Author

Zi-Zhao Mo

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Preprint Sep 2026

Poseidon: DAG-Guided Parallelism Search for LLM Pre-Training on Heterogeneous Clusters

Poseidon is an efficient and scalable LLM training framework designed with heterogeneity awareness, which employs two efficient, theoretically grounded strategies: stage-level pruning via early stopping with partial estimation, and layer-to-stage mapping exploiting a ridge-like distribution pattern.

Xiao-Song Chen, Shao Nie, Zhong-Min Zhao et al. · 0 citations

Preprint Aug 2026

psRL: Efficient Training for Agentic AI via Training-Time Prefix Sharing

This paper proposes psRL (prefix sharing for RL), a new training system for agentic AI designed to exploit prefix redundancy among training samples, and introduces two novel prefix-sharing mechanisms that enable flexible, fine-grained workload distribution across GPU workers.

Mian-Jie Yu, Zi-Zhao Mo, Huanyu Qu et al. · 0 citations