Efficient Resource-Shiftable RL Post-training with Generative Rewards
Reinforcement learning (RL) post-training with generative reward models (GenRM) has become a central recipe for improving large language models (LLMs), and it is also increasingly resource-intensive: policy rollout, GenRM-based reward evaluation, and policy training all compete for GPU resources. However, existing colo...
Yan-Feng Zhao, Hao-Yang Li, Sheng Lin et al.
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