← Search

Keyu Tu

2 accepted papers

2025

A4A: Adapter for Adapter Transfer via All-for-All Mapping for Cross-Architecture Models

CVPR 2025poster

Large-scale text-to-image models evolve rapidly in size and architecture. The existing adapters struggle to keep pace with these models, requiring extensive retraining. This paper proposes a novel adapter transfer framework, A4A (Adapter for Adapter), which uses an all-for-all mapping approach to se…

Cited by 0Source ↗PDF ↗Scholar ↗
2024

Probabilistic Contrastive Learning for Domain Adaptation

IJCAI 2024poster

Contrastive learning has shown impressive success in enhancing feature discriminability for various visual tasks in a self-supervised manner, but the standard contrastive paradigm (features+l2 normalization) has limited benefits when applied in domain adaptation. We find that this is mainly because…