Author

Shuo He

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#artificial intelligence Feb 2026

Dr. MAS: Stable Reinforcement Learning for Multi-Agent LLM Systems

It is shown that under GRPO-style optimization, a global normalization baseline may deviate from diverse agents'reward distributions, which ultimately leads to gradient-norm instability, which theoretically pinpoints a key reason for training instability when extending group-based RL to multi-agent LLM systems.

Lang Feng, Long-Tao Zheng, Shuo He et al. · arXiv.org · 14 citations · ⚡1

Jul 2026

Progress-conditioned Group Policy Optimization for Long-Horizon Agentic Tasks

Progress-conditioned Group Policy Optimization is proposed, which uses first-visit observation coverage only when all samples in a group receive zero outcome reward, and consistently improves over group-based baselines, with particularly large gains on hard tasks.

Kaibing Yang, Guangfeng Cai, Sheng-Tian Yang et al. · arXiv.org · 1 citation