AutoTQA: Towards Autonomous Tabular Question Answering through Multi-Agent Large Language Models
Summary: AutoTQA extends tabular QA from single to multi-table, heterogeneous systems via a five-agent LLM architecture for planning, execution, critique, and scheduling. LinguFlow and connectors enable rapid tool integration, with strong results across four datasets. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Jun-Peng Zhu (East China Normal University; PingCAP)
- 2. Peng Cai (East China Normal University)
- 3. Kai Xu (PingCAP)
- 4. Li Li (PingCAP)
- 5. Yishen Sun (PingCAP)
- 6. Shuai Zhou (PingCAP)
- 7. Haihuang Su (PingCAP)
- 8. Liu Tang (PingCAP)
- 9. Qi Liu (PingCAP)
BibTeX Citation
@article{zhu_vldb24,
title = {{AutoTQA: Towards Autonomous Tabular Question Answering through Multi-Agent Large Language Models}},
author = {Zhu, Jun-Peng and Cai, Peng and Xu, Kai and Li, Li and Sun, Yishen and Zhou, Shuai and Su, Haihuang and Tang, Liu and Liu, Qi},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {12},
pages = {3920--3933},
doi = {10.14778/3685800.3685816},
url = {https://doi.org/10.14778/3685800.3685816},
year = {2024}
}Incoming Citations (Sorted by Pagerank)
Showing 9 of 9 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 6 of 6 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 271 | TiDB: A Raft-based HTAP Database | 2020 | VLDB | 0.00022703024 |
| 1,920 | D-Bot: Database Diagnosis System using Large Language Models | 2024 | VLDB | 9.4846185e-05 |
| 1,948 | Greenplum: A Hybrid Database for Transactional and Analytical Workloads | 2021 | SIGMOD | 9.432395e-05 |
| 1,981 | ReAcTable: Enhancing ReAct for Table Question Answering | 2024 | VLDB | 9.3579557e-05 |
| 4,120 | Big Metadata: When Metadata is Big Data | 2021 | VLDB | 6.8896959e-05 |
| 5,354 | Can Large Language Models Predict Data Correlations from Column Names? | 2023 | VLDB | 6.2515841e-05 |
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