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Generative Large Language Models (LLMs) show potential in data analysis, yet their full capabilities remain uncharted.
A multi-modal interface for man machine interaction with knowledge based systems-mmi 2
EVERT KUIJPERS and MICHAEL WILSON. 1992 · 1992
Earlier work this paper cites.
Persuasive Computers: Perspectives and Research Directions. In Proc. CHI’98 . ACM Press/Addison-Wesley Publishing Co., USA, 225–232
BJ Fogg. 1998 · 1998
Earlier work this paper cites.
CodeBERT: A Pre-Trained Model for Programming and Natural Languages
Zhangyin Feng, Daya Guo, Duyu Tang, Nan Duan, Xiaocheng Feng, Ming Gong, Linjun Shou, Bing Qin, Ting Liu, Daxin Jiang, and Ming Zhou. 2020 · 2002
Earlier work this paper cites.
Using thematic analysis in psychology
Virginia Braun and Victoria Clarke. 2006 · 2006
Earlier work this paper cites.
Constructing Grounded Theory
Kathy Charmaz. 2006 · 2006
Earlier work this paper cites.
Matplotlib: A 2D graphics environment
J. D. Hunter. 2007 · 2007
Earlier work this paper cites.
Show Me: Automatic Presentation for Visual Analysis
Jock Mackinlay, Pat Hanrahan, and Chris Stolte. 2007 · 2007
Earlier work this paper cites.
Characterizing users’ visual analytic activity for insight provenance. In 2008 IEEE Symposium on Visual Analytics Science and Technology . 123–130
David Gotz and Michelle X. Zhou. 2008 · 2008
Earlier work this paper cites.
VizDeck: Self-Organizing Dashboards for Visual Analytics. In Proc. SIGMOD’12 . 681–684
Alicia Key, Bill Howe, Daniel Perry, and Cecilia Aragon. 2012 · 2012
Earlier work this paper cites.
The Persuasive Power of Data Visualization
Anshul Vikram Pandey, Anjali Manivannan, Oded Nov, Margaret Satterthwaite, and Enrico Bertini. 2014 · 2014
Earlier work this paper cites.
DataTone: Managing Ambiguity in Natural Language Interfaces for Data Visualization. In Proc. UIST ’15
Tong Gao, Mira Dontcheva, Eytan Adar, Zhicheng Liu, and Karrie G. Karahalios. 2015 · 2015
Earlier work this paper cites.
Characterizing Provenance in Visualization and Data Analysis: An Organizational Framework of Provenance Types and Purposes
Eric D. Ragan, Alex Endert, Jibonananda Sanyal, and Jian Chen. 2016 · 2015
Earlier work this paper cites.
Voyager: Exploratory Analysis via Faceted Browsing of Visualization Recommendations
Kanit Wongsuphasawat, Dominik Moritz, Anushka Anand, Jock Mackinlay, Bill Howe, and Jeffrey Heer. 2016 · 2015
Earlier work this paper cites.
Eviza: A Natural Language Interface for Visual Analysis. In Proc. UIST’16 (Tokyo, Japan). Association for Computing Machinery, New York, NY, USA, 365–377
Vidya Setlur, Sarah E. Battersby, Melanie Tory, Rich Gossweiler, and Angel X. Chang. 2016 · 2016
Earlier work this paper cites.
Applying Pragmatics Principles for Interaction with Visual Analytics
Enamul Hoque, Vidya Setlur, Melanie Tory, and Isaac Dykeman. 2018 · 2017
Earlier work this paper cites.
GraphScape: A Model for Automated Reasoning about Visualization Similarity and Sequencing. In Proc. CHI’17
Younghoon Kim, Kanit Wongsuphasawat, Jessica Hullman, and Jeffrey Heer. 2017 · 2017
Earlier work this paper cites.
ChartAccent: Annotation for data-driven storytelling. In Proc. PacificVis’17 . 230–239
Donghao Ren, Matthew Brehmer, Bongshin Lee, Tobias Höllerer, and Eun Kyoung Choe. 2017 · 2017
Earlier work this paper cites.
Natural Language Interfaces for Data Analysis with Visualization: Considering What Has and Could Be Asked. In Proc EuroVis’17 Short Papers . 55–59
Arjun Srinivasan and John Stasko. 2017 · 2017
Earlier work this paper cites.
Orko: Facilitating Multimodal Interaction for Visual Exploration and Analysis of Networks
Arjun Srinivasan and John Stasko. 2018 · 2017
Earlier work this paper cites.
Information Visualization Evaluation Using Crowdsourcing
R. Borgo, L. Micallef, B. Bach, F. McGee, and B. Lee. 2018 · 2018
Earlier work this paper cites.
Iris: A Conversational Agent for Complex Tasks. In Proc. CHI’18 . 1–12
Ethan Fast, Binbin Chen, Julia Mendelsohn, Jonathan Bassen, and Michael S. Bernstein. 2018 · 2018
Earlier work this paper cites.
The Story in the Notebook: Exploratory Data Science Using a Literate Programming Tool. In Proc. CHI’18 . Association for Computing Machinery, New York, NY, USA, 1–11
Mary Beth Kery, Marissa Radensky, Mahima Arya, Bonnie E. John, and Brad A. Myers. 2018 · 2018
Earlier work this paper cites.
DeepEye: Creating Good Data Visualizations by Keyword Search. In Proceedings of the 2018 International Conference on Man. SIGMOD’18 . 1733–1736
Yuyu Luo, Xuedi Qin, Nan Tang, Guoliang Li, and Xinran Wang. 2018 · 2018
Earlier work this paper cites.
Formalizing Visualization Design Knowledge as Constraints: Actionable and Extensible Models in Draco
Dominik Moritz, Chenglong Wang, Greg L. Nelson, Halden Lin, Adam M. Smith, Bill Howe, and Jeffrey Heer. 2019 · 2018
Earlier work this paper cites.
Speech Acts in Discourse Context
Craige Roberts. 2018 · 2018
Earlier work this paper cites.
Exploration and Explanation in Computational Notebooks. In Proc. CHI’18 . 1–12
Adam Rule, Aurélien Tabard, and James D. Hollan. 2018 · 2018
Cited alongside, same era.
Altair: Interactive statistical visualizations for python
Jacob VanderPlas, Brian Granger, Jeffrey Heer, Dominik Moritz, Kanit Wongsuphasawat, Arvind Satyanarayan, Eitan Lees, Ilia Timofeev, Ben Welsh, and Scott Sievert. 2018 · 2018
Cited alongside, same era.
Guidelines for Human-AI Interaction. In Proc. CHI’19 . 1–13
Saleema Amershi, Dan Weld, Mihaela Vorvoreanu, Adam Fourney, Besmira Nushi, Penny Collisson, Jina Suh, Shamsi Iqbal, Paul N. Bennett, Kori Inkpen, Jaime Teevan, Ruth Kikin-Gil, and Eric Horvitz. 2019 · 2019
Cited alongside, same era.
Would You Like A Chart With That? Incorporating Visualizations into Conversational Interfaces. In 2019 IEEE Visualization Conference (VIS) . 1–5
Marti Hearst and Melanie Tory. 2019 · 2019
Cited alongside, same era.
Understanding the Role of Alternatives in Data Analysis Practices
Jiali Liu, Nadia Boukhelifa, and James R. Eagan. 2020 · 2019
Cited alongside, same era.
seaborn: statistical data visualization
Michael L. Waskom. 2021 · 2021
Later among the works it cites.
A neural network solves, explains, and generates university math problems by program synthesis and few-shot learning at human level
Iddo Drori, Sarah Zhang, Reece Shuttleworth, Leonard Tang, Albert Lu, Elizabeth Ke, Kevin Liu, Linda Chen, Sunny Tran, Newman Cheng, Roman Wang, Nikhil Singh, Taylor L. Patti, Jayson Lynch, Avi Shporer, Nakul Verma, Eugene Wu, and Gilbert Strang. 2022 · 2022
Later among the works it cites.
The appropriation of conversational AI in the workplace: A taxonomy of AI chatbot users
Lorentsa Gkinko and Amany Elbanna. 2023 · 2022
Later among the works it cites.
Chart Question Answering: State of the Art and Future Directions
E. Hoque, P. Kavehzadeh, and A. Masry. 2022 · 2022
Later among the works it cites.
GenoREC: A Recommendation System for Interactive Genomics Data Visualization
Aditeya Pandey, Sehi L’Yi, Qianwen Wang, Michelle A. Borkin, and Nils Gehlenborg. 2023a · 2022
Later among the works it cites.
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Barack’s Wife Hillary: Using Knowledge Graphs for Fact-Aware Language Modeling. In Proc. ACL’19 . 5962–5971
Robert Logan, Nelson F. Liu, Matthew E. Peters, Matt Gardner, and Sameer Singh. 2019 · 2019
Cited alongside, same era.
Language Models are Unsupervised Multitask Learners
Alec Radford, Jeff Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
Cited alongside, same era.
Do What I Mean, Not What I Say! Design Considerations for Supporting Intent and Context in Analytical Conversation. In 2019 IEEE Conference on Visual Analytics Science and Technology (VAST) . 93–103
Melanie Tory and Vidya Setlur. 2019 · 2019
Cited alongside, same era.
FlowSense: A Natural Language Interface for Visual Data Exploration within a Dataflow System
Bowen Yu and Cláudio T. Silva. 2020 · 2019
Cited alongside, same era.
Universal and Transferable Adversarial Attacks on Aligned Language Models
Andy Zou, Zifan Wang, J. Zico Kolter, and Matt Fredrikson. 2023 · 2019
Cited alongside, same era.
Language Models are Few-Shot Learners
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, T. J. Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeff Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 2020
Cited alongside, same era.
Answering Questions about Charts and Generating Visual Explanations. In Proc. CHI’20 . 1–13
Dae Hyun Kim, Enamul Hoque, and Maneesh Agrawala. 2020 · 2020
Cited alongside, same era.
MEDLEY: Intent-based Recommendations to Support Dashboard Composition
A. Pandey, A. Srinivasan, and V. Setlur. 2023b · 2022
Later among the works it cites.
Synchromesh: Reliable code generation from pre-trained language models
Gabriel Poesia, Oleksandr Polozov, Vu Le, Ashish Tiwari, Gustavo Soares, Christopher Meek, and Sumit Gulwani. 2022 · 2022
Later among the works it cites.
How Do You Converse with an Analytical Chatbot? Revisiting Gricean Maxims for Designing Analytical Conversational Behavior. In Proc. CHI’22 . Article 29, 17 pages
Vidya Setlur and Melanie Tory. 2022 · 2022
Later among the works it cites.
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 · 2022
Later among the works it cites.
Explaining Patterns in Data with Language Models via Interpretable Autoprompting
Chandan Singh, John X. Morris, Jyoti Aneja, Alexander M. Rush, and Jianfeng Gao. 2022 · 2022
Later among the works it cites.
The Why and The How: A Survey on Natural Language Interaction in Visualization. In Proc. NAACL’22 . 348–374
Henrik Voigt, Ozge Alacam, Monique Meuschke, Kai Lawonn, and Sina Zarrieß. 2022 · 2022
Later among the works it cites.
AI Chains: Transparent and Controllable Human-AI Interaction by Chaining Large Language Model Prompts. In Proc. CHI’22 . Article 385, 22 pages
Tongshuang Wu, Michael Terry, and Carrie Jun Cai. 2022 · 2022
Later among the works it cites.
Large Language Models Are Human-Level Prompt Engineers
Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han, Keiran Paster, Silviu Pitis, Harris Chan, and Jimmy Ba. 2022 · 2022
Later among the works it cites.
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Qing Chen, Ying Chen, Wei Shuai, Ruishi Zou, Yi Guo, Jiazhe Wang, and Nana Cao. 2023 · 2023
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Victor C. Dibia. 2023 · 2023
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Nouha Dziri, Ximing Lu, Melanie Sclar, Xiang Lorraine Li, Liwei Jian, Bill Yuchen Lin, Peter West, Chandra Bhagavatula, Ronan Le Bras, Jena D. Hwang, Soumya Sanyal, Sean Welleck, Xiang Ren, Allyson Ettinger, Zaïd Harchaoui, and Yejin Choi. 2023 · 2023
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