7 papers
Learning Fingerprints for Medical Time Series with Redundancy-Constrained Information Maximization
Huayu Li, ZhengXiao He, Xiwen Chen +4
Learning meaningful representations from medical time series (MedTS) such as ECG or EEG signals is a critical challenge. These signals are often high-dimensional, variable-length a…
MedMamba: Recasting Mamba for Medical Time Series Classification
ZhengXiao He, Huayu Li, Xiwen Chen +4
Medical time series, such as electrocardiograms (ECG) and electroencephalograms (EEG), exhibit complex temporal dynamics and structured cross-channel dependencies, posing fundament…
Martingale Foresight Sampling: A Principled Approach to Inference-Time LLM Decoding
Huayu Li, ZhengXiao He, Siyuan Tian +2
Standard autoregressive decoding in large language models (LLMs) is inherently short-sighted, often failing to find globally optimal reasoning paths due to its token-by-token gener…
Advancing time series completion via RFAMoE and MDFF
Ci Zhang, Huayu Li, Changdi Yang +6
Recent studies show that using diffusion models for time series signal reconstruction holds great promise. However, such approaches remain largely unexplored in the domain of medic…
NeuroHD-RA: Neural-distilled Hyperdimensional Model with Rhythm Alignment
ZhengXiao He, Jinghao Wen, Huayu Li +2
We present a novel and interpretable framework for electrocardiogram (ECG)-based disease detection that combines hyperdimensional computing (HDC) with learnable neural encoding. Un…
Smarter Together: Combining Large Language Models and Small Models for Physiological Signals Visual Inspection
Huayu Li, Zhengxiao He, Xiwen Chen +8
Large language models (LLMs) have shown promising capabilities in visually interpreting medical time-series data. However, their general-purpose design can limit domain-specific pr…