2 papers
cs.LG2025
Communication-Efficient and Personalized Federated Foundation Model Fine-Tuning via Tri-Matrix Adaptation
Yongle Li, Bo Liu, Sheng Huang +3
In federated learning, fine-tuning pre-trained foundation models poses significant challenges, particularly regarding high communication cost and suboptimal model performance due t…
cs.CL2024
Dual-Phase Accelerated Prompt Optimization
Muchen Yang, Moxin Li, Yongle Li +5
Gradient-free prompt optimization methods have made significant strides in enhancing the performance of closed-source Large Language Models (LLMs) across a wide range of tasks. How…