Oct 9, 2023 � Abstract:Prompt learning for vision-language models, e.g., CoOp, has shown great success in adapting CLIP to different downstream tasks,�...
This is the companion code for the implementation of FedTPG proposed in the ICLR 2024 paper Federated Text-driven Prompt Generation for Vision-Language�...
Oct 9, 2023 � (2) We propose FedTPG, a scalable way of learning a unified, generalized text- driven prompt generator across multiple clients with various�...
Text-driven Prompt Generation for Vision-Language Models in Federated Learning. C. Qiu, X. Li, C. Mummadi, M. Ganesh, Z. Li, L. Peng, and W. Lin. CoRR, (2023 ).
Text-driven Prompt Generation for Vision-Language Models in Federated Learning; Shaunak Halbe, James Smith, Junjiao Tian & Zsolt Kira. HePCo: Data-Free�...
Dec 11, 2023 � Can prompt learning overcome vision-language model challenges? The study "Text-driven Prompt Generation for Vision-Language Models in Federated�...
Efficient Test-Time Prompt Tuning for Vision-Language Models, arXiv 2024, -. Text-driven Prompt Generation for Vision-Language Models in Federated Learning�...
Sat 6:30 a.m. - 6:40 a.m.. Text-driven Prompt Generation for Vision-Language Models in Federated Learning ( Oral ) > link SlidesLive Video.
CLIP and Prompt Tuning. The contrastive vision- language pre-trained model CLIP (Radford et al. 2021) transforms image recognition into an image-text matching.
This work proposes a novel personalized FL framework of client-specific Prompt Generation (pFedPG), which learns to deploy a personalized prompt generator�...
