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Han et al., 2024 - Google Patents

Dota: Distributional test-time adaptation of vision-language models

Han et al., 2024

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Document ID
14786199961698906049
Author
Han Z
Yang J
Wang G
Li J
Xu Q
Shou M
Zhang C
Publication year
Publication venue
arXiv preprint arXiv:2409.19375

External Links

Snippet

Vision-language foundation models (VLMs), such as CLIP, exhibit remarkable performance across a wide range of tasks. However, deploying these models can be unreliable when significant distribution gaps exist between training and test data, while fine-tuning for diverse …
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