AsyncOPD: How Stale Can On-Policy Distillation Be?
Asynchronous on-policy distillation addresses training bottlenecks in large language model post-training by decoupling rollout generation from learner updates, though it introduces…
Hugging Face · Daily Papers
·Wonjun Kang, Kevin Galim
·
·▲ 10 upvotes
Este artigo está em destaque na seleção diária de papers do Hugging Face, curada pela comunidade de pesquisa em IA.
Autores: Wonjun Kang, Kevin Galim, Seunghyuk Oh, Minjun Kang, Sanghyun Park, Donghoon Kim
- 10 upvotes da comunidade
- Temas: on-policy distillation, asynchronous training, stale-policy data, KL divergence, reverse KL, forward KL
Resumo
Resumo original (em inglês), extraído do paper:
Asynchronous on-policy distillation addresses training bottlenecks in large language model post-training by decoupling rollout generation from learner updates, though it introduces challenges with stale policy data that require specialized solutions.Onde ler
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