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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 0SourcePDFScholar
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…