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News/Patterns behind Chaos: Forecasting Data Movement for Efficient Large-Scale MoE LLM Inference
arxiv
PublishedMay 13, 2026 at 4:00 AM

Patterns behind Chaos: Forecasting Data Movement for Efficient Large-Scale MoE LLM Inference

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arXiv:2510.05497v5 Announce Type: replace-cross Abstract: Large-scale Mixture of Experts (MoE) Large Language Models (LLMs) have recently become the frontier open-weight models, achieving remarkable model capability similar to proprietary ones. But their random expert selection mechanism introduces

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