UNITQA: A Unified Automated Tabular Question Answering System with Multi-Agent Large Language Models
Summary: UNITQA is a unified automated TQA system enabling multi-table queries across varied data sources via multi-agent LLMs. Five agents collaborate under a dynamic FSM scheduler; GUI and data connectors enable production deployment across diverse systems. (summarized by gpt-5-nano on Feb 09 2026)
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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
@inproceedings{zhu_sigmod25,
title = {{UNITQA: A Unified Automated Tabular Question Answering System with 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},
series = {{SIGMOD} '25},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3722212.3725140},
url = {https://dl.acm.org/doi/10.1145/3722212.3725140},
year = {2025}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11,013 | Towards Automated Cross-domain Exploratory Data Analysis through Large Language Models | 2025 | VLDB | 5.093636e-05 |
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,981 | ReAcTable: Enhancing ReAct for Table Question Answering | 2024 | VLDB | 9.3579557e-05 |
| 4,308 | AutoTQA: Towards Autonomous Tabular Question Answering through Multi-Agent Large Language Models | 2024 | VLDB | 6.7682891e-05 |
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