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ReAcTable: Enhancing ReAct for Table Question Answering

Research article (Proceedings of the VLDB Endowment, 2024) · cited 35× · AI/ML
CreativeWork academia

Facts

4 properties
Instance of
scholarly article[2]
Publication date
April 1, 2024as of 2026-09-23
where from?
Source
OpenAlex
Edition
20260923 · as of 2026-09-23
Bronze
not in the catalog
Transform
4ort-mint · openalex:20260923 · version not recorded
Published in
Proceedings of the VLDB Endowment. International Conference on Very Large Data Basesas of 2026-09-23
where from?
Source
OpenAlex
Edition
20260923 · as of 2026-09-23
Bronze
not in the catalog
Transform
4ort-mint · openalex:20260923 · version not recorded
Title
ReAcTable: Enhancing ReAct for Table Question Answeringas of 2026-09-23
where from?
Source
OpenAlex
Edition
20260923 · as of 2026-09-23
Bronze
not in the catalog
Transform
4ort-mint · openalex:20260923 · version not recorded
🔖 Identifiers · 2
OpenAlex ID
W4399208468as of 2026-09-23
where from?
Source
OpenAlex
Edition
20260923 · as of 2026-09-23
Bronze
not in the catalog
Transform
4ort-mint · openalex:20260923 · version not recorded
DOI
10.14778/3659437.3659452as of 2026-09-23
where from?
Source
OpenAlex
Edition
20260923 · as of 2026-09-23
Bronze
not in the catalog
Transform
4ort-mint · openalex:20260923 · version not recorded
📚 Sources · 1

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📜 Data licence
Source: OpenAlex (openalex.org), snapshot of 2026-09-23. CC0 1.0 Universal. CC0 1.0 Universal · OpenAlex
🔗 Connections
Authored by 5
Avrilia Floratou, Jignesh M. Patel, Jordan Henkel, Joyce Cahoon, Shaleen Deep
← Author of 5
Avrilia Floratou, Jignesh M. Patel, Jordan Henkel, Joyce Cahoon, Shaleen Deep
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Summary

ReAcTable: Enhancing ReAct for Table Question Answering is a scholarly article[1].

References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

📑 Cite this page

Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA 4ort.xyz Knowledge Graph. (2026). ReAcTable: Enhancing ReAct for Table Question Answering. Retrieved October 20, 2026, from https://4ort.xyz/entity/reactable-enhancing-react-for-table-question-answering
MLA “ReAcTable: Enhancing ReAct for Table Question Answering.” 4ort.xyz Knowledge Graph, 4ort.xyz, 20 Oct. 2026, https://4ort.xyz/entity/reactable-enhancing-react-for-table-question-answering.
BibTeX @misc{4ortxyz_reactable-enhancing-react-for-table-question-answering_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{ReAcTable: Enhancing ReAct for Table Question Answering}}, year = {2026}, url = {https://4ort.xyz/entity/reactable-enhancing-react-for-table-question-answering}, note = {Accessed: 2026-10-20}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): ReAcTable: Enhancing ReAct for Table Question Answering — https://4ort.xyz/entity/reactable-enhancing-react-for-table-question-answering (retrieved 2026-10-20)

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