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With the advancements in Large Language Models (LLMs), Vision-Language Models (VLMs) have reached a new level of sophistication, showing notable competence in executing intricate cognition and reasoning tasks.
Vizwiz: nearly real-time answers to visual questions
Jeffrey P Bigham, Chandrika Jayant, Hanjie Ji, Greg Little, Andrew Miller, Robert C Miller, Robin Miller, Aubrey Tatarowicz, Brandyn White, Samual White, et al · 2010
Earlier work this paper cites.
Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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Microsoft coco captions: Data collection and evaluation server
Xinlei Chen, Hao Fang, Tsung-Yi Lin, Ramakrishna Vedantam, Saurabh Gupta, Piotr Dollár, and C Lawrence Zitnick · 2015
Earlier work this paper cites.
Coco-text: Dataset and benchmark for text detection and recognition in natural images
Andreas Veit, Tomas Matera, Lukas Neumann, Jiri Matas, and Serge Belongie · 2016
Earlier work this paper cites.
Making the v in vqa matter: Elevating the role of image understanding in visual question answering
Yash Goyal, Tejas Khot, Douglas Summers-Stay, Dhruv Batra, and Devi Parikh · 2017
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An analysis of visual question answering algorithms
Kushal Kafle and Christopher Kanan · 2017
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Why we need new evaluation metrics for nlg
Jekaterina Novikova, Ondřej Dušek, Amanda Cercas Curry, and Verena Rieser · 2017
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Tallyqa: Answering complex counting questions
Manoj Acharya, Kushal Kafle, and Christopher Kanan · 2019
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Gqa: A new dataset for real-world visual reasoning and compositional question answering
Drew A Hudson and Christopher D Manning · 2019
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Ok-vqa: A visual question answering benchmark requiring external knowledge
Kenneth Marino, Mohammad Rastegari, Ali Farhadi, and Roozbeh Mottaghi · 2019
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Towards vqa models that can read
Amanpreet Singh, Vivek Natarajan, Meet Shah, Yu Jiang, Xinlei Chen, Dhruv Batra, Devi Parikh, and Marcus Rohrbach · 2019
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Clevrer: Collision events for video representation and reasoning
Kexin Yi, Chuang Gan, Yunzhu Li, Pushmeet Kohli, Jiajun Wu, Antonio Torralba, and Joshua B Tenenbaum · 2019
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Simcse: Simple contrastive learning of sentence embeddings
Tianyu Gao, Xingcheng Yao, and Danqi Chen · 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
Cited alongside, same era.
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
Cited alongside, same era.
Scaling instruction-finetuned language models
Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Eric Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, et al · 2022
Cited alongside, same era.
Introducing chatgpt
OpenAI · 2022
Cited alongside, same era.
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
Visual programming: Compositional visual reasoning without training
Tanmay Gupta and Aniruddha Kembhavi · 2023
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Generating images with multimodal language models
Jing Yu Koh, Daniel Fried, and Ruslan Salakhutdinov · 2023
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Scaling autoregressive multi-modal models: Pretraining and instruction tuning
Yu Lili, Shi Bowen, Pasunuru Ram, Miller Benjamin, Golovneva Olga, Wang Tianlu, Babu Arun, Tang Binh, Karrer Brian, Sheynin Shelly, Ross Candace, Polyak Adam, Howes Russ, Sharma Vasu, Xu Jacob, Singer Uriel, Li (AI) Daniel, Ghosh Gargi, Taigman Yaniv, Fazel-Zarandi Maryam, Celikyilmaz Asli, Zettlemoyer Luke, and Aghajanyan Armen · 2023
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Gpt-4v(ision) system card, 2023
OpenAI · 2023
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Kosmos-2: Grounding multimodal large language models to the world
Zhiliang Peng, Wenhui Wang, Li Dong, Yaru Hao, Shaohan Huang, Shuming Ma, and Furu Wei · 2023
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Cited alongside, same era.
Panoptic scene graph generation
Jingkang Yang, Yi Zhe Ang, Zujin Guo, Kaiyang Zhou, Wayne Zhang, and Ziwei Liu · 2022
Cited alongside, same era.
Touchstone: Evaluating vision-language models by language models
Shuai Bai, Shusheng Yang, Jinze Bai, Peng Wang, Xingxuan Zhang, Junyang Lin, Xinggang Wang, Chang Zhou, and Jingren Zhou · 2023
Cited alongside, same era.
VisIT-Bench: A Benchmark for Vision-Language Instruction Following Inspired by Real-World Use
Yonatan Bitton, Hritik Bansal, Jack Hessel, Rulin Shao, Wanrong Zhu, Anas Awadalla, Josh Gardner, Rohan Taori, and Ludwig Schimdt · 2023
Cited alongside, same era.
Instructblip: Towards general-purpose vision-language models with instruction tuning
Wenliang Dai, Junnan Li, Dongxu Li, Anthony Meng Huat Tiong, Junqi Zhao, Weisheng Wang, Boyang Li, Pascale Fung, and Steven Hoi · 2023
Cited alongside, same era.
What do llms know about financial markets? a case study on reddit market sentiment analysis
Xiang Deng, Vasilisa Bashlovkina, Feng Han, Simon Baumgartner, and Michael Bendersky · 2023
Cited alongside, same era.
MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models
Chaoyou Fu, Peixian Chen, Yunhang Shen, Yulei Qin, Mengdan Zhang, Xu Lin, Zhenyu Qiu, Wei Lin, Jinrui Yang, Xiawu Zheng, Ke Li, Xing Sun, and Rongrong Ji · 2023
Cited alongside, same era.
Llama-adapter v2: Parameter-efficient visual instruction model
Peng Gao, Jiaming Han, Renrui Zhang, Ziyi Lin, Shijie Geng, Aojun Zhou, Wei Zhang, Pan Lu, Conghui He, Xiangyu Yue, et al · 2023
Cited alongside, same era.
Pandagpt: One model to instruction-follow them all
Yixuan Su, Tian Lan, Huayang Li, Jialu Xu, Yan Wang, and Deng Cai · 2023
Closest in time.
Generative pretraining in multimodality
Quan Sun, Qiying Yu, Yufeng Cui, Fan Zhang, Xiaosong Zhang, Yueze Wang, Hongcheng Gao, Jingjing Liu, Tiejun Huang, and Xinlong Wang · 2023
Closest in time.
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
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LVLM-eHub: A Comprehensive Evaluation Benchmark for Large Vision-Language Models
Peng Xu, Wenqi Shao, Kaipeng Zhang, Peng Gao, Shuo Liu, Meng Lei, Fanqing Meng, Siyuan Huang, Yu Qiao, and Ping Luo · 2023
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mplug-owl: Modularization empowers large language models with multimodality
Qinghao Ye, Haiyang Xu, Guohai Xu, Jiabo Ye, Ming Yan, Yiyang Zhou, Junyang Wang, Anwen Hu, Pengcheng Shi, Yaya Shi, et al · 2023
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LAMM: Language-Assisted Multi-Modal Instruction-Tuning Dataset, Framework, and Benchmark
Zhenfei Yin, Jiong Wang, Jianjian Cao, Zhelun Shi, Dingning Liu, Mukai Li, Lu Sheng, Lei Bai, Xiaoshui Huang, Zhiyong Wang, Jing Shao, and Wanli Ouyang · 2023
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Transfer visual prompt generator across llms
Ao Zhang, Hao Fei, Yuan Yao, Wei Ji, Li Li, Zhiyuan Liu, and Tat-Seng Chua · 2023
Closest in time.
Minigpt-4: Enhancing vision-language understanding with advanced large language models
Deyao Zhu, Jun Chen, Xiaoqian Shen, Xiang Li, and Mohamed Elhoseiny · 2023
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