ICML Papers
5,975 papers found • Page 34 of 120
Learning State-Based Node Representations from a Class Hierarchy for Fine-Grained Open-Set Detection
Spandan Pyakurel, Qi Yu
Learning Strategic Language Agents in the Werewolf Game with Iterative Latent Space Policy Optimization
Zelai Xu, Wanjun Gu, Chao Yu et al.
Learning Survival Distributions with the Asymmetric Laplace Distribution
Deming Sheng, Ricardo Henao
Learning the Electronic Hamiltonian of Large Atomic Structures
Chen Hao Xia, Manasa Kaniselvan, Alexandros Nikolaos Ziogas et al.
Learning the RoPEs: Better 2D and 3D Position Encodings with STRING
Connor Schenck, Isaac Reid, Mithun Jacob et al.
Learning Time-Aware Causal Representation for Model Generalization in Evolving Domains
Zhuo He, Shuang Li, Wenze Song et al.
Learning Time-Varying Multi-Region Brain Communications via Scalable Markovian Gaussian Processes
Weihan Li, Yule Wang, Chengrui Li et al.
Learning to Generate Projections for Reducing Dimensionality of Heterogeneous Linear Programming Problems
Tomoharu Iwata, Shinsaku Sakaue
Learning to Incentivize in Repeated Principal-Agent Problems with Adversarial Agent Arrivals
Junyan Liu, ARNAB MAITI, Artin Tajdini et al.
Learning to Keep a Promise: Scaling Language Model Decoding Parallelism with Learned Asynchronous Decoding
Tian Jin, Ellie Cheng, Zachary Ankner et al.
Learning to (Learn at Test Time): RNNs with Expressive Hidden States
Yu Sun, Xinhao Li, Karan Dalal et al.
Learning to Match Unpaired Data with Minimum Entropy Coupling
Mustapha Bounoua, Giulio Franzese, Pietro Michiardi
Learning to Plan & Reason for Evaluation with Thinking-LLM-as-a-Judge
Swarnadeep Saha, Xian Li, Marjan Ghazvininejad et al.
Learning to Quantize for Training Vector-Quantized Networks
Peijia Qin, Jianguo Zhang
Learning to Reuse Policies in State Evolvable Environments
Ziqian Zhang, Bohan Yang, Lihe Li et al.
Learning to Route LLMs with Confidence Tokens
Yu-Neng Chuang, Prathusha Sarma, Parikshit Gopalan et al.
Learning to Steer Learners in Games
Yizhou Zhang, Yian Ma, Eric Mazumdar
Learning to Stop: Deep Learning for Mean Field Optimal Stopping
Lorenzo Magnino, Yuchen Zhu, Mathieu Lauriere
Learning to Trust Bellman Updates: Selective State-Adaptive Regularization for Offline RL
Qin-Wen Luo, Ming-Kun Xie, Ye-Wen Wang et al.
Learning Utilities from Demonstrations in Markov Decision Processes
Filippo Lazzati, Alberto Maria Metelli
Learning Vision and Language Concepts for Controllable Image Generation
Shaoan Xie, Lingjing Kong, Yujia Zheng et al.
Learning with Exact Invariances in Polynomial Time
Ashkan Soleymani, Behrooz Tahmasebi, Stefanie Jegelka et al.
Learning with Expected Signatures: Theory and Applications
Lorenzo Lucchese, Mikko S. Pakkanen, Almut E. D. Veraart
Learning With Multi-Group Guarantees For Clusterable Subpopulations
Jessica Dai, Nika Haghtalab, Eric Zhao
Learning without Isolation: Pathway Protection for Continual Learning
Zhikang Chen, Abudukelimu Wuerkaixi, Sen Cui et al.
Learning with Selectively Labeled Data from Multiple Decision-makers
Jian Chen, Zhehao Li, Xiaojie Mao
Learn Singularly Perturbed Solutions via Homotopy Dynamics
Chuqi CHEN, Yahong Yang, Yang Xiang et al.
Learn to Vaccinate: Combining Structure Learning and Effective Vaccination for Epidemic and Outbreak Control
Sepehr Elahi, Paula Mürmann, Patrick Thiran
Learnware Specification via Dual Alignment
Wei Chen, Jun-Xiang Mao, Xiaozheng Wang et al.
Lego Sketch: A Scalable Memory-augmented Neural Network for Sketching Data Streams
Yuan Feng, Yukun Cao, Hairu Wang et al.
LEMoN: Label Error Detection using Multimodal Neighbors
Haoran Zhang, Aparna Balagopalan, Nassim Oufattole et al.
LensLLM: Unveiling Fine-Tuning Dynamics for LLM Selection
Xinyue Zeng, Haohui Wang, Junhong Lin et al.
Less is More: Federated Graph Learning with Alleviating Topology Heterogeneity from A Causal Perspective
Lele Fu, Bowen Deng, Sheng Huang et al.
Let LLM Tell What to Prune and How Much to Prune
Mingzhe Yang, Sihao Lin, Changlin Li et al.
LETS Forecast: Learning Embedology for Time Series Forecasting
Abrar Majeedi, Viswanatha Reddy Gajjala, Satya Sai Srinath Namburi GNVV et al.
Leveraging Diffusion Model as Pseudo-Anomalous Graph Generator for Graph-Level Anomaly Detection
Jinyu Cai, Yunhe Zhang, Fusheng Liu et al.
Leveraging Model Guidance to Extract Training Data from Personalized Diffusion Models
Xiaoyu Wu, Jiaru Zhang, Steven Wu
Leveraging Offline Data in Linear Latent Contextual Bandits
Chinmaya Kausik, Kevin Tan, Ambuj Tewari
Leveraging Online Olympiad-Level Math Problems for LLMs Training and Contamination-Resistant Evaluation
Sadegh Mahdavi, Muchen Li, Kaiwen Liu et al.
Leveraging Per-Instance Privacy for Machine Unlearning
Naz Sepahvand, Anvith Thudi, Berivan Isik et al.
Leveraging Predictive Equivalence in Decision Trees
Hayden McTavish, Zachery Boner, Jon Donnelly et al.
Leveraging Randomness in Model and Data Partitioning for Privacy Amplification
Andy Dong, Wei-Ning Chen, Ayfer Ozgur
Leveraging Skills from Unlabeled Prior Data for Efficient Online Exploration
Max Wilcoxson, Qiyang Li, Kevin Frans et al.
Leveraging Sparsity for Sample-Efficient Preference Learning: A Theoretical Perspective
Yunzhen Yao, Lie He, Michael Gastpar
LEVIS: Large Exact Verifiable Input Spaces for Neural Networks
Mohamad Chehade, Wenting Li, Brian Bell et al.
Lexico: Extreme KV Cache Compression via Sparse Coding over Universal Dictionaries
Junhyuck Kim, Jongho Park, Jaewoong Cho et al.
LGDM: Latent Guidance in Diffusion Models for Perceptual Evaluations
Shreshth Saini, Ru-Ling Liao, Yan Ye et al.
LieRE: Lie Rotational Positional Encodings
Sophie Ostmeier, Brian Axelrod, Maya Varma et al.
LIFT the Veil for the Truth: Principal Weights Emerge after Rank Reduction for Reasoning-Focused Supervised Fine-Tuning
Zihang Liu, Tianyu Pang, Oleg Balabanov et al.
Liger: Linearizing Large Language Models to Gated Recurrent Structures
Disen Lan, Weigao Sun, Jiaxi Hu et al.