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cs.LG2026
When Muon Optimizer Meets Adversarial Training: A Theoretical and Empirical Study
Jun Yan, Weiquan Huang, Jiankai Zuo +4
Adversarial training (AT) remains one of the most reliable empirical defenses against adversarial attacks. Its robustness critically depends on how the underlying min-max objective…
cs.LG2026
Absorber LLM: Harnessing Causal Synchronization for Test-Time Training
Zhixin Zhang, Shabo Zhang, Chengcan Wu +2
Transformers suffer from a high computational cost that grows with sequence length for self-attention, making inference in long streams prohibited by memory consumption. Constant-m…