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.CV2024
Unveiling Uncertainty: A Deep Dive into Calibration and Performance of Multimodal Large Language Models
Zijun Chen, Wenbo Hu, Guande He +3
Multimodal large language models (MLLMs) combine visual and textual data for tasks such as image captioning and visual question answering. Proper uncertainty calibration is crucial…