Jasper Dekoninck, Maximilian Baader, Martin Vechev
A Unified Comparative Study with Generalized Conformity Scores for Multi-Output Conformal Regression
Victor Dheur, Matteo Fontana, Yorick Estievenart et al.
A Unified Framework for Generalization Error Analysis of Learning with Arbitrary Discrete Weak Features
Kosuke Sugiyama, Masato Uchida
A Unified View on Learning Unnormalized Distributions via Noise-Contrastive Estimation
Jongha (Jon) Ryu, Abhin Shah, Gregory Wornell
AuPair: Golden Example Pairs for Code Repair
Aditi Mavalankar, Hassan Mansoor, Zita Marinho et al.
AutoAL: Automated Active Learning with Differentiable Query Strategy Search
Yifeng Wang, Xueying Zhan, Siyu Huang
AutoCATE: End-to-End, Automated Treatment Effect Estimation
Toon Vanderschueren, Tim Verdonck, Mihaela van der Schaar et al.
AUTOCIRCUIT-RL: Reinforcement Learning-Driven LLM for Automated Circuit Topology Generation
Prashanth Vijayaraghavan, Luyao Shi, Ehsan Degan et al.
AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling
Alexander Capstick, Rahul G. Krishnan, Payam Barnaghi
Autoencoder-Based Hybrid Replay for Class-Incremental Learning
Milad Khademi Nori, Il-Min Kim, Guanghui Wang
AutoEval Done Right: Using Synthetic Data for Model Evaluation
Pierre Boyeau, Anastasios Angelopoulos, Tianle Li et al.
Autoformulation of Mathematical Optimization Models Using LLMs
Nicolás Astorga, Tennison Liu, Yuanzhang Xiao et al.
Automated Benchmark Generation for Repository-Level Coding Tasks
Konstantinos Vergopoulos, Mark Müller, Martin Vechev
Automated Hypothesis Validation with Agentic Sequential Falsifications
Kexin Huang, Ying Jin, Ryan Li et al.
Automated Red Teaming with GOAT: the Generative Offensive Agent Tester
Maya Pavlova, Erik Brinkman, Krithika Iyer et al.
Automatically Interpreting Millions of Features in Large Language Models
Gonçalo Paulo, Alex Mallen, Caden Juang et al.
Automatic Differentiation of Optimization Algorithms with Time-Varying Updates
Sheheryar Mehmood, Peter Ochs
Automatic Reward Shaping from Confounded Offline Data
Mingxuan Li, Junzhe Zhang, Elias Bareinboim
AutoML-Agent: A Multi-Agent LLM Framework for Full-Pipeline AutoML
Patara Trirat, Wonyong Jeong, Sung Ju Hwang
Autonomy-of-Experts Models
Ang Lv, Ruobing Xie, Yining Qian et al.
Auto-reconfiguration for Latency Minimization in CPU-based DNN Serving
Ankit Bhardwaj, Amar Phanishayee, Deepak Narayanan et al.
AutoStep: Locally adaptive involutive MCMC
Tiange Liu, Nikola Surjanovic, Miguel Biron-Lattes et al.
A Variational Framework for Improving Naturalness in Generative Spoken Language Models
Li-Wei Chen, Takuya Higuchi, Zakaria Aldeneh et al.
A Variational Information Theoretic Approach to Out-of-Distribution Detection
Sudeepta Mondal, Zhuolin Jiang, Ganesh Sundaramoorthi
A Variational Perspective on Generative Protein Fitness Optimization
Lea Bogensperger, Dominik Narnhofer, Ahmed Allam et al.
Average Certified Radius is a Poor Metric for Randomized Smoothing
Chenhao Sun, Yuhao Mao, Mark Müller et al.
Average Sensitivity of Hierarchical $k$-Median Clustering
Shijie Li, Weiqiang He, Ruobing Bai et al.
A Versatile Influence Function for Data Attribution with Non-Decomposable Loss
Junwei Deng, Weijing Tang, Jiaqi Ma