CLIPArTT: Light-weight Adaptation of CLIP to New Domains at Test Time

[PDF] arxiv.org

Words Matter: Leveraging Individual Text Embeddings for Code Generation in CLIP Test-Time Adaptation

S Mishra, J Silva-Rodrıguez, IB Ayed… - arXiv preprint arXiv …, 2024 - arxiv.org
Vision-language foundation models, such as CLIP, have shown unprecedented zero-shot
performance across a wide range of tasks. Nevertheless, these models may be unreliable …
相关文章 所有 2 个版本
[PDF] arxiv.org

WATT: Weight Average Test-Time Adaption of CLIP

D Osowiechi, M Noori, GAV Hakim… - arXiv preprint arXiv …, 2024 - arxiv.org
Vision-Language Models (VLMs) such as CLIP have yielded unprecedented performance
for zero-shot image classification, yet their generalization capability may still be seriously …
被引用次数：5 相关文章