Teacher-Evolution Self-Distillation Improves Model Training Stability
October 27, 2026
Teacher-Evolution Self-Distillation (TESD) addresses unreliable guidance in on-policy self-distillation. It enables the self-teacher to generate rollouts and receive environmental feedback to provide more stable training objectives.
HOW THIS AFFECTS YOU
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researcherThis method helps overcome performance plateaus in sequence-level post-training paradigms.