Papers

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machine learning Oct 09 One Block, Multiple Depths: Recurrent Vision Transformers with Depth-Programmed Experts by Adrian Bulat, Yassine Ouali, Georgios Tzimiropoulos machine learning Oct 09 Caught in the Act: Probes Effectively Detect Sabotage and Catch Unverbalized Deception by Oskar J. Hollinsworth, Alex F. Spies, Tigist Diriba, Adam Gleave, Chris Cundy machine learning Oct 09 Rounding in Preconditioner Space: Redesigning 4-bit AdamW Optimizer-State Quantization by Hanyang Li, Shao Tang, Daniel Thomas Braithwaite, Gregory Dexter, Leonardo Neves, Aman Gupta, Hiroto Udagawa, Abhishek Shivanna, Daniel Silva, Rohan Ramanath machine learning Oct 09 A Unified Bellman Operator for Safety-Critical Reinforcement Learning by Nishanth Arun Rao, Royina Karegoudra Jayanth, Benjamin Eysenbach, Jaime Fernández Fisac machine learning Oct 09 Learning Kilometer-Scale Weather Prediction with Global-Regional Alignment by Guowen Li, Yang Liu, Yujie Wang, Qiuyan Sun, Haoyuan Liang, Juepeng Zheng, Hong Cheng, Haohuan Fu machine learning Oct 09 Prospective Prediction of OOD Degradation from Source-Side Training Dynamics by Sasha (Alexander) Monin machine learning Oct 09 Marformer: A Transformer for Predicting Missing Data Distributions by Prabhav Singh, Xiheng Tom Wang, Haojun Shi, Jason Eisner machine learning Oct 08 Decoupling Exploration from Optimization in RLVR by Saif Punjwani, Micah Goldblum machine learning Oct 08 Distilling Graph Geometry: Knowledge Gap from GNNs to MLPs by Zhewei Chen, Hao Zhu, Jiaojiao Jiang, Ahad N. Zehmakan machine learning Oct 08 Why Forget-Only Unlearning Needs Memorization by Luka Radić, Vikrant Singhal, Amartya Sanyal