10 citations · 13 across the 16 of their papers we have counts for
Showing 2024Show all
3 papers · 1 filter
cs.CV2024
Split to Merge: Unifying Separated Modalities for Unsupervised Domain Adaptation
Xinyao Li, Yuke Li, Zhekai Du +3
Large vision-language models (VLMs) like CLIP have demonstrated good zero-shot learning performance in the unsupervised domain adaptation task. Yet, most transfer approaches for VL…
cs.CV2024
Agile Multi-Source-Free Domain Adaptation
Xinyao Li, Jingjing Li, Fengling Li +2
Efficiently utilizing rich knowledge in pretrained models has become a critical topic in the era of large models. This work focuses on adaptively utilizing knowledge from multiple…
cs.AI2024★ 3 cited
Domain-Agnostic Mutual Prompting for Unsupervised Domain Adaptation
Zhekai Du, Xinyao Li, Fengling Li +3
Conventional Unsupervised Domain Adaptation (UDA) strives to minimize distribution discrepancy between domains, which neglects to harness rich semantics from data and struggles to…