nvAgent: Automated Data Visualization from Natural Language via Collaborative Agent Workflow

Geliang Ouyang, Jingyao Chen, Zhihe Nie, Yi Gui, Yao Wan, Hongyu Zhang, Dongping Chen


Abstract
*Natural Language to Visualization* (NL2Vis) seeks to convert natural-language descriptions into visual representations of given tables, empowering users to derive insights from large-scale data. Recent advancements in *Large Language Models* (LLMs) show promise in automating code generation to transform tabular data into accessible visualizations. However, they often struggle with complex queries that require reasoning across multiple tables. To address this limitation, we propose a collaborative agent workflow, termed **nvAgent**, for NL2Vis. Specifically, **nvAgent** comprises three agents: a processor agent for database processing and context filtering, a composer agent for planning visualization generation, and a validator agent for code translation and output verification. Comprehensive evaluations on the new VisEval benchmark demonstrate that **nvAgent** consistently surpasses state-of-the-art baselines, achieving a 7.88% improvement in single-table and a 9.23% improvement in multi-table scenarios. Qualitative analyses further highlight that **nvAgent** maintains nearly a 20% performance margin over previous models, underscoring its capacity to produce high-quality visual representations from complex, heterogeneous data sources. All datasets and source code are available at: [https://github.com/geliang0114/nvAgent](https://github.com/geliang0114/nvAgent).
Anthology ID:
2025.acl-long.960
Volume:
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
July
Year:
2025
Address:
Vienna, Austria
Editors:
Wanxiang Che, Joyce Nabende, Ekaterina Shutova, Mohammad Taher Pilehvar
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
19534–19567
Language:
URL:
https://preview.aclanthology.org/ingestion-acl-25/2025.acl-long.960/
DOI:
Bibkey:
Cite (ACL):
Geliang Ouyang, Jingyao Chen, Zhihe Nie, Yi Gui, Yao Wan, Hongyu Zhang, and Dongping Chen. 2025. nvAgent: Automated Data Visualization from Natural Language via Collaborative Agent Workflow. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 19534–19567, Vienna, Austria. Association for Computational Linguistics.
Cite (Informal):
nvAgent: Automated Data Visualization from Natural Language via Collaborative Agent Workflow (Ouyang et al., ACL 2025)
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PDF:
https://preview.aclanthology.org/ingestion-acl-25/2025.acl-long.960.pdf