General Table Question Answering via Answer-Formula Joint Generation

ReAcTable: Enhancing ReAct for Table Question Answering

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Compositional Semantic Parsing on Semi-Structured Tables

Pasupat, P.; and Liang, P. 2015 · 2015

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TabFact: A Large-scale Dataset for Table-based Fact Verification

Chen, W.; Wang, H.; Chen, J.; Zhang, Y.; Wang, H.; Li, S.; Zhou, X.; and Wang, W. Y. 2020 · 2020

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TaPas: Weakly Supervised Table Parsing via Pre-training

Herzig, J.; Nowak, P. K.; Mueller, T.; Piccinno, F.; and Eisenschlos, J. 2020 · 2020

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On the Potential of Lexico-logical Alignments for Semantic Parsing to SQL Queries

Shi, T.; Zhao, C.; Boyd-Graber, J.; Daumé III, H.; and Lee, L. 2020 · 2020

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TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data

Yin, P.; Neubig, G.; Yih, W.-t.; and Riedel, S. 2020 · 2020

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FinQA: A Dataset of Numerical Reasoning over Financial Data

Chen, Z.; Chen, W.; Smiley, C.; Shah, S.; Borova, I.; Langdon, D.; Moussa, R.; Beane, M.; Huang, T.-H.; Routledge, B. R.; et al. 2021b · 2021

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LoRA: Low-Rank Adaptation of Large Language Models

Hu, E. J.; yelong shen; Wallis, P.; Allen-Zhu, Z.; Li, Y.; Wang, S.; Wang, L.; and Chen, W. 2022 · 2022

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AIT-QA: Question Answering Dataset over Complex Tables in the Airline Industry

Katsis, Y.; Chemmengath, S.; Kumar, V.; Bharadwaj, S.; Canim, M.; Glass, M.; Gliozzo, A.; Pan, F.; Sen, J.; Sankaranarayanan, K.; et al. 2022 · 2022

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TAPEX: Table Pre-training via Learning a Neural SQL Executor

Liu, Q.; Chen, B.; Guo, J.; Ziyadi, M.; Lin, Z.; Chen, W.; and Lou, J.-G. 2022 · 2022

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API-Assisted Code Generation for Question Answering on Varied Table Structures

Cao, Y.; Chen, S.; Liu, R.; Wang, Z.; and Fried, D. 2023 · 2023

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Binding Language Models in Symbolic Languages

Cheng, Z.; Xie, T.; Shi, P.; Li, C.; Nadkarni, R.; Hu, Y.; Xiong, C.; Radev, D.; Ostendorf, M.; Zettlemoyer, L.; Smith, N. A.; and Yu, T. 2023 · 2023

Cited alongside, same era.

Efficient Memory Management for Large Language Model Serving with PagedAttention

Kwon, W.; Li, Z.; Zhuang, S.; Sheng, Y.; Zheng, L.; Yu, C. H.; Gonzalez, J. E.; Zhang, H.; and Stoica, I. 2023 · 2023

Cited alongside, same era.

LEVER: learning to verify language-to-code generation with execution

Ni, A.; Iyer, S.; Radev, D.; Stoyanov, V.; Yih, W.-t.; Wang, S. I.; and Lin, X. V. 2023 · 2023

Cited alongside, same era.

Large Language Models are Versatile Decomposers: Decomposing Evidence and Questions for Table-based Reasoning

Ye, Y.; Hui, B.; Yang, M.; Li, B.; Huang, F.; and Li, Y. 2023 · 2023

Cited alongside, same era.

Auto-Formula: Recommend Formulas in Spreadsheets using Contrastive Learning for Table Representations

Chen, S.; He, Y.; Cui, W.; Fan, J.; Ge, S.; Zhang, H.; Zhang, D.; and Chaudhuri, S. 2024 · 2024

Cited alongside, same era.

Deepseekmath: Pushing the limits of mathematical reasoning in open language models

Original

Shao, Z.; Wang, P.; Zhu, Q.; Xu, R.; Song, J.; Bi, X.; Zhang, H.; Zhang, M.; Li, Y.; Wu, Y.; et al. 2024 · 2024

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Tablegpt2: A large multimodal model with tabular data integration

Original

Su, A.; Wang, A.; Ye, C.; Zhou, C.; Zhang, G.; Zhu, G.; Wang, H.; Xu, H.; Chen, H.; Li, H.; et al. 2024 · 2024

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Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding

Wang, Z.; Zhang, H.; Li, C.-L.; Eisenschlos, J. M.; Perot, V.; Wang, Z.; Miculicich, L.; Fujii, Y.; Shang, J.; Lee, C.-Y.; and Pfister, T. 2024 · 2024

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TableBench: A Comprehensive and Complex Benchmark for Table Question Answering

Original

Wu, X.; Yang, J.; Chai, L.; Zhang, G.; Liu, J.; Du, X.; Liang, D.; Shu, D.; Cheng, X.; Sun, T.; et al. 2024 · 2024

Later among the works it cites.