Muon-RT reuses teacher trajectory to drop momentum buffers in LLM self-distillation
Read original source →arxiv.orgMuon-RT replaces separate momentum buffers by reusing the teacher-student displacement for hidden weight matrices, cutting memory while improving fine-tuning and policy-optimization accuracy. The method targets self-distillation fine-tuning (SDFT) and self-distillation policy optimization (SDPO), using Newton-Schulz orthogonalization.
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