2 papers
cs.CL2025
Breaking the MoE LLM Trilemma: Dynamic Expert Clustering with Structured Compression
Peijun Zhu, Ning Yang, Baoliang Tian +4
Mixture-of-Experts (MoE) Large Language Models (LLMs) face a trilemma of load imbalance, parameter redundancy, and communication overhead. We introduce a unified framework based on…
cs.LG2025
Proactive Constrained Policy Optimization with Preemptive Penalty
Ning Yang, Pengyu Wang, Guoqing Liu +3
Safe Reinforcement Learning (RL) often faces significant issues such as constraint violations and instability, necessitating the use of constrained policy optimization, which seeks…