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We propose a novel framework that leverages Visual Question Answering (VQA) models to automate the evaluation of LLM-generated data visualizations.
M Lewis. 2019 · 1910
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Huggingface’s transformers: State-of-the-art natural language processing
T Wolf. 2019 · 1910
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Natural language interfaces for data analysis with visualization: considering what has and could be asked
Arjun Srinivasan and John Stasko. 2017 · 2017
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A comparative survey of recent natural language interfaces for databases
Katrin Affolter, Kurt Stockinger, and Abraham Bernstein. 2019 · 2019
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Data2vis: Automatic generation of data visualizations using sequence-to-sequence recurrent neural networks
Victor Dibia and Çağatay Demiralp. 2019 · 2019
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al. 2019 · 2019
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Do what i mean, not what i say! design considerations for supporting intent and context in analytical conversation
Melanie Tory and Vidya Setlur. 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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Inchorus: Designing consistent multimodal interactions for data visualization on tablet devices
Arjun Srinivasan, Bongshin Lee, Nathalie Henry Riche, Steven M. Drucker, and Ken Hinckley. 2020 · 2020
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How to ask what to say?: Strategies for evaluating natural language interfaces for data visualization
Arjun Srinivasan and John Stasko. 2020 · 2020
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The language interpretability tool: Extensible, interactive visualizations and analysis for NLP models
Ian Tenney, James Wexler, Jasmijn Bastings, Tolga Bolukbasi, Andy Coenen, Sebastian Gehrmann, Ellen Jiang, Mahima Pushkarna, Carey Radebaugh, Emily Reif, and Ann Yuan. 2020 · 2020
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Designing and evaluating multimodal interactions for facilitating visual analysis with dashboards
Imran Chowdhury, Abdul Moeid, Enamul Hoque, Muhammad Ashad Kabir, Md. Sabir Hossain, and Mohammad Mainul Islam. 2021 · 2021
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Nl4dv: A toolkit for generating analytic specifications for data visualization from natural language queries
Arpit Narechania, Arjun Srinivasan, and John Stasko. 2021 · 2021
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Nl2interface: Interactive visualization interface generation from natural language queries
Yiru Chen, Ryan Li, Austin Mac, Tianbao Xie, Tao Yu, and Eugene Wu. 2022 · 2022
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Ocr-free document understanding transformer
Geewook Kim, Teakgyu Hong, Moonbin Yim, JeongYeon Nam, Jinyoung Park, Jinyeong Yim, Wonseok Hwang, Sangdoo Yun, Dongyoon Han, and Seunghyun Park. 2022 · 2022
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ChartQA: A benchmark for question answering about charts with visual and logical reasoning
Ahmed Masry, Xuan Long Do, Jia Qing Tan, Shafiq Joty, and Enamul Hoque. 2022 · 2022
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Beyond generating code: Evaluating gpt on a data visualization course
Zhutian Chen, Chenyang Zhang, Qianwen Wang, Jakob Troidl, Simon Warchol, Johanna Beyer, Nils Gehlenborg, and Hanspeter Pfister. 2023 · 2023
Chat2vis: Generating data visualizations via natural language using chatgpt, codex and gpt-3 large language models
Paula Maddigan and Teo Susnjak. 2023 · 2023
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UniChart: A universal vision-language pretrained model for chart comprehension and reasoning
Ahmed Masry, Parsa Kavehzadeh, Xuan Long Do, Enamul Hoque, and Shafiq Joty. 2023 · 2023
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Towards natural language interfaces for data visualization: A survey
Leixian Shen, Enya Shen, Yuyu Luo, Xiaocong Yang, Xuming Hu, Xiongshuai Zhang, Zhiwei Tai, and Jianmin Wang. 2023 · 2023
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Mapping with chatgpt
Ran Tao and Jinwen Xu. 2023 · 2023
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VIST5: An adaptive, retrieval-augmented language model for visualization-oriented dialog
Henrik Voigt, Nuno Carvalhais, Monique Meuschke, Markus Reichstein, Sina Zarrie, and Kai Lawonn. 2023 · 2023
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Is GPT-4 a good data analyst?
Liying Cheng, Xingxuan Li, and Lidong Bing. 2023 · 2023
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LIDA: A tool for automatic generation of grammar-agnostic visualizations and infographics using large language models
Victor Dibia. 2023 · 2023
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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
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Conversational ai threads for visualizing multidimensional datasets
Matt-Heun Hong and Anamaria Crisan. 2023 · 2023
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Chatbot-based natural language interfaces for data visualisation: A scoping review
Ecem Kavaz, Anna Puig, and Inmaculada Rodríguez. 2023 · 2023
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Pix2struct: Screenshot parsing as pretraining for visual language understanding
Kenton Lee, Mandar Joshi, Iulia Raluca Turc, Hexiang Hu, Fangyu Liu, Julian Martin Eisenschlos, Urvashi Khandelwal, Peter Shaw, Ming-Wei Chang, and Kristina Toutanova. 2023 · 2023
Cited alongside, same era.
MatCha: Enhancing visual language pretraining with math reasoning and chart derendering
Fangyu Liu, Francesco Piccinno, Syrine Krichene, Chenxi Pang, Kenton Lee, Mandar Joshi, Yasemin Altun, Nigel Collier, and Julian Eisenschlos. 2023 · 2023
Cited alongside, same era.
Viseval: A benchmark for data visualization in the era of large language models
Nan Chen, Yuge Zhang, Jiahang Xu, Kan Ren, and Yuqing Yang. 2024 · 2024
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How do analysts understand and verify ai-assisted data analyses?
Ken Gu, Ruoxi Shang, Tim Althoff, Chenglong Wang, and Steven M. Drucker. 2024 · 2024
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How good is chatgpt in giving advice on your visualization design?
Nam Wook Kim, Grace Myers, and Benjamin Bach. 2024 · 2024
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Visualization generation with large language models: An evaluation
Guozheng Li, Xinyu Wang, Gerile Aodeng, Shunyuan Zheng, Yu Zhang, Chuangxin Ou, Song Wang, and Chi Harold Liu. 2024 · 2024
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Meta-llama-3-70b-instruct-fp8
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Chartgpt: Leveraging llms to generate charts from abstract natural language
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Leva: Using large language models to enhance visual analytics
Yuheng Zhao, Yixing Zhang, Yu Zhang, Xinyi Zhao, Junjie Wang, Zekai Shao, Cagatay Turkay, and Siming Chen. 2024 · 2024
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