Author

Liang-Qiong Qu

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#artificial intelligence Preprint Oct 2026

Fed-GRPO: Reward-Signal-Driven Federated Group Relative Policy Optimization

Large Language Models (LLMs) have shown strong reasoning capabilities when fine-tuned with reinforcement learning (RL), particularly through Group Relative Policy Optimization (GRPO). However, existing GRPO methods assume centralized access to training data, which may not hold in practice due to privacy or regulatory c...

Peng-Xin Guo, Shuang Zeng, Zong-Gen Li et al. · 0 citations

#artificial intelligence Feb 2026

Unveiling Implicit Advantage Symmetry: Why GRPO Struggles with Exploration and Difficulty Adaptation

This work identifies an implicit advantage symmetry inherent in Group Relative Advantage Estimation (GRAE) as a structural property that provides a new perspective for understanding bottlenecks in reinforcement learning, and proposes Asymmetric GRAE (A-GRAE), which dynamically modulates exploration incentives and sampl...

Zhiqiu Yu, Zhangquan Chen, Meng-Ting Liu et al. · arXiv.org · 6 citations