MOPD: Multi-Teacher On-Policy Distillation for Capability Integration in LLM Post-Training
Multi-teacher On-Policy Distillation (MOPD) enables efficient integration of multiple domain capabilities in large language models through specialized reinforcement learning teache…
Hugging Face · Daily Papers
·Wenhan Ma, Jianyu Wei
·
·▲ 4 upvotes
Este artigo está em destaque na seleção diária de papers do Hugging Face, curada pela comunidade de pesquisa em IA.
Autores: Wenhan Ma, Jianyu Wei, Liang Zhao, Hailin Zhang, Bangjun Xiao, Lei Li
- 4 upvotes da comunidade
- Temas: reinforcement learning, post-training, domain RL teachers, on-policy distillation, exposure bias, dense optimization signal
Resumo
Resumo original (em inglês), extraído do paper:
Multi-teacher On-Policy Distillation (MOPD) enables efficient integration of multiple domain capabilities in large language models through specialized reinforcement learning teachers and on-policy distillation, achieving superior performance over existing methods.Onde ler
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