Overcoming Scaling Limits in On-Policy Self-Distillation for LLM Reasoning
cs.LG, cs.CL
Submitted: 2026-09-29
Updated: 2026-09-29
Terminology
Sources
- Distilling the Knowledge in a Neural Network
- DASH: Divergence-Adaptive Supervision Horizons for On-Policy Self-Distillation of Reasoning Models
- Privileged Solutions or Context-Induced Teacher Behavior? Dissecting On-Policy Self-Distillation
- Respecting Self-Uncertainty in On-Policy Self-Distillation for Efficient LLM Reasoning
- AVSD: Adaptive-View Self-Distillation by Balancing Consensus and Teacher-Specific Privileged Signals
- FitNets: Hints for Thin Deep Nets
- CRISP: Compressed Reasoning via Iterative Self-Policy Distillation
- Proximal Policy Optimization Algorithms
- DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
- Purified OPSD: On-Policy Self-Distillation Without Losing How to Think
- Solving math word problems with process- and outcome-based feedback
- Qwen3 Technical Report
- Scaling Relationship on Learning Mathematical Reasoning with Large Language Models
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