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We perform a missing, reproducible evaluation of all publicly available GPT-4 family models concerning the Document Understanding field, where it is frequently required to comprehend text spacial arrangement and visual clues in addition to textual semantics.
Document Visual Question Answering Challenge 2020
Minesh Mathew, Ruben Tito, Dimosthenis Karatzas, R Manmatha, and CV Jawahar. 2020 · 2008
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From dataset recycling to multi-property extraction and beyond
Tomasz Dwojak, Michał Pietruszka, Łukasz Borchmann, Jakub Chłędowski, and Filip Graliński. 2020 · 2020
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DUE: End-to-End Document Understanding Benchmark
Łukasz Borchmann, Michał Pietruszka, Tomasz Stanisławek, Dawid Jurkiewicz, Michał Turski, Karolina Szyndler, and Filip Graliński. 2021 · 2021
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Teaching models to express their uncertainty in words
Stephanie Lin, Jacob Hilton, and Owain Evans. 2022 · 2022
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InfographicVQA
Minesh Mathew, Viraj Bagal, Rubèn Tito, Dimosthenis Karatzas, Ernest Valveny, and CV Jawahar. 2022 · 2022
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Qwen-vl: A versatile vision-language model for understanding, localization, text reading, and beyond
Jinze Bai, Shuai Bai, Shusheng Yang, Shijie Wang, Sinan Tan, Peng Wang, Junyang Lin, Chang Zhou, and Jingren Zhou. 2023 · 2023
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Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks
Zhe Chen, Jiannan Wu, Wenhai Wang, Weijie Su, Guo Chen, Sen Xing, Zhong Muyan, Qinglong Zhang, Xizhou Zhu, Lewei Lu, et al. 2023 · 2023
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Time Travel in LLMs: Tracing Data Contamination in Large Language Models
Shahriar Golchin and Mihai Surdeanu. 2023 · 2023
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Lost in the Middle: How Language Models Use Long Contexts
Nelson F. Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, and Percy Liang. 2023 · 2023
Cited alongside, same era.
Document Understanding Dataset and Evaluation (DUDE)
Jordy Van Landeghem, Rubèn Tito, Łukasz Borchmann, Michał Pietruszka, Pawel Joziak, Rafal Powalski, Dawid Jurkiewicz, Mickael Coustaty, Bertrand Anckaert, Ernest Valveny, Matthew Blaschko, Sien Moens, and Tomasz Stanislawek. 2023 · 2023
Later among the works it cites.
Gram: Global reasoning for multi-page vqa
Tsachi Blau, Sharon Fogel, Roi Ronen, Alona Golts, Roy Ganz, Elad Ben Avraham, Aviad Aberdam, Shahar Tsiper, and Ron Litman. 2024 · 2024
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How far are we to gpt-4v? closing the gap to commercial multimodal models with open-source suites
Zhe Chen, Weiyun Wang, Hao Tian, Shenglong Ye, Zhangwei Gao, Erfei Cui, Wenwen Tong, Kongzhi Hu, Jiapeng Luo, Zheng Ma, et al. 2024 · 2024
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Ryota Tanaka, Taichi Iki, Kyosuke Nishida, Kuniko Saito, and Jun Suzuki. 2024 · 2024
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SlideVQA: A Dataset for Document Visual Question Answering on Multiple Images
Ryota Tanaka, Kyosuke Nishida, Kosuke Nishida, Taku Hasegawa, Itsumi Saito, and Kuniko Saito. 2023 · 2023
Cited alongside, same era.