2 papers
cs.LG2026
FediLoRA: Practical Federated Fine-Tuning of Foundation Models Under Missing-Modality Constraints
Lishan Yang, Wei Emma Zhang, Nam Kha Nguygen +4
Federated Learning with LoRA fine-tuning offers an efficient and privacy-aware solution for institutions to collaboratively leverage their large datasets to train VLLMs. However, p…
eess.IV2025
Blind Super Resolution with Reference Images and Implicit Degradation Representation
Huu-Phu Do, Po-Chih Hu, Hao-Chien Hsueh +3
Previous studies in blind super-resolution (BSR) have primarily concentrated on estimating degradation kernels directly from low-resolution (LR) inputs to enhance super-resolution.…