FedHPL: Efficient Heterogeneous Federated Learning with Prompt Tuning and Logit Distillation

27 May 2024

Papers citing "FedHPL: Efficient Heterogeneous Federated Learning with Prompt Tuning and Logit Distillation"

7 / 7 papers shown

Title
A Survey on Parameter-Efficient Fine-Tuning for Foundation Models in Federated Learning Jieming Bian Yuanzhe Peng Lei Wang Yin Huang Jie Xu FedML 55 0 0 29 Apr 2025
A Survey on Federated Fine-tuning of Large Language Models Yebo Wu Chunlin Tian Jingguang Li He Sun Kahou Tam Li Li Chengzhong Xu FedML 81 0 0 15 Mar 2025
Leveraging Foundation Models for Efficient Federated Learning in Resource-restricted Edge Networks S. K. Atapour S. J. Seyedmohammadi S. Mohammad Sheikholeslami J. Abouei Konstantinos N. Plataniotis Arash Mohammadi FedML 47 1 0 14 Sep 2024
Revisiting the Power of Prompt for Visual Tuning Yuzhu Wang Lechao Cheng Chaowei Fang Dingwen Zhang Manni Duan Meng Wang VLM 44 14 0 04 Feb 2024
A Region-Prompted Adapter Tuning for Visual Abductive Reasoning Hao Zhang Yeo Keat Ee Basura Fernando VLM 14 3 0 18 Mar 2023
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 258 7,337 0 11 Nov 2021
FedProto: Federated Prototype Learning across Heterogeneous Clients Yue Tan Guodong Long Lu Liu Tianyi Zhou Qinghua Lu Jing Jiang Chengqi Zhang FedML 141 287 0 01 May 2021