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Reasoning about images with rich text, such as charts and documents, is a critical application of vision-language models (VLMs).
Sentence-bert: Sentence embeddings using siamese bert-networks
N Reimers. 2019 · 1908
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A diagram is worth a dozen images
Aniruddha Kembhavi, Mike Salvato, Eric Kolve, Minjoon Seo, Hannaneh Hajishirzi, and Ali Farhadi. 2016 · 2016
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Figureseer: Parsing result-figures in research papers
Noah Siegel, Zachary Horvitz, Roie Levin, Santosh Divvala, and Ali Farhadi. 2016 · 2016
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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 · 2017
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Clevr: A diagnostic dataset for compositional language and elementary visual reasoning
Justin Johnson, Bharath Hariharan, Laurens Van Der Maaten, Li Fei-Fei, C Lawrence Zitnick, and Ross Girshick. 2017 · 2017
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Driving in the matrix: Can virtual worlds replace human-generated annotations for real world tasks?
Matthew Johnson-Roberson, Charles Barto, Rounak Mehta, Sharath Nittur Sridhar, Karl Rosaen, and Ram Vasudevan. 2017 · 2017
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FigureQA: An annotated figure dataset for visual reasoning
Samira Ebrahimi Kahou, Vincent Michalski, Adam Atkinson, Ákos Kádár, Adam Trischler, and Yoshua Bengio. 2017 · 2017
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Vizwiz grand challenge: Answering visual questions from blind people
Danna Gurari, Qing Li, Abigale J Stangl, Anhong Guo, Chi Lin, Kristen Grauman, Jiebo Luo, and Jeffrey P Bigham. 2018 · 2018
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DVQA: Understanding data visualizations via question answering
Kushal Kafle, Brian Price, Scott Cohen, and Christopher Kanan. 2018 · 2018
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Know what you don’t know: Unanswerable questions for SQuAD
Pranav Rajpurkar, Robin Jia, and Percy Liang. 2018 · 2018
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TallyQA: Answering complex counting questions
Manoj Acharya, Kushal Kafle, and Christopher Kanan. 2019 · 2019
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Scene text visual question answering
Ali Furkan Biten, Ruben Tito, Andres Mafla, Lluis Gomez, Marçal Rusinol, Ernest Valveny, CV Jawahar, and Dimosthenis Karatzas. 2019 · 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 · 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 · 2019
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Ocr-vqa: Visual question answering by reading text in images
Anand Mishra, Shashank Shekhar, Ajeet Kumar Singh, and Anirban Chakraborty. 2019 · 2019
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Towards VQA models that can read
Amanpreet Singh, Vivek Natarjan, Meet Shah, Yu Jiang, Xinlei Chen, Devi Parikh, and Marcus Rohrbach. 2019 · 2019
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PlotQA: Reasoning over scientific plots
Nitesh Methani, Pritha Ganguly, Mitesh M Khapra, and Pratyush Kumar. 2020 · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu. 2020 · 2020
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Stl-cqa: Structure-based transformers with localization and encoding for chart question answering
Hrituraj Singh and Sumit Shekhar. 2020 · 2020
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DocVQA: A dataset for VQA on document images
Minesh Mathew, Dimosthenis Karatzas, and CV Jawahar. 2021 · 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, Gretchen Krueger, and Ilya Sutskever. 2021 · 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 · 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 · 2022
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Simvqa: Exploring simulated environments for visual question answering
Paola Cascante-Bonilla, Hui Wu, Letao Wang, Rogerio S Feris, and Vicente Ordonez. 2022 · 2022
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Learn to explain: Multimodal reasoning via thought chains for science question answering
Pan Lu, Swaroop Mishra, Tanglin Xia, Liang Qiu, Kai-Wei Chang, Song-Chun Zhu, Oyvind Tafjord, Peter Clark, and Ashwin Kalyan. 2022 · 2022
Cited alongside, same era.
ChartQA: A benchmark for question answering about charts with visual and logical reasoning
Ahmed Masry, Do Long, Jia Qing Tan, Shafiq Joty, and Enamul Hoque. 2022 · 2022
Cited alongside, same era.
InfographicVQA
Minesh Mathew, Viraj Bagal, Rubèn Tito, Dimosthenis Karatzas, Ernest Valveny, and CV Jawahar. 2022 · 2022
Cited alongside, same era.
Seeclick: Harnessing gui grounding for advanced visual gui agents
Kanzhi Cheng, Qiushi Sun, Yougang Chu, Fangzhi Xu, Yantao Li, Jianbing Zhang, and Zhiyong Wu. 2024 · 2024
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Molmo and pixmo: Open weights and open data for state-of-the-art multimodal models
Matt Deitke, Christopher Clark, Sangho Lee, Rohun Tripathi, Yue Yang, Jae Sung Park, Mohammadreza Salehi, Niklas Muennighoff, Kyle Lo, Luca Soldaini, et al. 2024 · 2024
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Scaling synthetic data creation with 1,000,000,000 personas
Tao Ge, Xin Chan, Xiaoyang Wang, Dian Yu, Haitao Mi, and Dong Yu. 2024 · 2024
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Navigating the digital world as humans do: Universal visual grounding for gui agents
Boyu Gou, Ruohan Wang, Boyuan Zheng, Yanan Xie, Cheng Chang, Yiheng Shu, Huan Sun, and Yu Su. 2024 · 2024
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A-OKVQA: A benchmark for visual question answering using world knowledge
Dustin Schwenk, Apoorv Khandelwal, Christopher Clark, Kenneth Marino, and Roozbeh Mottaghi. 2022 · 2022
Cited alongside, same era.
Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al. 2022 · 2022
Cited alongside, same era.
Chartllama: A multimodal llm for chart understanding and generation
Yucheng Han, Chi Zhang, Xin Chen, Xu Yang, Zhibin Wang, Gang Yu, Bin Fu, and Hanwang Zhang. 2023 · 2023
Cited alongside, same era.
Albert Q Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, et al. 2023 · 2023
Cited alongside, same era.
Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models
Junnan Li, Dongxu Li, Silvio Savarese, and Steven Hoi. 2023 · 2023
Cited alongside, same era.
Scigraphqa: A large-scale synthetic multi-turn question-answering dataset for scientific graphs
Shengzhi Li and Nima Tajbakhsh. 2023 · 2023
Cited alongside, same era.
Visual instruction tuning
Haotian Liu, Chunyuan Li, Qingyang Wu, and Yong Jae Lee. 2023 · 2023
Cited alongside, same era.
Wei He, Zhiheng Xi, Wanxu Zhao, Xiaoran Fan, Yiwen Ding, Zifei Shan, Tao Gui, Qi Zhang, and Xuanjing Huang. 2024 · 2024
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Cogagent: A visual language model for gui agents
Wenyi Hong, Weihan Wang, Qingsong Lv, Jiazheng Xu, Wenmeng Yu, Junhui Ji, Yan Wang, Zihan Wang, Yuxiao Dong, Ming Ding, et al. 2024 · 2024
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Tablevqa-bench: A visual question answering benchmark on multiple table domains
Yoonsik Kim, Moonbin Yim, and Ka Yeon Song. 2024 · 2024
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LLaVA-OneVision: Easy visual task transfer
Bo Li, Yuanhan Zhang, Dong Guo, Renrui Zhang, Feng Li, Hao Zhang, Kaichen Zhang, Yanwei Li, Ziwei Liu, and Chunyuan Li. 2024 · 2024
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Llava-next: Improved reasoning, ocr, and world knowledge
Haotian Liu, Chunyuan Li, Yuheng Li, Bo Li, Yuanhan Zhang, Sheng Shen, and Yong Jae Lee. 2024 · 2024
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Llama 3.2: Revolutionizing edge ai and vision with open, customizable models
Meta. 2024 · 2024
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Unraveling the truth: Do VLMs really understand charts? a deep dive into consistency and robustness
Srija Mukhopadhyay, Adnan Qidwai, Aparna Garimella, Pritika Ramu, Vivek Gupta, and Dan Roth. 2024 · 2024
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DataDreamer: A tool for synthetic data generation and reproducible LLM workflows
Ajay Patel, Colin Raffel, and Chris Callison-Burch. 2024 · 2024
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Scifibench: Benchmarking large multimodal models for scientific figure interpretation
Jonathan Roberts, Kai Han, Neil Houlsby, and Samuel Albanie. 2024 · 2024
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Sbs figures: Pre-training figure qa from stage-by-stage synthesized images
Risa Shinoda, Kuniaki Saito, Shohei Tanaka, Tosho Hirasawa, and Yoshitaka Ushiku. 2024 · 2024
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To cot or not to cot? chain-of-thought helps mainly on math and symbolic reasoning
Zayne Sprague, Fangcong Yin, Juan Diego Rodriguez, Dongwei Jiang, Manya Wadhwa, Prasann Singhal, Xinyu Zhao, Xi Ye, Kyle Mahowald, and Greg Durrett. 2024 · 2024
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Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Gemini Team. 2024 · 2024
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Cambrian-1: A fully open, vision-centric exploration of multimodal LLMs
Shengbang Tong, Ellis Brown, Penghao Wu, Sanghyun Woo, Manoj Middepogu, Sai Charitha Akula, Jihan Yang, Shusheng Yang, Adithya Iyer, Xichen Pan, et al. 2024 · 2024
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Chartx & chartvlm: A versatile benchmark and foundation model for complicated chart reasoning
Renqiu Xia, Bo Zhang, Hancheng Ye, Xiangchao Yan, Qi Liu, Hongbin Zhou, Zijun Chen, Min Dou, Botian Shi, Junchi Yan, et al. 2024 · 2024
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Osworld: Benchmarking multimodal agents for open-ended tasks in real computer environments
Tianbao Xie, Danyang Zhang, Jixuan Chen, Xiaochuan Li, Siheng Zhao, Ruisheng Cao, Toh Jing Hua, Zhoujun Cheng, Dongchan Shin, Fangyu Lei, Yitao Liu, Yiheng Xu, Shuyan Zhou, Silvio Savarese, Caiming Xiong, Victor Zhong, and Tao Yu. 2024 · 2024
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xGen-MM (BLIP-3): A family of open large multimodal models
Le Xue, Manli Shu, Anas Awadalla, Jun Wang, An Yan, Senthil Purushwalkam, Honglu Zhou, Viraj Prabhu, Yutong Dai, Michael S Ryoo, et al. 2024 · 2024
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Provision: Programmatically scaling vision-centric instruction data for multimodal language models
Jieyu Zhang, Le Xue, Linxin Song, Jun Wang, Weikai Huang, Manli Shu, An Yan, Zixian Ma, Juan Carlos Niebles, Caiming Xiong, et al. 2024 · 2024
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