Papers
11,951 papers found
Repetition Improves Language Model Embeddings
Jacob Mitchell Springer, Suhas Kotha, Daniel Fried et al.
RepoGraph: Enhancing AI Software Engineering with Repository-level Code Graph
Siru Ouyang, Wenhao Yu, Kaixin Ma et al.
Representation Alignment for Generation: Training Diffusion Transformers Is Easier Than You Think
Sihyun Yu, Sangkyung Kwak, Huiwon Jang et al.
Representational Similarity via Interpretable Visual Concepts
Neehar Kondapaneni, Oisin Mac Aodha, Pietro Perona
Representative Guidance: Diffusion Model Sampling with Coherence
Anh-Dung Dinh, Daochang Liu, Chang Xu
Repulsive Latent Score Distillation for Solving Inverse Problems
Nicolas Zilberstein, Morteza Mardani, Santiago Segarra
RESfM: Robust Deep Equivariant Structure from Motion
Fadi Khatib, Yoni Kasten, Dror Moran et al.
ReSi: A Comprehensive Benchmark for Representational Similarity Measures
Max Klabunde, Tassilo Wald, Tobias Schumacher et al.
Residual Connections and Normalization Can Provably Prevent Oversmoothing in GNNs
Michael Scholkemper, Xinyi Wu, Ali Jadbabaie et al.
Residual Deep Gaussian Processes on Manifolds
Kacper Wyrwal, Andreas Krause, Viacheslav Borovitskiy
Residual Kernel Policy Network: Enhancing Stability and Robustness in RKHS-Based Reinforcement Learning
Yixian Zhang, Huaze Tang, Huijing Lin et al.
Residual-MPPI: Online Policy Customization for Continuous Control
Pengcheng Wang, Chenran Li, Catherine Weaver et al.
Residual Stream Analysis with Multi-Layer SAEs
Tim Lawson, Lucy Farnik, Conor Houghton et al.
Resolution Attack: Exploiting Image Compression to Deceive Deep Neural Networks
Wangjia Yu, Xiaomeng Fu, Qiao Li et al.
Restructuring Vector Quantization with the Rotation Trick
Christopher Fifty, Ronald Guenther Junkins, Dennis Duan et al.
Restyling Unsupervised Concept Based Interpretable Networks with Generative Models
Jayneel Parekh, Quentin Bouniot, Pavlo Mozharovskyi et al.
RESuM: A Rare Event Surrogate Model for Physics Detector Design
Ann-Kathrin Schuetz, A.W.P. Poon, Aobo Li
Rethinking and Improving Autoformalization: Towards a Faithful Metric and a Dependency Retrieval-based Approach
Qi Liu, Xinhao Zheng, Xudong Lu et al.
Rethinking Artistic Copyright Infringements In the Era Of Text-to-Image Generative Models
Mazda Moayeri, Sriram Balasubramanian, Samyadeep Basu et al.
Rethinking Audio-Visual Adversarial Vulnerability from Temporal and Modality Perspectives
Zeliang Zhang, Susan Liang, Daiki Shimada et al.
Rethinking Classifier Re-Training in Long-Tailed Recognition: Label Over-Smooth Can Balance
Siyu Sun, Han Lu, Jiangtong Li et al.
Rethinking Diffusion Posterior Sampling: From Conditional Score Estimator to Maximizing a Posterior
Tongda Xu, Xiyan Cai, Xinjie Zhang et al.
Rethinking Evaluation of Sparse Autoencoders through the Representation of Polysemous Words
Gouki Minegishi, Hiroki Furuta, Yusuke Iwasawa et al.
Rethinking Fair Representation Learning for Performance-Sensitive Tasks
Charles Jones, Fabio De Sousa Ribeiro, Mélanie Roschewitz et al.
Rethinking Graph Neural Networks From A Geometric Perspective Of Node Features
Feng Ji, Yanan Zhao, Kai Zhao et al.