Papers

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machine learning Oct 02 Decoding Looped Transformers Better for (Almost) Free by Weihao Liu, Huangjie Zheng, Tianrong Chen, Rohit Dilip, Richard He Bai, Yizhu Jiao, Yuyang Wang, Ruixiang Zhang machine learning Oct 02 SoftServe: A Scalable Quasi-Newton Method for Deep Learning by Joohwan Ko, Tetiana Parshakova, Diana Cai, Robert M. Gower machine learning Oct 02 From Gradients to Capabilities: Understanding Multi-Teacher On-Policy Distillation by Siqi Zhu, Suozhi Huang, Kaixuan Zhang, Yuheng Yang, Zhanyang Jin, Yihang Sun, Jiaxuan You machine learning Oct 02 Effective Resistance and Graph Neural Network Reliability in Tissue-Specific Interactomes by Jianru Shen machine learning Oct 02 Every Ablation Is a Dose: Counterweights and the Semblance of Self-Repair by Areeb Ahmad, Pratinav Seth, Vinay Kumar Sankarapu machine learning Oct 02 When Do Intrinsic Rewards Lead to Exploration? by Scott W. Viteri (Stanford University), Laura Gomezjurado Gonzalez (Stanford University), Clark Barrett (Stanford University) machine learning Oct 02 Muon meets Tamed Langevin: Momentum Preconditioning beyond Convex and gradient-Lipschitz Potentials by Nikolaos Makras, Sotirios Sabanis machine learning Oct 02 Faynt: Scaling and Optimizing Policies for Competitive Melee by Ali Janati, Nikita Kuzmin, Rohit Swamy, Charles Niu programming languages Oct 02 MIRTO: a registration-gated, multiverse-tested evaluation protocol for unsupervised anomaly segmentation in brain MRI by Negin Kafee Hernashki, Soumick Chatterjee machine learning Oct 02 Local Support Learning by Assaf Ben-Kish, Akarsh Kumar, James Glass, Raja Giryes