Single-Expansion Async Optimization Boosts Agent RL
zai-org · hf · 2026-07-09
This paper proposes a single-expansion asynchronous optimization method for agent reinforcement learning. It addresses stability issues of LLMs during complex task training and outperforms existing methods on coding and reasoning benchmarks.
Related event: GLM Team Proposes SAO Algorithm for Asynchronous Agent RL(15 posts)→
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