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Pre-trained vision-language models (VLMs) like CLIP have demonstrated impressive zero-shot performance on a wide range of downstream computer vision tasks.
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Jordan T Ash, Chicheng Zhang, Akshay Krishnamurthy, John Langford, and Alekh Agarwal · 2019
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Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification
Patrick Helber, Benjamin Bischke, Andreas Dengel, and Damian Borth · 2019
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
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Autoprompt: Eliciting knowledge from language models with automatically generated prompts
Taylor Shin, Yasaman Razeghi, Robert L Logan IV, Eric Wallace, and Sameer Singh · 2020
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Transfer learning for image classification using vgg19: Caltech-101 image data set
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Timo Lüddecke and Alexander Ecker · 2022
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Slip: Self-supervision meets language-image pre-training
Norman Mu, Alexander Kirillov, David Wagner, and Saining Xie · 2022
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Active learning by feature mixing
Amin Parvaneh, Ehsan Abbasnejad, Damien Teney, Gholamreza Reza Haffari, Anton Van Den Hengel, and Javen Qinfeng Shi · 2022
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Flava: A foundational language and vision alignment model
Amanpreet Singh, Ronghang Hu, Vedanuj Goswami, Guillaume Couairon, Wojciech Galuba, Marcus Rohrbach, and Douwe Kiela · 2022
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Ontology-enhanced prompt-tuning for few-shot learning
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Sequential graph convolutional network for active learning
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Scaling up visual and vision-language representation learning with noisy text supervision
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Active domain adaptation via clustering uncertainty-weighted embeddings
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Vlp: A survey on vision-language pre-training
Fei-Long Chen, Du-Zhen Zhang, Ming-Lun Han, Xiu-Yi Chen, Jing Shi, Shuang Xu, and Bo Xu · 2023
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Junnan Li, Dongxu Li, Silvio Savarese, and Steven Hoi · 2023
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Investigating the limitation of clip models: The worst-performing categories
Jie-Jing Shao, Jiang-Xin Shi, Xiao-Wen Yang, Lan-Zhe Guo, and Yu-Feng Li · 2023
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Towards free data selection with general-purpose models
Yichen Xie, Mingyu Ding, Masayoshi Tomizuka, and Wei Zhan · 2023
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Alip: Adaptive language-image pre-training with synthetic caption
Kaicheng Yang, Jiankang Deng, Xiang An, Jiawei Li, Ziyong Feng, Jia Guo, Jing Yang, and Tongliang Liu · 2023
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Adversarial prompt tuning for vision-language models
Jiaming Zhang, Xingjun Ma, Xin Wang, Lingyu Qiu, Jiaqi Wang, Yu-Gang Jiang, and Jitao Sang · 2023
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Prompt-aligned gradient for prompt tuning
Beier Zhu, Yulei Niu, Yucheng Han, Yue Wu, and Hanwang Zhang · 2023
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Entropic open-set active learning
Bardia Safaei, VS Vibashan, Celso M de Melo, and Vishal M Patel · 2024
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