Discretizing Reward Models
Reward models in reinforcement learning suffer from oversensitivity issues where they assign different scores to equally good responses, leading to poor policy learning, but this c…
Hugging Face · Daily Papers
·Vijay Viswanathan, Shiqi Wang
·
·▲ 7 upvotes
Este artigo está em destaque na seleção diária de papers do Hugging Face, curada pela comunidade de pesquisa em IA.
Autores: Vijay Viswanathan, Shiqi Wang, Devamanyu Hazarika, Chirag Nagpal, Tongshuang Wu, Graham Neubig
- 7 upvotes da comunidade
- Temas: reward models, reinforcement learning, oversensitivity, discriminative ability, specificity, Monte Carlo dropout
Resumo
Resumo original (em inglês), extraído do paper:
Reward models in reinforcement learning suffer from oversensitivity issues where they assign different scores to equally good responses, leading to poor policy learning, but this can be mitigated through discretization techniques that maintain discriminative ability while reducing oversensitivity.Onde ler
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