Author

Zi-Jun Wei

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#artificial intelligence May 2026

Diagnosing Training Inference Mismatch in LLM Reinforcement Learning

It is shown that small token-level numerical disagreements can independently cause training collapse, and that TIM is not benign numerical noise, but a systems-level perturbation that should be treated as a first-order factor in analyzing LLM RL stability.

Tian-Le Zhong, Neiwen Ling, Yifan Pi et al. · arXiv.org · 8 citations · ⚡1

#artificial intelligence Preprint Sep 2026

Where Does Staleness Accumulate? Pool Aware Effective Staleness Control for Asynchronous RL in LLM Post-Training

This work decomposes trajectory staleness into Generation Staleness, accumulated before rollout completion, and Waiting Staleness, accumulated after a completed trajectory enters the pool, and introduces PACE (Pool-Aware Control of Effective Staleness), which improves validation performance in multi-turn tool-integrate...

Chen-Liang Li, Neiwen Ling, Zi-Jun Wei et al. · 0 citations