EvoChart: A Benchmark and a Self-Training Approach Towards Real-World Chart Understanding

DVQA: Understanding Data Visualizations via Question Answering

Kafle, K.; Price, B. L.; Cohen, S.; and Kanan, C. 2018 · 2018

Earlier work this paper cites.

FigureQA: An Annotated Figure Dataset for Visual Reasoning

Kahou, S. E.; Michalski, V.; Atkinson, A.; Kádár, Á.; Trischler, A.; and Bengio, Y. 2018 · 2018

Earlier work this paper cites.

ECharts: A declarative framework for rapid construction of web-based visualization

Li, D.; Mei, H.; Shen, Y.; Su, S.; Zhang, W.; Wang, J.; Zu, M.; and Chen, W. 2018 · 2018

Earlier work this paper cites.

Answering Questions about Data Visualizations using Efficient Bimodal Fusion

Kafle, K.; Shrestha, R.; Price, B. L.; Cohen, S.; and Kanan, C. 2020 · 2020

Earlier work this paper cites.

PlotQA: Reasoning over Scientific Plots

Methani, N.; Ganguly, P.; Khapra, M. M.; and Kumar, P. 2020 · 2020

Earlier work this paper cites.

GPT3Mix: Leveraging Large-scale Language Models for Text Augmentation

Yoo, K. M.; Park, D.; Kang, J.; Lee, S.; and Park, W. 2021 · 2021

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ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoning

Masry, A.; Long, D. X.; Tan, J. Q.; Joty, S. R.; and Hoque, E. 2022 · 2022

Earlier work this paper cites.

RealCQA: Scientific Chart Question Answering as a Test-Bed for First-Order Logic

Ahmed, S.; Jawade, B.; Pandey, S.; Setlur, S.; and Govindaraju, V. 2023 · 2023

Earlier work this paper cites.

Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Original

Bai, J.; Bai, S.; Yang, S.; Wang, S.; Tan, S.; Wang, P.; Lin, J.; Zhou, C.; and Zhou, J. 2023 · 2023

Earlier work this paper cites.

ChartReader: A Unified Framework for Chart Derendering and Comprehension without Heuristic Rules

Cheng, Z.; Dai, Q.; and Hauptmann, A. G. 2023 · 2023

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InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning

Dai, W.; Li, J.; Li, D.; Tiong, A. M. H.; Zhao, J.; Wang, W.; Li, B.; Fung, P.; and Hoi, S. C. H. 2023 · 2023

Earlier work this paper cites.

Reinforced Self-Training (ReST) for Language Modeling

Original

Gülçehre, Ç.; Paine, T. L.; Srinivasan, S.; Konyushkova, K.; Weerts, L.; Sharma, A.; Siddhant, A.; Ahern, A.; Wang, M.; Gu, C.; Macherey, W.; Doucet, A.; Firat, O.; and de Freitas, N. 2023 · 2023

Cited alongside, same era.

ChartLlama: A Multimodal LLM for Chart Understanding and Generation

Original

Han, Y.; Zhang, C.; Chen, X.; Yang, X.; Wang, Z.; Yu, G.; Fu, B.; and Zhang, H. 2023 · 2023

Cited alongside, same era.

SPHINX: The Joint Mixing of Weights, Tasks, and Visual Embeddings for Multi-modal Large Language Models

Original

Lin, Z.; Liu, C.; Zhang, R.; Gao, P.; Qiu, L.; Xiao, H.; Qiu, H.; Lin, C.; Shao, W.; Chen, K.; Han, J.; Huang, S.; Zhang, Y.; He, X.; Li, H.; and Qiao, Y. 2023 · 2023

Cited alongside, same era.

UniChart: A Universal Vision-language Pretrained Model for Chart Comprehension and Reasoning

Masry, A.; Kavehzadeh, P.; Long, D. X.; Hoque, E.; and Joty, S. 2023 · 2023

Cited alongside, same era.

ChartAssisstant: A Universal Chart Multimodal Language Model via Chart-to-Table Pre-training and Multitask Instruction Tuning

Meng, F.; Shao, W.; Lu, Q.; Gao, P.; Zhang, K.; Qiao, Y.; and Luo, P. 2024 · 2024

Closest in time.

GPT-4 Technical Report

Original

OpenAI; Achiam, J.; Adler, S.; Agarwal, S.; Ahmad, L.; Akkaya, I.; and et al., F. L. A. 2024 · 2024

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Visual Chain of Thought: Bridging Logical Gaps with Multimodal Infillings

Original

Rose, D.; Himakunthala, V.; Ouyang, A.; He, R.; Mei, A.; Lu, Y.; Saxon, M.; Sonar, C.; Mirza, D.; and Wang, W. Y. 2024 · 2024

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Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Original

Team, G.; Georgiev, P.; Lei, V. I.; Burnell, R.; Bai, L.; Gulati, A.; Tanzer, G.; Vincent, D.; Pan, Z.; Wang, S.; and et al., S. M. 2024 · 2024

Closest in time.