Papers
Rethinking Imbalance in Image Super-Resolution for Efficient Inference
Wei Yu, Bowen Yang, Qinglin Liu et al.
Rethinking Inverse Reinforcement Learning: from Data Alignment to Task Alignment
Weichao Zhou, Wenchao Li
Rethinking LLM Memorization through the Lens of Adversarial Compression
Avi Schwarzschild, Zhili Feng, Pratyush Maini et al.
Rethinking Memory and Communication Costs for Efficient Data Parallel Training of Large Language Models
Hanxiao Zhang, Lin Ju, Chan Wu et al.
Rethinking Misalignment in Vision-Language Model Adaptation from a Causal Perspective
Yanan Zhang, Jiangmeng Li, Lixiang Liu et al.
Rethinking No-reference Image Exposure Assessment from Holism to Pixel: Models, Datasets and Benchmarks
Shuai He, Shuntian Zheng, Anlong Ming et al.
Rethinking Optimal Transport in Offline Reinforcement Learning
Arip Asadulaev, Rostislav Korst, Alexander Korotin et al.
Rethinking Out-of-Distribution Detection on Imbalanced Data Distribution
Kai Liu, Zhihang Fu, Sheng Jin et al.
Rethinking Parity Check Enhanced Symmetry-Preserving Ansatz
Ge Yan, Mengfei Ran, Ruocheng Wang et al.
Rethinking Reconstruction-based Graph-Level Anomaly Detection: Limitations and a Simple Remedy
Sunwoo Kim, Soo Yong Lee, Fanchen Bu et al.
Rethinking Score Distillation as a Bridge Between Image Distributions
David McAllister, Songwei Ge, Jia-Bin Huang et al.
Rethinking the Capacity of Graph Neural Networks for Branching Strategy
Ziang Chen, Jialin Liu, Xiaohan Chen et al.
Rethinking the Diffusion Models for Missing Data Imputation: A Gradient Flow Perspective
Zhichao Chen, Haoxuan Li, Fangyikang Wang et al.
Rethinking the Evaluation of Out-of-Distribution Detection: A Sorites Paradox
Xingming Long, Jie Zhang, Shiguang Shan et al.
Rethinking the Membrane Dynamics and Optimization Objectives of Spiking Neural Networks
Hangchi Shen, Qian Zheng, Huamin Wang et al.
Rethinking the Power of Timestamps for Robust Time Series Forecasting: A Global-Local Fusion Perspective
Chengsen Wang, Qi Qi, Jingyu Wang et al.
Rethinking The Training And Evaluation of Rich-Context Layout-to-Image Generation
Jiaxin Cheng, Zixu Zhao, Tong He et al.
Rethinking Transformer for Long Contextual Histopathology Whole Slide Image Analysis
Honglin Li, Yunlong Zhang, Pingyi Chen et al.
Rethinking Weight Decay for Robust Fine-Tuning of Foundation Models
Junjiao Tian, Chengyue Huang, Zsolt Kira
Retrieval-Augmented Diffusion Models for Time Series Forecasting
Jingwei Liu, Ling Yang, Hongyan Li et al.
Retrieval & Fine-Tuning for In-Context Tabular Models
Valentin Thomas, Junwei Ma, Rasa Hosseinzadeh et al.
Retrieval-Retro: Retrieval-based Inorganic Retrosynthesis with Expert Knowledge
Heewoong Noh, Namkyeong Lee, Gyoung S. Na et al.
RETR: Multi-View Radar Detection Transformer for Indoor Perception
Ryoma Yataka, Adriano Cardace, Pu (Perry) Wang et al.
Retrospective for the Dynamic Sensorium Competition for predicting large-scale mouse primary visual cortex activity from videos
Polina Turishcheva, Paul G. Fahey, Michaela Vystrčilová et al.