ICML Papers
5,975 papers found • Page 12 of 120
Conformal Tail Risk Control for Large Language Model Alignment
Catherine Chen, Jingyan Shen, Xinyu Yang et al.
Conformity Score Averaging for Classification
Rui Luo, Zhixin Zhou
Confounder-Free Continual Learning via Recursive Feature Normalization
Yash Shah, Camila Gonzalez, MohammadHassan Abbasi et al.
ConfPO: Exploiting Policy Model Confidence for Critical Token Selection in Preference Optimization
Hee Suk Yoon, Eunseop Yoon, Mark Hasegawa-Johnson et al.
Connecting Thompson Sampling and UCB: Towards More Efficient Trade-offs Between Privacy and Regret
Bingshan Hu, Zhiming Huang, Tianyue Zhang et al.
Consensus Based Stochastic Optimal Control
Liyao Lyu, Jingrun Chen
Consensus Is All You Get: The Role of Attention in Transformers
Alvaro Rodriguez Abella, João Pedro Silvestre, Paulo Tabuada
Conservative Offline Goal-Conditioned Implicit V-Learning
Ke Kaiqiang, qian lin, Zongkai Liu et al.
Constant Stepsize Local GD for Logistic Regression: Acceleration by Instability
Michael Crawshaw, Blake Woodworth, Mingrui Liu
Constrain Alignment with Sparse Autoencoders
Qingyu Yin, Chak Tou Leong, Hongbo Zhang et al.
Constrained Belief Updates Explain Geometric Structures in Transformer Representations
Mateusz Piotrowski, Paul Riechers, Daniel Filan et al.
Constrained Exploitability Descent: An Offline Reinforcement Learning Method for Finding Mixed-Strategy Nash Equilibrium
Runyu Lu, Yuanheng Zhu, Dongbin Zhao
Constrained Online Convex Optimization with Polyak Feasibility Steps
Spencer Hutchinson, Mahnoosh Alizadeh
Constrained Pareto Set Identification with Bandit Feedback
Cyrille Kone, Emilie Kaufmann, Laura Richert
ConText: Driving In-context Learning for Text Removal and Segmentation
Fei Zhang, Pei Zhang, Baosong Yang et al.
Context-Informed Neural ODEs Unexpectedly Identify Broken Symmetries: Insights from the Poincaré–Hopf Theorem
In Huh, Changwook Jeong, Muhammad Alam
Context is Key: A Benchmark for Forecasting with Essential Textual Information
Andrew Williams, Arjun Ashok, Étienne Marcotte et al.
Context Matters: Query-aware Dynamic Long Sequence Modeling of Gigapixel Images
Zhengrui Guo, Qichen Sun, Jiabo MA et al.
Contextual Bandits for Unbounded Context Distributions
Puning Zhao, Rongfei Fan, Shaowei Wang et al.
Contextual Linear Bandits with Delay as Payoff
Mengxiao Zhang, Yingfei Wang, Haipeng Luo
Contextual Online Decision Making with Infinite-Dimensional Functional Regression
Haichen Hu, Rui Ai, Stephen Bates et al.
Contextual Optimization Under Model Misspecification: A Tractable and Generalizable Approach
Omar Bennouna, Jiawei Zhang, Saurabh Amin et al.
Contextures: Representations from Contexts
Runtian Zhai, Kai Yang, Burak VARICI et al.
Continual Generalized Category Discovery: Learning and Forgetting from a Bayesian Perspective
Hao Dai, Jagmohan Chauhan
Continual Reinforcement Learning by Planning with Online World Models
Zichen Liu, Guoji Fu, Chao Du et al.
Continuous Bayesian Model Selection for Multivariate Causal Discovery
Anish Dhir, Ruby Sedgwick, Avinash Kori et al.
Continuously Updating Digital Twins using Large Language Models
Harry Amad, Nicolás Astorga, Mihaela van der Schaar
Continuous Semi-Implicit Models
Longlin Yu, Jiajun Zha, Tong Yang et al.
Continuous-Time Analysis of Heavy Ball Momentum in Min-Max Games
Yi Feng, Kaito Fujii, EFSTRATIOS PANTELEIMON SKOULAKIS et al.
Continuous Visual Autoregressive Generation via Score Maximization
Chenze Shao, Fandong Meng, Jie Zhou
Contour Integration Underlies Human-Like Vision
Ben Lonnqvist, Elsa Scialom, Abdulkadir Gokce et al.
Contract Design Under Approximate Best Responses
Francesco Bacchiocchi, Jiarui Gan, Matteo Castiglioni et al.
Contradiction Retrieval via Contrastive Learning with Sparsity
Haike Xu, Zongyu Lin, Kai-Wei Chang et al.
Contrastive Learning with Simplicial Convolutional Networks for Short-Text Classification
Liang Huang, Benedict Lee, Daniel Ng et al.
Contrastive Localized Language-Image Pre-Training
Hong-You Chen, Zhengfeng Lai, Haotian Zhang et al.
Contrastive Private Data Synthesis via Weighted Multi-PLM Fusion
Tianyuan Zou, Yang Liu, Peng Li et al.
Contrastive Visual Data Augmentation
Yu Zhou, Bingxuan Li, Mohan Tang et al.
Control and Realism: Best of Both Worlds in Layout-to-Image without Training
Bonan Li, Yinhan Hu, Songhua Liu et al.
Controllable Data Generation with Hierarchical Neural Representations
Sheyang Tang, xiaoyu xu, Jiayan Qiu et al.
Controlled Generation with Equivariant Variational Flow Matching
Floor Eijkelboom, Heiko Zimmermann, Sharvaree Vadgama et al.
Controlling Large Language Model with Latent Action
Chengxing Jia, Ziniu Li, Pengyuan Wang et al.
Controlling Neural Collapse Enhances Out-of-Distribution Detection and Transfer Learning
Md Yousuf Harun, Jhair Gallardo, Christopher Kanan
Controlling Underestimation Bias in Constrained Reinforcement Learning for Safe Exploration
Shiqing Gao, Jiaxin Ding, Luoyi Fu et al.
Convergence Analysis of Policy Gradient Methods with Dynamic Stochasticity
Alessandro Montenegro, Marco Mussi, Matteo Papini et al.
Convergence of Consistency Model with Multistep Sampling under General Data Assumptions
Yiding Chen, Yiyi Zhang, Owen Oertell et al.
Convergence of Mean-Field Langevin Stochastic Descent-Ascent for Distributional Minimax Optimization
Zhangyi Liu, Feng Liu, Rui Gao et al.
Convergence of Policy Mirror Descent Beyond Compatible Function Approximation
Uri Sherman, Tomer Koren, Yishay Mansour
Convex Markov Games: A New Frontier for Multi-Agent Reinforcement Learning
Ian Gemp, Andreas Haupt, Luke Marris et al.
Cooperation of Experts: Fusing Heterogeneous Information with Large Margin
Shuo Wang, Shunyang Huang, Jinghui Yuan et al.
Copilot Arena: A Platform for Code LLM Evaluation in the Wild
Wayne Chi, Valerie Chen, Anastasios Angelopoulos et al.