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Large language models are effective at few-shot in-context learning (ICL).
Bag-of-visual-words and spatial extensions for land-use classification
Yi Yang and Shawn Newsam · 2010
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Cats and dogs
Omkar M Parkhi, Andrea Vedaldi, Andrew Zisserman, and CV Jawahar · 2012
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Describing textures in the wild
Mircea Cimpoi, Subhransu Maji, Iasonas Kokkinos, Sammy Mohamed, and Andrea Vedaldi · 2014
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From detection of individual metastases to classification of lymph node status at the patient level: the camelyon17 challenge
Peter Bandi, Oscar Geessink, Quirine Manson, Marcory Van Dijk, Maschenka Balkenhol, Meyke Hermsen, Babak Ehteshami Bejnordi, Byungjae Lee, Kyunghyun Paeng, Aoxiao Zhong, et al · 2018
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Recognition in terra incognita
Sara Beery, Grant Van Horn, and Pietro Perona · 2018
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A dataset of clinically generated visual questions and answers about radiology images
Jason J Lau, Soumya Gayen, Asma Ben Abacha, and Dina Demner-Fushman · 2018
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The ham10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions
Philipp Tschandl, Cliff Rosendahl, and Harald Kittler · 2018
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Deeplesion: automated mining of large-scale lesion annotations and universal lesion detection with deep learning
Ke Yan, Xiaosong Wang, Le Lu, and Ronald M Summers · 2018
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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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Chexpert: A large chest radiograph dataset with uncertainty labels and expert comparison
Jeremy Irvin, Pranav Rajpurkar, Michael Ko, Yifan Yu, Silviana Ciurea-Ilcus, Chris Chute, Henrik Marklund, Behzad Haghgoo, Robyn Ball, Katie Shpanskaya, et al · 2019
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Language models are few-shot learners, 2020
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei · 2020
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Object detection in optical remote sensing images: A survey and a new benchmark
Ke Li, Gang Wan, Gong Cheng, Liqiu Meng, and Junwei Han · 2020
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Rsvqa: Visual question answering for remote sensing data
Sylvain Lobry, Diego Marcos, Jesse Murray, and Devis Tuia · 2020
Cited alongside, same era.
Generalizing from a few examples: A survey on few-shot learning
Yaqing Wang, Quanming Yao, James T Kwok, and Lionel M Ni · 2020
Cited alongside, same era.
Yuanfeng Ji, Lu Zhang, Jiaxiang Wu, Bingzhe Wu, Long-Kai Huang, Tingyang Xu, Yu Rong, Lanqing Li, Jie Ren, Ding Xue, et al · 2022
Cited alongside, same era.
Fives: A fundus image dataset for artificial intelligence based vessel segmentation
Kai Jin, Xingru Huang, Jingxing Zhou, Yunxiang Li, Yan Yan, Yibao Sun, Qianni Zhang, Yaqi Wang, and Juan Ye · 2022
Cited alongside, same era.
Rethinking the role of demonstrations: What makes in-context learning work?
Sewon Min, Xinxi Lyu, Ari Holtzman, Mikel Artetxe, Mike Lewis, Hannaneh Hajishirzi, and Luke Zettlemoyer · 2022
Cited alongside, same era.
Batchprompt: Accomplish more with less
Jianzhe Lin, Maurice Diesendruck, Liang Du, and Robin Abraham · 2023
Later among the works it cites.
Contextual object detection with multimodal large language models
Yuhang Zang, Wei Li, Jun Han, Kaiyang Zhou, and Chen Change Loy · 2023
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Mmicl: Empowering vision-language model with multi-modal in-context learning
Haozhe Zhao, Zefan Cai, Shuzheng Si, Xiaojian Ma, Kaikai An, Liang Chen, Zixuan Liu, Sheng Wang, Wenjuan Han, and Baobao Chang · 2023
Later among the works it cites.
Rishabh Agarwal, Avi Singh, Lei M Zhang, Bernd Bohnet, Stephanie Chan, Ankesh Anand, Zaheer Abbas, Azade Nova, John D Co-Reyes, Eric Chu, et al · 2024
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Learning from few examples: A summary of approaches to few-shot learning
Archit Parnami and Minwoo Lee · 2022
Cited alongside, same era.
Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
Cited alongside, same era.
Self-icl: Zero-shot in-context learning with self-generated demonstrations
Wei-Lin Chen, Cheng-Kuang Wu, and Hsin-Hsi Chen · 2023
Cited alongside, same era.
Batch prompting: Efficient inference with large language model apis
Zhoujun Cheng, Jungo Kasai, and Tao Yu · 2023
Cited alongside, same era.
How well does gpt-4v (ision) adapt to distribution shifts? a preliminary investigation
Zhongyi Han, Guanglin Zhou, Rundong He, Jindong Wang, Xing Xie, Tailin Wu, Yilong Yin, Salman Khan, Lina Yao, Tongliang Liu, et al · 2023
Cited alongside, same era.
In-context learning with many demonstration examples
Mukai Li, Shansan Gong, Jiangtao Feng, Yiheng Xu, Jun Zhang, Zhiyong Wu, and Lingpeng Kong · 2023
Cited alongside, same era.
URL https://ai.meta.com/blog/meta-llama-3/
Introducing meta llama 3: The most capable openly available llm to date
Cited in the paper.
Amanda Bertsch, Maor Ivgi, Uri Alon, Jonathan Berant, Matthew R Gormley, and Graham Neubig · 2024
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Jiayi Liu, Tinghan Yang, and Jennifer Neville · 2024
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Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Machel Reid, Nikolay Savinov, Denis Teplyashin, Dmitry Lepikhin, Timothy Lillicrap, Jean-baptiste Alayrac, Radu Soricut, Angeliki Lazaridou, Orhan Firat, Julian Schrittwieser, et al · 2024
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Multi-task inference: Can large language models follow multiple instructions at once?
Guijin Son, Sangwon Baek, Sangdae Nam, Ilgyun Jeong, and Seungone Kim · 2024
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Dettoolchain: A new prompting paradigm to unleash detection ability of mllm
Yixuan Wu, Yizhou Wang, Shixiang Tang, Wenhao Wu, Tong He, Wanli Ouyang, Jian Wu, and Philip Torr · 2024
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Collage prompting: Budget-friendly visual recognition with gpt-4v
Siyu Xu, Yunke Wang, Daochang Liu, and Chang Xu · 2024
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Vl-icl bench: The devil in the details of benchmarking multimodal in-context learning
Yongshuo Zong, Ondrej Bohdal, and Timothy Hospedales · 2024
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