Entong Li — accepted AI-conference papers

2025

Body-Temperature-Responsive Balloon Actuator for Adaptive In-Ear Microneedle Electrode Deployment

Ruizhou Zhao, Wenchao Yue, Entong Li, Chengxi Bai, Hongliang Ren

IROS 2025

Conventional in-ear electrodes face challenges such as inconsistent skin contact, motion artifacts, and discomfort, limiting their reliability in dynamic conditions. To overcome these limitations, this study presents a body-temperature responsive in-ear balloon actuator (BBA) based on liquid-to-vapo

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2024

LocMoE: A Low-overhead MoE for Large Language Model Training

Jing Li, Zhijie Sun, Xuan He, Li Zeng, Yi Lin, Entong Li +3

IJCAI 2024poster

The Mixtures-of-Experts (MoE) model is a widespread distributed and integrated learning method for large language models (LLM), which is favored due to its ability to sparsify and expand models efficiently. However, the performance of MoE is limited by load imbalance and high latency of All-to-All c…

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