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cs.LG2026
Unveiling Implicit Advantage Symmetry: Why GRPO Struggles with Exploration and Difficulty Adaptation
Zhiqi Yu, Zhangquan Chen, Mengting Liu +2
Reinforcement Learning with Verifiable Rewards (RLVR), particularly GRPO, has become the standard for eliciting LLM reasoning. However, its efficiency in exploration and difficulty…
cs.LG2025
Exploring Federated Pruning for Large Language Models
Pengxin Guo, Yinong Wang, Wei Li +4
LLM pruning has emerged as a promising technology for compressing LLMs, enabling their deployment on resource-limited devices. However, current methodologies typically require acce…