Papers
STAR: Learning Diverse Robot Skill Abstractions through Rotation-Augmented Vector Quantization
Hao Li, Qi Lv, Rui Shao et al.
Statistical and Computational Guarantees of Kernel Max-Sliced Wasserstein Distances
Jie Wang, March Boedihardjo, Yao Xie
Statistical Collusion by Collectives on Learning Platforms
Etienne Gauthier, Francis Bach, Michael I. Jordan
Statistical Hypothesis Testing for Auditing Robustness in Language Models
Paulius Rauba, Qiyao Wei, Mihaela Van Der Schaar
Statistical Query Hardness of Multiclass Linear Classification with Random Classification Noise
Ilias Diakonikolas, Mingchen Ma, Lisheng Ren et al.
Statistical Test for Feature Selection Pipelines by Selective Inference
Tomohiro Shiraishi, Tatsuya Matsukawa, Shuichi Nishino et al.
Stay Hungry, Keep Learning: Sustainable Plasticity for Deep Reinforcement Learning
Huaicheng Zhou, Zifeng Zhuang, Donglin Wang
Stay-Positive: A Case for Ignoring Real Image Features in Fake Image Detection
Anirudh Sundara Rajan, Yong Jae Lee
STD-FD: Spatio-Temporal Distribution Fitting Deviation for AIGC Forgery Identification
Hengrui Lou, Zunlei Feng, Jinsong Geng et al.
Stealing That Free Lunch: Exposing the Limits of Dyna-Style Reinforcement Learning
Brett Barkley, David Fridovich-Keil
Stealix: Model Stealing via Prompt Evolution
Zhixiong Zhuang, Hui-Po Wang, Maria-Irina Nicolae et al.
StealthInk: A Multi-bit and Stealthy Watermark for Large Language Models
Ya Jiang, Chuxiong Wu, Massieh Kordi Boroujeny et al.
Steerable Transformers for Volumetric Data
Soumyabrata Kundu, Risi Kondor
Steering Protein Language Models
Long-Kai Huang, Rongyi Zhu, Bing He et al.
Steer LLM Latents for Hallucination Detection
Seongheon Park, Xuefeng Du, Min-Hsuan Yeh et al.
Step-DAD: Semi-Amortized Policy-Based Bayesian Experimental Design
Marcel Hedman, Desi R. Ivanova, Cong Guan et al.
Stochastic Control for Fine-tuning Diffusion Models: Optimality, Regularity, and Convergence
Yinbin Han, Meisam Razaviyayn, Renyuan Xu
Stochastic Deep Restoration Priors for Imaging Inverse Problems
Yuyang Hu, Albert Peng, Weijie Gan et al.
Stochastic Encodings for Active Feature Acquisition
Alexander Luke Ian Norcliffe, Changhee Lee, Fergus Imrie et al.
Stochastic Forward–Backward Deconvolution: Training Diffusion Models with Finite Noisy Datasets
Haoye Lu, Qifan Wu, Yaoliang Yu
Stochastic Layer-Wise Shuffle for Improving Vision Mamba Training
Zizheng Huang, Haoxing Chen, Jiaqi Li et al.
Stochastic Online Conformal Prediction with Semi-Bandit Feedback
Haosen Ge, Hamsa Bastani, Osbert Bastani
Stochastic Poisson Surface Reconstruction with One Solve using Geometric Gaussian Processes
Sidhanth Holalkere, David Bindel, Silvia Sellán et al.
Stochastic Smoothed Primal-Dual Algorithms for Nonconvex Optimization with Linear Inequality Constraints
Ruichuan Huang, Jiawei Zhang, Ahmet Alacaoglu
SToFM: a Multi-scale Foundation Model for Spatial Transcriptomics
Suyuan Zhao, Yizhen Luo, Ganbo Yang et al.