April 4, 2024, 4:46 a.m. | Zhaoheng Zheng, Jingmin Wei, Xuefeng Hu, Haidong Zhu, Ram Nevatia

cs.CV updates on arXiv.org arxiv.org

arXiv:2312.04076v2 Announce Type: replace
Abstract: Low-shot image classification, where training images are limited or inaccessible, has benefited from recent progress on pre-trained vision-language (VL) models with strong generalizability, e.g. CLIP. Prompt learning methods built with VL models generate text features from the class names that only have confined class-specific information. Large Language Models (LLMs), with their vast encyclopedic knowledge, emerge as the complement. Thus, in this paper, we discuss the integration of LLMs to enhance pre-trained VL models, specifically on …

arxiv classification cs.cv good image language language models large language large language models low prompt type

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