2 papers
cs.LG2026
Conflict-Aware Federated Fine-Tuning of Large Language Models with Mixture-of-Experts
Yijun Lu, Zihan Fang, Pengpeng Qiao +6
The continuous scaling of large language models (LLMs) incurs prohibitive computational costs, making Mixture-of-Experts (MoE) a scalable alternative for efficient fine-tuning via…
cs.CL2025
EMPOWER: Evolutionary Medical Prompt Optimization With Reinforcement Learning
Yinda Chen, Yangfan He, Jing Yang +5
Prompt engineering significantly influences the reliability and clinical utility of Large Language Models (LLMs) in medical applications. Current optimization approaches inadequate…