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Foundation models, large-scale, pre-trained deep-learning models adapted to a wide range of downstream tasks have gained significant interest lately in various deep-learning problems undergoing a paradigm shift with the rise of these models.
Representation learning with contrastive predictive coding
Aäron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
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Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov · 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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Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
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A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2020
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Big self-supervised models are strong semi-supervised learners
Ting Chen, Simon Kornblith, Kevin Swersky, Mohammad Norouzi, and Geoffrey E. Hinton · 2020
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Rethinking bias-variance trade-off for generalization of neural networks
Zitong Yang, Yaodong Yu, Chong You, Jacob Steinhardt, and Yi Ma · 2020
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On the opportunities and risks of foundation models
Rishi Bommasani, Drew A Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, et al · 2021
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Scaling up visual and vision-language representation learning with noisy text supervision
Chao Jia, Yinfei Yang, Ye Xia, Yi-Ting Chen, Zarana Parekh, Hieu Pham, Quoc Le, Yun-Hsuan Sung, Zhen Li, and Tom Duerig · 2021
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Filip: Fine-grained interactive language-image pre-training
Lewei Yao, Runhui Huang, Lu Hou, Guansong Lu, Minzhe Niu, Hang Xu, Xiaodan Liang, Zhenguo Li, Xin Jiang, and Chunjing Xu · 2021
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Laion-400m: Open dataset of clip-filtered 400 million image-text pairs
Christoph Schuhmann, Richard Vencu, Romain Beaumont, Robert Kaczmarczyk, Clayton Mullis, Aarush Katta, Theo Coombes, Jenia Jitsev, and Aran Komatsuzaki · 2021
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Slip: Self-supervision meets language-image pre-training, 2021
Norman Mu, Alexander Kirillov, David Wagner, and Saining Xie · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Filip: Fine-grained interactive language-image pre-training
Lewei Yao, Runhu Huang, Lu Hou, Guansong Lu, Minzhe Niu, Hang Xu, Xiaodan Liang, Zhenguo Li, Xin Jiang, and Chunjing Xu · 2021
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Beit: Bert pre-training of image transformers
Hangbo Bao, Li Dong, and Furu Wei · 2021
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Align before fuse: Vision and language representation learning with momentum distillation
Junnan Li, Ramprasaath R. Selvaraju, Akhilesh Deepak Gotmare, Shafiq R. Joty, Caiming Xiong, and Steven C. H. Hoi · 2021
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Lora: Low-rank adaptation of large language models
Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen · 2021
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Palm: Scaling language modeling with pathways
Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, et al · 2022
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Galactica: A large language model for science
Ross Taylor, Marcin Kardas, Guillem Cucurull, Thomas Scialom, Anthony Hartshorn, Elvis Saravia, Andrew Poulton, Viktor Kerkez, and Robert Stojnic · 2022
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Expert-level detection of pathologies from unannotated chest x-ray images via self-supervised learning
Ekin Tiu, Ellie Talius, Pujan Patel, Curtis P Langlotz, Andrew Y Ng, and Pranav Rajpurkar · 2022
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Medclip: Contrastive learning from unpaired medical images and text
Zifeng Wang, Zhenbang Wu, Dinesh Agarwal, and Jimeng Sun · 2022
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Clinical-bert: Vision-language pre-training for radiograph diagnosis and reports generation
Bin Yan and Mingtao Pei · 2022
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Towards reasoning in large language models: A survey
Jie Huang and Kevin Chen-Chuan Chang · 2022
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Unified contrastive learning in image-text-label space
J. Yang, C. Li, P. Zhang, B. Xiao, C. Liu, L. Yuan, and J. Gao · 2022
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Grounded language-image pre-training
Liunian Harold Li, Pengchuan Zhang, Haotian Zhang, Jianwei Yang, Chunyuan Li, Yiwu Zhong, Lijuan Wang, Lu Yuan, Lei Zhang, Jenq-Neng Hwang, et al · 2022
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Glipv2: Unifying localization and vision-language understanding
Haotian Zhang, Pengchuan Zhang, Xiaowei Hu, Yen-Chun Chen, Liunian Li, Xiyang Dai, Lijuan Wang, Lu Yuan, Jenq-Neng Hwang, and Jianfeng Gao · 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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Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al · 2022
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Constitutional ai: Harmlessness from ai feedback
Yuntao Bai, Saurav Kadavath, Sandipan Kundu, Amanda Askell, Jackson Kernion, Andy Jones, Anna Chen, Anna Goldie, Azalia Mirhoseini, Cameron McKinnon, et al · 2022
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Biomedlm: a domain-specific large language model for biomedical text
A Venigalla, J Frankle, and M Carbin · 2022
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Medical image segmentation review: The success of u-net
Reza Azad, Ehsan Khodapanah Aghdam, Amelie Rauland, Yiwei Jia, Atlas Haddadi Avval, Afshin Bozorgpour, Sanaz Karimijafarbigloo, Joseph Paul Cohen, Ehsan Adeli, and Dorit Merhof · 2022
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Anti-oversmoothing in deep vision transformers via the fourier domain analysis: From theory to practice
Peihao Wang, Wenqing Zheng, Tianlong Chen, and Zhangyang Wang · 2022
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Foundational models defining a new era in vision: A survey and outlook
Muhammad Awais, Muzammal Naseer, Salman Khan, Rao Muhammad Anwer, Hisham Cholakkal, Mubarak Shah, Ming-Hsuan Yang, and Fahad Shahbaz Khan · 2023
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Llama: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, et al · 2023
Cited alongside, same era.
Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C Berg, Wan-Yen Lo, et al · 2023
Cited alongside, same era.
Sam-med2d, 2023
Junlong Cheng, Jin Ye, Zhongying Deng, Jianpin Chen, Tianbin Li, Haoyu Wang, Yanzhou Su, Ziyan Huang, Jilong Chen, Lei Jiang, Hui Sun, Junjun He, Shaoting Zhang, Min Zhu, and Yu Qiao · 2023
Cited alongside, same era.
Segment anything in medical images
Jun Ma and Bo Wang · 2023
Cited alongside, same era.
Medlsam: Localize and segment anything model for 3d medical images
Sam-u: Multi-box prompts triggered uncertainty estimation for reliable sam in medical image, 2023
Guoyao Deng, Ke Zou, Kai Ren, Meng Wang, Xuedong Yuan, Sancong Ying, and Huazhu Fu · 2023
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How to efficiently adapt large segmentation model (sam) to medical images
Xinrong Hu, Xiaowei Xu, and Yiyu Shi · 2023
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Medical sam adapter: Adapting segment anything model for medical image segmentation
Junde Wu, Rao Fu, Huihui Fang, Yuanpei Liu, Zhaowei Wang, Yanwu Xu, Yueming Jin, and Tal Arbel · 2023
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Customized segment anything model for medical image segmentation
Kaidong Zhang and Dong Liu · 2023
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Wenhui Lei, Xu Wei, Xiaofan Zhang, Kang Li, and Shaoting Zhang · 2023
Cited alongside, same era.
Inpaint anything: Segment anything meets image inpainting
Tao Yu, Runseng Feng, Ruoyu Feng, Jinming Liu, Xin Jin, Wenjun Zeng, and Zhibo Chen · 2023
Cited alongside, same era.
Any-to-any style transfer: Making picasso and da vinci collaborate
Songhua Liu, Jingwen Ye, and Xinchao Wang · 2023
Cited alongside, same era.
Caption anything: Interactive image description with diverse multimodal controls
Teng Wang, Jinrui Zhang, Junjie Fei, Yixiao Ge, Hao Zheng, Yunlong Tang, Zhe Li, Mingqi Gao, Shanshan Zhao, Ying Shan, et al · 2023
Cited alongside, same era.
Zhanghexuan Ji, Dazhou Guo, Puyang Wang, Ke Yan, Jia Ge, Xianghua Ye, Minfeng Xu, Jingren Zhou, Le Lu, Mingchen Gao, et al · 2023
Cited alongside, same era.
Text-guided foundation model adaptation for pathological image classification
Yunkun Zhang, Jin Gao, Mu Zhou, Xiaosong Wang, Yu Qiao, Shaoting Zhang, and Dequan Wang · 2023
Cited alongside, same era.
Advances in medical image analysis with vision transformers: A comprehensive review
Reza Azad, Amirhossein Kazerouni, Moein Heidari, Ehsan Khodapanah Aghdam, Amirali Molaei, Yiwei Jia, Abin Jose, Rijo Roy, and Dorit Merhof · 2023
Cited alongside, same era.
Foundation model for endoscopy video analysis via large-scale self-supervised pre-train
Zhao Wang, Chang Liu, Shaoting Zhang, and Qi Dou · 2023
Cited alongside, same era.
Eugene Vorontsov, Alican Bozkurt, Adam Casson, George Shaikovski, Michal Zelechowski, Siqi Liu, Philippe Mathieu, Alexander van Eck, Donghun Lee, Julian Viret, et al · 2023
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Pmc-llama: Towards building open-source language models for medicine, 2023
Chaoyi Wu, Weixiong Lin, Xiaoman Zhang, Ya Zhang, Yanfeng Wang, and Weidi Xie · 2023
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Clinicalgpt: Large language models finetuned with diverse medical data and comprehensive evaluation, 2023
Guangyu Wang, Guoxing Yang, Zongxin Du, Longjun Fan, and Xiaohu Li · 2023
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Llava-med: Training a large language-and-vision assistant for biomedicine in one day
Chunyuan Li, Cliff Wong, Sheng Zhang, Naoto Usuyama, Haotian Liu, Jianwei Yang, Tristan Naumann, Hoifung Poon, and Jianfeng Gao · 2023
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Xraygpt: Chest radiographs summarization using medical vision-language models
Omkar Thawkar, Abdelrahman Shaker, Sahal Shaji Mullappilly, Hisham Cholakkal, Rao Muhammad Anwer, Salman Khan, Jorma Laaksonen, and Fahad Shahbaz Khan · 2023
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Radiology-llama2: Best-in-class large language model for radiology, 2023
Zhengliang Liu, Yiwei Li, Peng Shu, Aoxiao Zhong, Longtao Yang, Chao Ju, Zihao Wu, Chong Ma, Jie Luo, Cheng Chen, Sekeun Kim, Jiang Hu, Haixing Dai, Lin Zhao, Dajiang Zhu, Jun Liu, Wei Liu, Dinggang Shen, Tianming Liu, Quanzheng Li, and Xiang Li · 2023
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Chatcad: Interactive computer-aided diagnosis on medical image using large language models
Sheng Wang, Zihao Zhao, Xi Ouyang, Qian Wang, and Dinggang Shen · 2023
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Deid-gpt: Zero-shot medical text de-identification by gpt-4
Zheng-Long Liu, Xiao-Xing Yu, Lu Zhang, Zihao Wu, Chao-Yang Cao, Haixing Dai, Lin Zhao, W. Liu, Dinggang Shen, Quanzheng Li, Tianming Liu, Dajiang Zhu, and Xiang Li · 2023
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Chatdoctor: A medical chat model fine-tuned on llama model using medical domain knowledge
Li Yunxiang, Li Zihan, Zhang Kai, Dan Ruilong, and Zhang You · 2023
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Visual med-alpaca: A parameter-efficient biomedical llm with visual capabilities
Chang Shu, Chen Baian, Fangyu Liu, Zihao Fu, Ehsan Shareghi, and Nigel Collier · 2023
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Diffusion models in medical imaging: A comprehensive survey
Amirhossein Kazerouni, Ehsan Khodapanah Aghdam, Moein Heidari, Reza Azad, Mohsen Fayyaz, Ilker Hacihaliloglu, and Dorit Merhof · 2023
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A survey of large language models
Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Xiaolei Wang, Yupeng Hou, Yingqian Min, Beichen Zhang, Junjie Zhang, Zican Dong, et al · 2023
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A bibliometric review of large language models research from 2017 to 2023
Lizhou Fan, Lingyao Li, Zihui Ma, Sanggyu Lee, Huizi Yu, and Libby Hemphill · 2023
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A systematic survey of prompt engineering on vision-language foundation models
Jindong Gu, Zhen Han, Shuo Chen, Ahmad Beirami, Bailan He, Gengyuan Zhang, Ruotong Liao, Yao Qin, Volker Tresp, and Philip Torr · 2023
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Vision-language models for vision tasks: A survey
Jingyi Zhang, Jiaxing Huang, Sheng Jin, and Shijian Lu · 2023
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On the challenges and perspectives of foundation models for medical image analysis
Shaoting Zhang and Dimitris Metaxas · 2023
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Xinsong Zhang, Yan Zeng, Jipeng Zhang, and Hang Li · 2023
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Image captioners are scalable vision learners too
Michael Tschannen, Manoj Kumar, Andreas Steiner, Xiaohua Zhai, Neil Houlsby, and Lucas Beyer · 2023
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Images speak in images: A generalist painter for in-context visual learning
Xinlong Wang, Wen Wang, Yue Cao, Chunhua Shen, and Tiejun Huang · 2023
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Segclip: Patch aggregation with learnable centers for open-vocabulary semantic segmentation
Huaishao Luo, Junwei Bao, Youzheng Wu, Xiaodong He, and Tianrui Li · 2023
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Junnan Li, Dongxu Li, Silvio Savarese, and Steven C. H. Hoi · 2023
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3dsam-adapter: Holistic adaptation of sam from 2d to 3d for promptable medical image segmentation
Shizhan Gong, Yuan Zhong, Wenao Ma, Jinpeng Li, Zhao Wang, Jingyang Zhang, Pheng-Ann Heng, and Qi Dou · 2023
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Pmc-llama: Further finetuning llama on medical papers
Chaoyi Wu, Xiaoman Zhang, Ya Zhang, Yanfeng Wang, and Weidi Xie · 2023
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Black box adversarial prompting for foundation models
Natalie Maus, Patrick Chao, Eric Wong, and Jacob R Gardner · 2023
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Xu Zhao, Wenchao Ding, Yongqi An, Yinglong Du, Tao Yu, Min Li, Ming Tang, and Jinqiao Wang · 2023
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YOLO by Ultralytics, January 2023
Glenn Jocher, Ayush Chaurasia, and Jing Qiu · 2023
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Laplacian-former: Overcoming the limitations of vision transformers in local texture detection
Reza Azad, Amirhossein Kazerouni, Babak Azad, Ehsan Khodapanah Aghdam, Yury Velichko, Ulas Bagci, and Dorit Merhof · 2023
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Beyond self-attention: Deformable large kernel attention for medical image segmentation
Reza Azad, Leon Niggemeier, Michael Huttemann, Amirhossein Kazerouni, Ehsan Khodapanah Aghdam, Yury Velichko, Ulas Bagci, and Dorit Merhof · 2023
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