10 papers
Locally Deployable Small Language Models for Emergency Department Decision Support: A Systematic Benchmark of Fine-Tuning Strategies
Qingfeng Zhang, Yuanxiong Guo, Yanmin Gong
Deploying large language models (LLMs) for decision support in emergency departments (EDs) faces two major challenges: privacy risks of transmitting patient data to closed-source c…
Unifying Acoustic Features and Text with Multimodal LLMs for Neurodegenerative Screening
Qingfeng Zhang, Yuanxiong Guo, Yanmin Gong
Voice-based screening offers a scalable and non-invasive way to assess neurodegenerative diseases such as Alzheimer's disease (AD) and Parkinson's disease (PD), but their staging r…
LLM-Powered Personalized Glycemic Assessment in Type 2 Diabetes with Wearable Sensor Data
Yifan Gao, Yanmin Gong, Yun Shi +1
Type 2 Diabetes (T2D) poses an increasing global health threat, demanding effective glycemic assessment to support personalized and improved diabetes care. Wearable sensors such as…
ReSS: Learning Reasoning Models for Tabular Data Prediction via Symbolic Scaffold
Chenlang Yi, Gang Li, Zizhan Xiong +4
Tabular data remains prevalent in high-stakes domains such as healthcare and finance, where predictive models are expected to provide both high accuracy and faithful, human-underst…
FedKRSO: Communication and Memory Efficient Federated Fine-Tuning of Large Language Models
Guohao Yang, Tongle Wu, Yuanxiong Guo +2
Fine-tuning is essential to adapt general-purpose large language models (LLMs) to domain-specific tasks. As a privacy-preserving framework to leverage decentralized data for collab…
Heterogeneity-Aware Cooperative Federated Edge Learning with Adaptive Computation and Communication Compression
Zhenxiao Zhang, Zhidong Gao, Yuanxiong Guo +1
Motivated by the drawbacks of cloud-based federated learning (FL), cooperative federated edge learning (CFEL) has been proposed to improve efficiency for FL over mobile edge networ…