Papers
Realistic Unsupervised CLIP Fine-tuning with Universal Entropy Optimization
Jian Liang, Lijun Sheng, Zhengbo Wang et al.
Reason for Future, Act for Now: A Principled Architecture for Autonomous LLM Agents
Zhihan Liu, Hao Hu, Shenao Zhang et al.
Receptive Fields As Experts in Convolutional Neural Architectures
Dongze Lian, Weihao Yu, Xinchao Wang
ReconBoost: Boosting Can Achieve Modality Reconcilement
Cong Hua, Qianqian Xu, Shilong Bao et al.
Recovering Labels from Local Updates in Federated Learning
Huancheng Chen, Haris Vikalo
Recovering the Pre-Fine-Tuning Weights of Generative Models
Eliahu Horwitz, Jonathan Kahana, Yedid Hoshen
Recurrent Distance Filtering for Graph Representation Learning
Yuhui Ding, Antonio Orvieto, Bobby He et al.
Recurrent Early Exits for Federated Learning with Heterogeneous Clients
Royson Lee, Javier Fernandez-Marques, Shell Xu Hu et al.
ReDiffuser: Reliable Decision-Making Using a Diffuser with Confidence Estimation
Nantian He, Shaohui Li, Zhi Li et al.
Re-Dock: Towards Flexible and Realistic Molecular Docking with Diffusion Bridge
Yufei Huang, Odin Zhang, Lirong Wu et al.
Reducing Balancing Error for Causal Inference via Optimal Transport
Yuguang Yan, Hao Zhou, Zeqin Yang et al.
Reducing Fine-Tuning Memory Overhead by Approximate and Memory-Sharing Backpropagation
Yuchen Yang, Yingdong Shi, Cheems Wang et al.
Reducing Item Discrepancy via Differentially Private Robust Embedding Alignment for Privacy-Preserving Cross Domain Recommendation
Weiming Liu, Xiaolin Zheng, Chaochao Chen et al.
Reducing sequential change detection to sequential estimation
Shubhanshu Shekhar, Aaditya Ramdas
Referee Can Play: An Alternative Approach to Conditional Generation via Model Inversion
Xuantong Liu, Tianyang Hu, Wenjia Wang et al.
Reference Neural Operators: Learning the Smooth Dependence of Solutions of PDEs on Geometric Deformations
Ze Cheng, Zhongkai Hao, Xiaoqiang Wang et al.
Refined Coreset Selection: Towards Minimal Coreset Size under Model Performance Constraints
Xiaobo Xia, Jiale Liu, Shaokun Zhang et al.
Refining Minimax Regret for Unsupervised Environment Design
Michael Beukman, Samuel Coward, Michael Matthews et al.
Reflected Flow Matching
Tianyu Xie, Yu Zhu, Longlin Yu et al.
Reflective Policy Optimization
Yaozhong Gan, Renye Yan, Zhe Wu et al.
ReGAL: Refactoring Programs to Discover Generalizable Abstractions
Elias Stengel-Eskin, Archiki Prasad, Mohit Bansal
Regression with Multi-Expert Deferral
Anqi Mao, Mehryar Mohri, Yutao Zhong
Regularized Q-learning through Robust Averaging
Peter Schmitt-Förster, Tobias Sutter
Regularizing with Pseudo-Negatives for Continual Self-Supervised Learning
Sungmin Cha, Kyunghyun Cho, Taesup Moon