3 papers
cs.LG2026
SDFLoRA: Selective Decoupled Federated LoRA for Privacy-preserving Fine-tuning with Heterogeneous Clients
Zhikang Shen, Jianrong Lu, Haiyuan Wan +1
Federated learning (FL) for large language models (LLMs) has attracted increasing attention as a privacy-preserving approach for adapting models over distributed data, where parame…
cs.LG2026
MLB: A Scenario-Driven Benchmark for Evaluating Large Language Models in Clinical Applications
Qing He, Dongsheng Bi, Jianrong Lu +20
The proliferation of Large Language Models (LLMs) presents transformative potential for healthcare, yet practical deployment is hindered by the absence of frameworks that assess re…
q-bio.GN2025
Toward a Team of AI-made Scientists for Scientific Discovery from Gene Expression Data
Haoyang Liu, Yijiang Li, Jinglin Jian +7
Machine learning has emerged as a powerful tool for scientific discovery, enabling researchers to extract meaningful insights from complex datasets. For instance, it has facilitate…