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Tabular data analysis is crucial in various fields, and large language models show promise in this area.
A Coefficient of Agreement for Nominal Scales
Cohen, J. 1960 · 1960
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A Coefficient of Agreement for Nominal Scales
Cohen, J. 1960 · 1960
Earlier work this paper cites.
A Guide to the SQL Standard
Date, C. J. 1989 · 1989
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A Guide to the SQL Standard
Date, C. J. 1989 · 1989
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Toward effective insight management in visual analytics systems
Chen, Y.; Yang, J.; and Ribarsky, W. 2009 · 2009
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Toward effective insight management in visual analytics systems
Chen, Y.; Yang, J.; and Ribarsky, W. 2009 · 2009
Earlier work this paper cites.
Compositional Semantic Parsing on Semi-Structured Tables
Pasupat, P.; and Liang, P. 2015 · 2015
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Compositional Semantic Parsing on Semi-Structured Tables
Pasupat, P.; and Liang, P. 2015 · 2015
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Language to Logical Form with Neural Attention
Dong, L.; and Lapata, M. 2016 · 2016
Earlier work this paper cites.
Language to Logical Form with Neural Attention
Dong, L.; and Lapata, M. 2016 · 2016
Earlier work this paper cites.
Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning
Zhong, V.; Xiong, C.; and Socher, R. 2017 · 2017
Earlier work this paper cites.
Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning
Zhong, V.; Xiong, C.; and Socher, R. 2017 · 2017
Earlier work this paper cites.
DeepEye: Towards Automatic Data Visualization
Luo, Y.; Qin, X.; Tang, N.; and Li, G. 2018 · 2018
Earlier work this paper cites.
Forecasting at scale
Taylor, S. J.; and Letham, B. 2018 · 2018
Earlier work this paper cites.
DeepEye: Towards Automatic Data Visualization
Luo, Y.; Qin, X.; Tang, N.; and Li, G. 2018 · 2018
Earlier work this paper cites.
Forecasting at scale
Taylor, S. J.; and Letham, B. 2018 · 2018
Earlier work this paper cites.
QuickInsights: Quick and Automatic Discovery of Insights from Multi-Dimensional Data
Ding, R.; Han, S.; Xu, Y.; Zhang, H.; and Zhang, D. 2019 · 2019
Earlier work this paper cites.
Formalizing Visualization Design Knowledge as Constraints: Actionable and Extensible Models in Draco
Moritz, D.; Wang, C.; Nelson, G. L.; Lin, H.; Smith, A. M.; Howe, B.; and Heer, J. 2019 · 2019
Cited alongside, same era.
QuickInsights: Quick and Automatic Discovery of Insights from Multi-Dimensional Data
Ding, R.; Han, S.; Xu, Y.; Zhang, H.; and Zhang, D. 2019 · 2019
Cited alongside, same era.
Formalizing Visualization Design Knowledge as Constraints: Actionable and Extensible Models in Draco
Moritz, D.; Wang, C.; Nelson, G. L.; Lin, H.; Smith, A. M.; Howe, B.; and Heer, J. 2019 · 2019
Cited alongside, same era.
TaPas: Weakly Supervised Table Parsing via Pre-training
Herzig, J.; Nowak, P. K.; Müller, T.; Piccinno, F.; and Eisenschlos, J. 2020 · 2020
Cited alongside, same era.
TaPas: Weakly Supervised Table Parsing via Pre-training
Herzig, J.; Nowak, P. K.; Müller, T.; Piccinno, F.; and Eisenschlos, J. 2020 · 2020
Cited alongside, same era.
StarCoder: may the source be with you!
Li, R.; Allal, L. B.; Zi, Y.; Muennighoff, N.; Kocetkov, D.; Mou, C.; Marone, M.; Akiki, C.; Li, J.; Chim, J.; Liu, Q.; Zheltonozhskii, E.; Zhuo, T. Y.; Wang, T.; Dehaene, O.; Davaadorj, M.; Lamy-Poirier, J.; Monteiro, J.; Shliazhko, O.; Gontier, N.; Meade, N.; Zebaze, A.; Yee, M.-H.; Umapathi, L. K.; Zhu, J.; Lipkin, B.; Oblokulov, M.; Wang, Z.; Murthy, R.; Stillerman, J.; Patel, S. S.; Abulkhanov, D.; Zocca, M.; Dey, M.; Zhang, Z.; Fahmy, N.; Bhattacharyya, U.; Yu, W.; Singh, S.; Luccioni, S.; Villegas, P.; Kunakov, M.; Zhdanov, F.; Romero, M.; Lee, T.; Timor, N.; Ding, J.; Schlesinger, C.; Schoelkopf, H.; Ebert, J.; Dao, T.; Mishra, M.; Gu, A.; Robinson, J.; Anderson, C. J.; Dolan-Gavitt, B.; Contractor, D.; Reddy, S.; Fried, D.; Bahdanau, D.; Jernite, Y.; Ferrandis, C. M.; Hughes, S.; Wolf, T.; Guha, A.; von Werra, L.; and de Vries, H. 2023 · 2023
Closest in time.
Demonstration of InsightPilot: An LLM-Empowered Automated Data Exploration System
Ma, P.; Ding, R.; Wang, S.; Han, S.; and Zhang, D. 2023 · 2023
Closest in time.
CodeGen2: Lessons for Training LLMs on Programming and Natural Languages
Nijkamp, E.; Hayashi, H.; Xiong, C.; Savarese, S.; and Zhou, Y. 2023 · 2023
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OpenAI. 2023 · 2023
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Hosseini, R.; Yang, K.; Chen, A.; and Patra, S. 2021 · 2021
Cited alongside, same era.
A Deep Dive into Deep Learning Approaches for Text-to-SQL Systems , 2846–2851
Katsogiannis-Meimarakis, G.; and Koutrika, G. 2021 · 2021
Cited alongside, same era.
Metainsight: Automatic discovery of structured knowledge for exploratory data analysis
Ma, P.; Ding, R.; Han, S.; and Zhang, D. 2021 · 2021
Cited alongside, same era.
Table2Charts: Recommending Charts by Learning Shared Table Representations
Zhou, M.; Li, Q.; He, X.; Li, Y.; Liu, Y.; Ji, W.; Han, S.; Chen, Y.; Jiang, D.; and Zhang, D. 2021 · 2021
Cited alongside, same era.
A flexible forecasting model for production systems
Hosseini, R.; Yang, K.; Chen, A.; and Patra, S. 2021 · 2021
Cited alongside, same era.
A Deep Dive into Deep Learning Approaches for Text-to-SQL Systems , 2846–2851
Katsogiannis-Meimarakis, G.; and Koutrika, G. 2021 · 2021
Cited alongside, same era.
Metainsight: Automatic discovery of structured knowledge for exploratory data analysis
Ma, P.; Ding, R.; Han, S.; and Zhang, D. 2021 · 2021
Cited alongside, same era.
Creating a Coding Assistant with StarCoder
Tunstall, L.; Lambert, N.; Rajani, N.; Beeching, E.; Le Scao, T.; von Werra, L.; Han, S.; Schmid, P.; and Rush, A. 2023 · 2023
Closest in time.
Know What I don’t Know: Handling Ambiguous and Unknown Questions for Text-to-SQL
Wang, B.; Gao, Y.; Li, Z.; and Lou, J.-G. 2023 · 2023
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Large Language Models are Versatile Decomposers: Decompose Evidence and Questions for Table-based Reasoning
Ye, Y.; Hui, B.; Yang, M.; Li, B.; Huang, F.; and Li, Y. 2023 · 2023
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Large Language Models are few(1)-shot Table Reasoners
Chen, W. 2023 · 2023
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StructGPT: A general framework for Large Language Model to Reason on Structured Data
Jiang, J.; Zhou, K.; Dong, Z.; Ye, K.; Zhao, W. X.; and Wen, J.-R. 2023 · 2023
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StarCoder: may the source be with you!
Li, R.; Allal, L. B.; Zi, Y.; Muennighoff, N.; Kocetkov, D.; Mou, C.; Marone, M.; Akiki, C.; Li, J.; Chim, J.; Liu, Q.; Zheltonozhskii, E.; Zhuo, T. Y.; Wang, T.; Dehaene, O.; Davaadorj, M.; Lamy-Poirier, J.; Monteiro, J.; Shliazhko, O.; Gontier, N.; Meade, N.; Zebaze, A.; Yee, M.-H.; Umapathi, L. K.; Zhu, J.; Lipkin, B.; Oblokulov, M.; Wang, Z.; Murthy, R.; Stillerman, J.; Patel, S. S.; Abulkhanov, D.; Zocca, M.; Dey, M.; Zhang, Z.; Fahmy, N.; Bhattacharyya, U.; Yu, W.; Singh, S.; Luccioni, S.; Villegas, P.; Kunakov, M.; Zhdanov, F.; Romero, M.; Lee, T.; Timor, N.; Ding, J.; Schlesinger, C.; Schoelkopf, H.; Ebert, J.; Dao, T.; Mishra, M.; Gu, A.; Robinson, J.; Anderson, C. J.; Dolan-Gavitt, B.; Contractor, D.; Reddy, S.; Fried, D.; Bahdanau, D.; Jernite, Y.; Ferrandis, C. M.; Hughes, S.; Wolf, T.; Guha, A.; von Werra, L.; and de Vries, H. 2023 · 2023
Closest in time.
Demonstration of InsightPilot: An LLM-Empowered Automated Data Exploration System
Ma, P.; Ding, R.; Wang, S.; Han, S.; and Zhang, D. 2023 · 2023
Closest in time.
CodeGen2: Lessons for Training LLMs on Programming and Natural Languages
Nijkamp, E.; Hayashi, H.; Xiong, C.; Savarese, S.; and Zhou, Y. 2023 · 2023
Closest in time.
OpenAI. 2023 · 2023
Closest in time.
Creating a Coding Assistant with StarCoder
Tunstall, L.; Lambert, N.; Rajani, N.; Beeching, E.; Le Scao, T.; von Werra, L.; Han, S.; Schmid, P.; and Rush, A. 2023 · 2023
Closest in time.
Know What I don’t Know: Handling Ambiguous and Unknown Questions for Text-to-SQL
Wang, B.; Gao, Y.; Li, Z.; and Lou, J.-G. 2023 · 2023
Closest in time.
Large Language Models are Versatile Decomposers: Decompose Evidence and Questions for Table-based Reasoning
Ye, Y.; Hui, B.; Yang, M.; Li, B.; Huang, F.; and Li, Y. 2023 · 2023
Closest in time.