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We introduce Kosmos-2, a Multimodal Large Language Model (MLLM), enabling new capabilities of perceiving object descriptions (e.g., bounding boxes) and grounding text to the visual world.
Generation and comprehension of unambiguous object descriptions
Junhua Mao, Jonathan Huang, Alexander Toshev, Oana-Maria Camburu, Alan Loddon Yuille, and Kevin P. Murphy · 2015
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Flickr30k entities: Collecting region-to-phrase correspondences for richer image-to-sentence models
Bryan A. Plummer, Liwei Wang, Christopher M. Cervantes, Juan C. Caicedo, J. Hockenmaier, and Svetlana Lazebnik · 2015
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Cider: Consensus-based image description evaluation
Ramakrishna Vedantam, C Lawrence Zitnick, and Devi Parikh · 2015
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Visual genome: Connecting language and vision using crowdsourced dense image annotations
Ranjay Krishna, Yuke Zhu, Oliver Groth, Justin Johnson, Kenji Hata, Joshua Kravitz, Stephanie Chen, Yannis Kalantidis, Li-Jia Li, David A. Shamma, Michael S. Bernstein, and Li Fei-Fei · 2016
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Modeling context in referring expressions
Licheng Yu, Patrick Poirson, Shan Yang, Alexander C. Berg, and Tamara L. Berg · 2016
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A joint speaker-listener-reinforcer model for referring expressions
Licheng Yu, Hao Tan, Mohit Bansal, and Tamara L. Berg · 2017
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Uniter: Universal image-text representation learning
Yen-Chun Chen, Linjie Li, Licheng Yu, Ahmed El Kholy, Faisal Ahmed, Zhe Gan, Yu Cheng, and Jingjing Liu · 2019
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Visualbert: A simple and performant baseline for vision and language
Liunian Harold Li, Mark Yatskar, Da Yin, Cho-Jui Hsieh, and Kai-Wei Chang · 2019
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SuperGLUE: A stickier benchmark for general-purpose language understanding systems
Alex Wang, Yada Pruksachatkun, Nikita Nangia, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R Bowman · 2019
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spaCy: Industrial-strength Natural Language Processing in Python
Matthew Honnibal, Ines Montani, Sofie Van Landeghem, and Adriane Boyd · 2020
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Pix2seq: A language modeling framework for object detection
Ting Chen, Saurabh Saxena, Lala Li, David J. Fleet, and Geo rey E. Hinton · 2021
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Mdetr - modulated detection for end-to-end multi-modal understanding
Aishwarya Kamath, Mannat Singh, Yann LeCun, Ishan Misra, Gabriel Synnaeve, and Nicolas Carion · 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, Roman Ring, Eliza Rutherford, Serkan Cabi, Tengda Han, Zhitao Gong, Sina Samangooei, Marianne Monteiro, Jacob Menick, Sebastian Borgeaud, Andrew Brock, Aida Nematzadeh, Sahand Sharifzadeh, Mikolaj Binkowski, Ricardo Barreira, Oriol Vinyals, Andrew Zisserman, and Karen Simonyan · 2022
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CM3: A causal masked multimodal model of the Internet
Armen Aghajanyan, Bernie Huang, Candace Ross, Vladimir Karpukhin, Hu Xu, Naman Goyal, Dmytro Okhonko, Mandar Joshi, Gargi Ghosh, Mike Lewis, and Luke Zettlemoyer · 2022
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Coyo-700m: Image-text pair dataset, 2022
Minwoo Byeon, Beomhee Park, Haecheon Kim, Sungjun Lee, Woonhyuk Baek, and Saehoon Kim · 2022
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Coarse-to-fine vision-language pre-training with fusion in the backbone
Hongyu Wang, Shuming Ma, Shaohan Huang, Li Dong, Wenhui Wang, Zhiliang Peng, Yu Wu, Payal Bajaj, Saksham Singhal, Alon Benhaim, Barun Patra, Zhun Liu, Vishrav Chaudhary, Xia Song, and Furu Wei · 2022
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Unifying architectures, tasks, and modalities through a simple sequence-to-sequence learning framework
Peng Wang, An Yang, Rui Men, Junyang Lin, Shuai Bai, Zhikang Li, Jianxin Ma, Chang Zhou, Jingren Zhou, and Hongxia Yang · 2022
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Breaking common sense: WHOOPS! a vision-and-language benchmark of synthetic and compositional images
Nitzan Bitton-Guetta, Yonatan Bitton, Jack Hessel, Ludwig Schmidt, Yuval Elovici, Gabriel Stanovsky, and Roy Schwartz · 2023
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Palm-e: An embodied multimodal language model
Danny Driess, F. Xia, Mehdi S. M. Sajjadi, Corey Lynch, Aakanksha Chowdhery, Brian Ichter, Ayzaan Wahid, Jonathan Tompson, Quan Ho Vuong, Tianhe Yu, Wenlong Huang, Yevgen Chebotar, Pierre Sermanet, Daniel Duckworth, Sergey Levine, Vincent Vanhoucke, Karol Hausman, Marc Toussaint, Klaus Greff, Andy Zeng, Igor Mordatch, and Peter R. Florence · 2023
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Zi-Yi Dou, Aishwarya Kamath, Zhe Gan, Pengchuan Zhang, Jianfeng Wang, Linjie Li, Zicheng Liu, Ce Liu, Yann LeCun, Nanyun Peng, Jianfeng Gao, and Lijuan Wang · 2022
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Language models are general-purpose interfaces
Yaru Hao, Haoyu Song, Li Dong, Shaohan Huang, Zewen Chi, Wenhui Wang, Shuming Ma, and Furu Wei · 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, Kai-Wei Chang, and Jianfeng Gao · 2022
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TorchScale: Transformers at scale
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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
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Language is not all you need: Aligning perception with language models
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Grill: Grounded vision-language pre-training via aligning text and image regions
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The flan collection: Designing data and methods for effective instruction tuning
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Gpt-4 technical report
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Visionllm: Large language model is also an open-ended decoder for vision-centric tasks
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