Papers
Revealing the unseen: Benchmarking video action recognition under occlusion
Shresth Grover, Vibhav Vineet, Yogesh Rawat
Reverse Engineering Self-Supervised Learning
Ido Ben-Shaul, Ravid Shwartz-Ziv, Tomer Galanti et al.
Reversible and irreversible bracket-based dynamics for deep graph neural networks
Anthony Gruber, Kookjin Lee, Nathaniel Trask
Revisiting Adversarial Robustness Distillation from the Perspective of Robust Fairness
Xinli Yue, Mou Ningping, Qian Wang et al.
Revisiting Adversarial Training for ImageNet: Architectures, Training and Generalization across Threat Models
Naman Deep Singh, Francesco Croce, Matthias Hein
Revisiting Area Convexity: Faster Box-Simplex Games and Spectrahedral Generalizations
Arun Jambulapati, Kevin Tian
Revisiting Evaluation Metrics for Semantic Segmentation: Optimization and Evaluation of Fine-grained Intersection over Union
Zifu Wang, Maxim Berman, Amal Rannen-Triki et al.
Revisiting Implicit Differentiation for Learning Problems in Optimal Control
Ming Xu, Timothy L. Molloy, Stephen Gould
Revisiting Logistic-softmax Likelihood in Bayesian Meta-Learning for Few-Shot Classification
Tianjun Ke, Haoqun Cao, Zenan Ling et al.
Revisiting Out-of-distribution Robustness in NLP: Benchmarks, Analysis, and LLMs Evaluations
Lifan Yuan, Yangyi Chen, Ganqu Cui et al.
Revisiting Scalarization in Multi-Task Learning: A Theoretical Perspective
Yuzheng Hu, Ruicheng Xian, Qilong Wu et al.
Revisiting the Evaluation of Image Synthesis with GANs
mengping yang, Ceyuan Yang, Yichi Zhang et al.
Revisiting the Minimalist Approach to Offline Reinforcement Learning
Denis Tarasov, Vladislav Kurenkov, Alexander Nikulin et al.
Revisiting Visual Model Robustness: A Frequency Long-Tailed Distribution View
Zhiyu Lin, Yifei Gao, Yunfan Yang et al.
Revisit the Power of Vanilla Knowledge Distillation: from Small Scale to Large Scale
Zhiwei Hao, Jianyuan Guo, Kai Han et al.
Revisit Weakly-Supervised Audio-Visual Video Parsing from the Language Perspective
Yingying Fan, Yu Wu, Bo Du et al.
Reward-agnostic Fine-tuning: Provable Statistical Benefits of Hybrid Reinforcement Learning
Gen Li, Wenhao Zhan, Jason Lee et al.
Reward-Directed Conditional Diffusion: Provable Distribution Estimation and Reward Improvement
Hui Yuan, Kaixuan Huang, Chengzhuo Ni et al.
Rewarded soups: towards Pareto-optimal alignment by interpolating weights fine-tuned on diverse rewards
Alexandre Rame, Guillaume Couairon, Corentin Dancette et al.
Reward Finetuning for Faster and More Accurate Unsupervised Object Discovery
Katie Luo, Zhenzhen Liu, Xiangyu Chen et al.
Reward Imputation with Sketching for Contextual Batched Bandits
Xiao Zhang, Ninglu Shao, Zihua Si et al.
Reward Scale Robustness for Proximal Policy Optimization via DreamerV3 Tricks
Ryan Sullivan, Akarsh Kumar, Shengyi Huang et al.
Rewiring Neurons in Non-Stationary Environments
Zhicheng Sun, Yadong Mu
Rewrite Caption Semantics: Bridging Semantic Gaps for Language-Supervised Semantic Segmentation
Yun Xing, Jian Kang, Aoran Xiao et al.
REx: Data-Free Residual Quantization Error Expansion
Edouard YVINEC, Arnaud Dapogny, Matthieu Cord et al.