collaborators

8 papers

cs.AI2026

S-SPPO: Semantic-Calibrated Self-Play Preference Optimization

Xiwen Chen, Wenhui Zhu, Jingjing Wang +13

Aligning Large Language Models (LLMs) with human preferences is often formulated via Direct Preference Optimization (DPO). However, the standard Bradley-Terry instantiation of DPO…

cs.AI2026

Context Pruning for Coding Agents via Multi-Rubric Latent Reasoning

Jingjing Wang, Xiwen Chen, Wenhui Zhu +6

LLM-powered coding agents spend the majority of their token budget reading repository files, yet much of the retrieved code is irrelevant to the task at hand. Existing learned prun…

cs.LG2026

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…

eess.SP2026

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…

cs.LG2026

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…

eess.SP2025

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…

cs.LG2025

Multimodal Cardiovascular Risk Profiling Using Self-Supervised Learning of Polysomnography

Zhengxiao He, Huayu Li, Geng Yuan +4

Methods: We developed a self-supervised deep learning model that extracts meaningful patterns from multi-modal signals (Electroencephalography (EEG), Electrocardiography (ECG), and…

cs.AI2025

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…