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Open-MOPD: Diagnosing and Fixing Capability Imbalance in Multi-Teacher On-Policy Distillation
arXiv cs.AI · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- Open-MOPD improves multi-teacher distillation by fixing token-level budget misallocation, raising capability recovery from 35.6% to 83.4% on SmolLM3.
- 为何重要
- Matters for engineers combining multiple specialized RL models into one generalist student model with dense reward supervision.
- 注意
- Evaluation limited to SmolLM3-3B with oracle routing; real-world performance with imperfect routing decisions remains undemonstrated.
收听本摘要
- llm
- distill
- token
- benchmark
- reinforcement learning
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