Papers
Rethinking Score Distilling Sampling for 3D Editing and Generation
Xingyu Miao, Haoran Duan, Yang Long et al.
Rethinking the Bias of Foundation Model under Long-tailed Distribution
Jiahao Chen, Bin Qin, Jiangmeng Li et al.
Rethinking the Stability-Plasticity Trade-off in Continual Learning from an Architectural Perspective
Aojun Lu, Hangjie Yuan, Tao Feng et al.
Rethinking the Temperature for Federated Heterogeneous Distillation
Fan Qi, Daxu Shi, Chuokun Xu et al.
Rethinking Time Encoding via Learnable Transformation Functions
Xi Chen, Yateng Tang, Jiarong Xu et al.
Rethink the Role of Deep Learning towards Large-scale Quantum Systems
Yusheng Zhao, Chi Zhang, Yuxuan Du
Retraining-free Merging of Sparse MoE via Hierarchical Clustering
I-Chun Chen, Hsu-Shen Liu, Wei-Fang Sun et al.
Retraining with Predicted Hard Labels Provably Increases Model Accuracy
Rudrajit Das, Inderjit S Dhillon, Alessandro Epasto et al.
Retrieval-Augmented Language Model for Knowledge-aware Protein Encoding
Jiasheng Zhang, Delvin Ce Zhang, Shuang Liang et al.
Retrieval-Augmented Perception: High-resolution Image Perception Meets Visual RAG
Wenbin Wang, Yongcheng Jing, Liang Ding et al.
Retrieval Augmented Time Series Forecasting
Sungwon Han, Seungeon Lee, Meeyoung Cha et al.
Retrieval Augmented Zero-Shot Enzyme Generation for Specified Substrate
Jiahe Du, Kaixiong Zhou, Xinyu Hong et al.
Return Capping: Sample Efficient CVaR Policy Gradient Optimisation
Harry Mead, Clarissa Costen, Bruno Lacerda et al.
Return of the Latent Space COWBOYS: Re-thinking the use of VAEs for Bayesian Optimisation of Structured Spaces
Henry Moss, Sebastian W. Ober, Tom Diethe
Revealing Weaknesses in Text Watermarking Through Self-Information Rewrite Attacks
Yixin Cheng, Hongcheng Guo, Yangming Li et al.
ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks
Yufei Guo, Yuhan Zhang, Zhou Jie et al.
ReVISE: Learning to Refine at Test-Time via Intrinsic Self-Verification
Hyunseok Lee, Seunghyuk Oh, Jaehyung Kim et al.
Revisiting Chain-of-Thought in Code Generation: Do Language Models Need to Learn Reasoning before Coding?
Ren-Biao Liu, Anqi Li, Chaoding Yang et al.
Revisiting Continuity of Image Tokens for Cross-domain Few-shot Learning
Shuai Yi, Yixiong Zou, Yuhua Li et al.
Revisiting Convergence: Shuffling Complexity Beyond Lipschitz Smoothness
Qi He, Peiran Yu, Ziyi Chen et al.
Revisiting Cooperative Off-Policy Multi-Agent Reinforcement Learning
Yueheng Li, Guangming Xie, Zongqing Lu
Revisiting Differentially Private Algorithms for Decentralized Online Learning
Xiaoyu Wang, Wenhao Yang, Chang Yao et al.
Revisiting Diffusion Models: From Generative Pre-training to One-Step Generation
Bowen Zheng, Tianming Yang
Revisiting Instance-Optimal Cluster Recovery in the Labeled Stochastic Block Model
Kaito Ariu, Alexandre Proutiere, Se-Young Yun