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20222026
most citedGalvatron: Efficient Transformer Training over Multiple GPUs Using Automatic Parallelism

57 citations · 76 across the 11 of their papers we have counts for

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2 papers · 1 filter

cs.LG2026

DARTS: Distribution-Aware Active Rollout Trajectory Shaping for Accelerating LLM Reinforcement Learning

Yujie Wang, Siwei Chen, Longzan Luo +4

Reinforcement Learning (RL) has become pivotal for improving model capabilities yet suffers from rollout efficiency bottlenecks due to the long-tail response length distribution. W…

cs.DC2026

LAER-MoE: Load-Adaptive Expert Re-layout for Efficient Mixture-of-Experts Training

Xinyi Liu, Yujie Wang, Fangcheng Fu +4

Expert parallelism is vital for effectively training Mixture-of-Experts (MoE) models, enabling different devices to host distinct experts, with each device processing different inp…