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Limin Xiao

2 accepted papers

2026

ReMoE: Boosting Expert Reuse through Router Fine-Tuning in Memory-Constrained MoE LLM Inference

ICML 2026poster

Fine-grained Mixture-of-Experts (MoE) models sparsely activate a subset of parameters, significantly reducing computational costs while maintaining performance. However, in memory-constrained inference scenarios, only a small set of experts can be cached. Experts not in the cache must be fetched fro…

Cited by 0SourceScholar
2018

How to Mobilize Mmwave: A Joint Beam and Channel Tracking Approach

ICASSP 2018accepted

Maintaining reliable millimeter wave (mmWave) connections to many fast-moving mobiles is a key challenge in the theory and practice of 5G systems. In this paper, we develop a new algorithm that can jointly track the beam direction and channel coefficient of mm Wave propagation paths using phased ant…

Cited by 0SourceScholar