Papers
ResoNet: Noise-Trained Physics-Informed MRI Off-Resonance Correction
Alfredo De Goyeneche Macaya, Shreya Ramachandran, Ke Wang et al.
Response Length Perception and Sequence Scheduling: An LLM-Empowered LLM Inference Pipeline
Zangwei Zheng, Xiaozhe Ren, Fuzhao Xue et al.
Responsible AI (RAI) Games and Ensembles
Yash Gupta, Runtian Zhai, Arun Suggala et al.
ResShift: Efficient Diffusion Model for Image Super-resolution by Residual Shifting
Zongsheng Yue, Jianyi Wang, Chen Change Loy
Restart Sampling for Improving Generative Processes
Yilun Xu, Mingyang Deng, Xiang Cheng et al.
Restless Bandits with Average Reward: Breaking the Uniform Global Attractor Assumption
Yige Hong, Qiaomin Xie, Yudong Chen et al.
Res-Tuning: A Flexible and Efficient Tuning Paradigm via Unbinding Tuner from Backbone
Zeyinzi Jiang, Chaojie Mao, Ziyuan Huang et al.
ReSync: Riemannian Subgradient-based Robust Rotation Synchronization
Huikang Liu, Xiao Li, Anthony Man-Cho So
Retaining Beneficial Information from Detrimental Data for Neural Network Repair
Long-Kai Huang, Peilin Zhao, Junzhou Huang et al.
Re-Think and Re-Design Graph Neural Networks in Spaces of Continuous Graph Diffusion Functionals
Tingting Dan, Jiaqi Ding, Ziquan Wei et al.
Rethinking Bias Mitigation: Fairer Architectures Make for Fairer Face Recognition
Samuel Dooley, Rhea Sukthanker, John Dickerson et al.
Rethinking Conditional Diffusion Sampling with Progressive Guidance
Anh-Dung Dinh, Daochang Liu, Chang Xu
Rethinking Gauss-Newton for learning over-parameterized models
Michael Arbel, Romain Menegaux, Pierre Wolinski
Rethinking Incentives in Recommender Systems: Are Monotone Rewards Always Beneficial?
Fan Yao, Chuanhao Li, Karthik Abinav Sankararaman et al.
Rethinking Semi-Supervised Imbalanced Node Classification from Bias-Variance Decomposition
Divin Yan, Gengchen Wei, Chen Yang et al.
Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective
Chenyu You, Weicheng Dai, Yifei Min et al.
Rethinking the Backward Propagation for Adversarial Transferability
Wang Xiaosen, Kangheng Tong, Kun He
Rethinking the Role of Token Retrieval in Multi-Vector Retrieval
Jinhyuk Lee, Zhuyun Dai, Sai Meher Karthik Duddu et al.
Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules
ZHIYUAN LIU, Yaorui Shi, An Zhang et al.
Retrieval-Augmented Multiple Instance Learning
Yufei CUI, Ziquan Liu, Yixin Chen et al.
ReTR: Modeling Rendering Via Transformer for Generalizable Neural Surface Reconstruction
Yixun Liang, Hao He, Yingcong Chen
RETVec: Resilient and Efficient Text Vectorizer
Elie Bursztein, Marina Zhang, Owen Vallis et al.
Reusable Slotwise Mechanisms
Trang Nguyen, Amin Mansouri, Kanika Madan et al.
Reusing Pretrained Models by Multi-linear Operators for Efficient Training
Yu Pan, Ye Yuan, Yichun Yin et al.
RevColV2: Exploring Disentangled Representations in Masked Image Modeling
Qi Han, Yuxuan Cai, Xiangyu Zhang