Author

Jun Luo

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#machine learning Preprint Sep 2026

Redundancy Meets Synergy: Dependency-aware Expert Selection for MoE via Submodular Optimization

While Mixture-of-Experts (MoE) models effectively scale model capacity through sparse activation, their deployment is often bottlenecked by prohibitive memory requirements. Extracting a compact subset of experts presents a promising solution. However, existing expert selection heuristics predominantly rely on Top-k ran...

Zheng Lin, Shao-Ke Fang, Yu-Xin Zhang et al. · 0 citations

#artificial intelligence Preprint Oct 2026

Asynchronous LLM Post-Training: Group-Mass Capping and Convergence Analysis

Asynchronous reinforcement learning (RL) improves the efficiency of large language model post-training but introduces stale rollouts generated by earlier policies. Theoretical understanding of how this staleness affects convergence and how to mitigate its impact remains limited. We derive a convergence bound for GRPO-s...

Qi-Jia He, Rui-Nan Jin, Jun Luo et al. · 0 citations