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The success of large language models (LLMs) has inspired an emerging research field of multimodal learning.
Vader: A parsimonious rule-based model for sentiment analysis of social media text
Clayton Hutto and Eric Gilbert · 2014
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textblob documentation
Steven Loria et al · 2018
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Improved artgan for conditional synthesis of natural image and artwork
Wei Ren Tan, Chee Seng Chan, Hernan Aguirre, and Kiyoshi Tanaka · 2018
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Parameter-efficient transfer learning for nlp
Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski, Bruna Morrone, Quentin De Laroussilhe, Andrea Gesmundo, Mona Attariyan, and Sylvain Gelly · 2019
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Sentence-bert: Sentence embeddings using siamese bert-networks
Nils Reimers and Iryna Gurevych · 2019
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Language models are few-shot learners
Tom B Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
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Artemis: Affective language for visual art
Panos Achlioptas, Maks Ovsjanikov, Kilichbek Haydarov, Mohamed Elhoseiny, and Leonidas Guibas · 2021
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Towards a unified view of parameter-efficient transfer learning
Junxian He, Chunting Zhou, Xuezhe Ma, Taylor Berg-Kirkpatrick, and Graham Neubig · 2021
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Vilt: Vision-and-language transformer without convolution or region supervision
Wonjae Kim, Bokyung Son, and Ildoo Kim · 2021
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Prefix-tuning: Optimizing continuous prompts for generation
Xiang Lisa Li and Percy Liang · 2021
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M6: A chinese multimodal pretrainer, 2021
Junyang Lin, Rui Men, An Yang, Chang Zhou, Ming Ding, Yichang Zhang, Peng Wang, Ang Wang, Le Jiang, Xianyan Jia, Jie Zhang, Jianwei Zhang, Xu Zou, Zhikang Li, Xiaodong Deng, Jie Liu, Jinbao Xue, Huiling Zhou, Jianxin Ma, Jin Yu, Yong Li, Wei Lin, Jingren Zhou, Jie Tang, and Hongxia Yang · 2021
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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 · 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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Multimodal few-shot learning with frozen language models
Maria Tsimpoukelli, Jacob L Menick, Serkan Cabi, SM Eslami, Oriol Vinyals, and Felix Hill · 2021
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Flamingo: a visual language model for few-shot learning
Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, Antoine Miech, Iain Barr, Yana Hasson, Karel Lenc, Arthur Mensch, Katherine Millican, Malcolm Reynolds, et al · 2022
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Visual prompting: Modifying pixel space to adapt pre-trained models
Bitfit: Simple parameter-efficient fine-tuning for transformer-based masked language-models
Elad Ben Zaken, Yoav Goldberg, and Shauli Ravfogel · 2022
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Multimodal-gpt: A vision and language model for dialogue with humans, 2023
Tao Gong, Chengqi Lyu, Shilong Zhang, Yudong Wang, Miao Zheng, Qian Zhao, Kuikun Liu, Wenwei Zhang, Ping Luo, and Kai Chen · 2023
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Junnan Li, Dongxu Li, Silvio Savarese, and Steven Hoi · 2023
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Visual instruction tuning, 2023
Haotian Liu, Chunyuan Li, Qingyang Wu, and Yong Jae Lee · 2023
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Introducing chatgpt
OpenAI · 2023
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Gpt-4 technical report, 2023
OpenAI · 2023
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Hyojin Bahng, Ali Jahanian, Swami Sankaranarayanan, and Phillip Isola · 2022
Cited alongside, same era.
Visual prompt tuning
Menglin Jia, Luming Tang, Bor-Chun Chen, Claire Cardie, Serge Belongie, Bharath Hariharan, and Ser-Nam Lim · 2022
Cited alongside, same era.
Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation, 2022
Junnan Li, Dongxu Li, Caiming Xiong, and Steven Hoi · 2022
Cited alongside, same era.
Youssef Mohamed, Faizan Farooq Khan, Kilichbek Haydarov, and Mohamed Elhoseiny · 2022
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Hierarchical text-conditional image generation with clip latents, 2022
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
Cited alongside, same era.
Laion-5b: An open large-scale dataset for training next generation image-text models
Christoph Schuhmann, Romain Beaumont, Richard Vencu, Cade Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, et al · 2022
Cited alongside, same era.
Git: A generative image-to-text transformer for vision and language
Jianfeng Wang, Zhengyuan Yang, Xiaowei Hu, Linjie Li, Kevin Lin, Zhe Gan, Zicheng Liu, Ce Liu, and Lijuan Wang · 2022
Cited alongside, same era.
Visualgpt: Data-efficient adaptation of pretrained language models for image captioning
Jun Chen, Han Guo, Kai Yi, Boyang Li, and Mohamed Elhoseiny
Cited in the paper.
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Mar: Masked autoencoders for efficient action recognition
Zhiwu Qing, Shiwei Zhang, Ziyuan Huang, Xiang Wang, Yuehuan Wang, Yiliang Lv, Changxin Gao, and Nong Sang · 2023
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AIM: Adapting image models for efficient video action recognition
Taojiannan Yang, Yi Zhu, Yusheng Xie, Aston Zhang, Chen Chen, and Mu Li · 2023
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mplug-owl: Modularization empowers large language models with multimodality, 2023
Qinghao Ye, Haiyang Xu, Guohai Xu, Jiabo Ye, Ming Yan, Yiyang Zhou, Junyang Wang, Anwen Hu, Pengcheng Shi, Yaya Shi, Chenliang Li, Yuanhong Xu, Hehong Chen, Junfeng Tian, Qian Qi, Ji Zhang, and Fei Huang · 2023
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Minigpt-4: Enhancing vision-language understanding with advanced large language models
Deyao Zhu, Jun Chen, Xiaoqian Shen, Xiang Li, and Mohamed Elhoseiny · 2023
Closest in time.