Federated Cross-Modal Style-Aware Prompt Generation (Student Abstract)

Suraj Prasad; Navyansh Mahla; Sunny Gupta; Amit Sethi

AAAI 2026technical0 citations

Federated Cross-Modal Style-Aware Prompt Generation (Student Abstract)

Suraj Prasad, Navyansh Mahla, Sunny Gupta, Amit Sethi

Abstract

Existing federated prompt learning methods for vision-language models like CLIP rely solely on text-based prompts and final-layer visual features, missing crucial multiscale visual details and client-specific style variations. This limits generalization across non-IID distributions and novel classes. We introduce FedCSAP (Federated Cross-Modal Style-Aware Prompt Generation), which harnesses multiscale features from CLIP

BibTeX

@inproceedings{aaai2026_federatedcrossmo,
  title = {Federated Cross-Modal Style-Aware Prompt Generation (Student Abstract)},
  author = {Suraj Prasad and Navyansh Mahla and Sunny Gupta and Amit Sethi},
  booktitle = {AAAI 2026},
  year = {2026}
}