MultiVis-Agent: A Multi-Agent Framework with Logic Rules for Reliable and Comprehensive Cross-Modal Data Visualization
Summary: MultiVis-Agent: multi-agent LLM framework for cross-modal chart generation/refinement with images, code, and iterative feedback. Key novelty: four-layer logic rules as mathematical constraints to prevent failures/loops, plus MultiVis-Bench for evaluating reliability and multimodal visualization tasks. (summarized by gpt-5-mini on Apr 11 2026)
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Authors
- 1. Jinwei Lu (Hong Kong Polytechnic University)
- 2. Yuanfeng Song (ByteDance)
- 3. Chen Zhang (Hong Kong Polytechnic University)
- 4. Raymond Chi-Wing Wong (Hong Kong University of Science and Technology)
BibTeX Citation
@inproceedings{lu_sigmod26,
title = {{MultiVis-Agent: A Multi-Agent Framework with Logic Rules for Reliable and Comprehensive Cross-Modal Data Visualization}},
author = {Lu, Jinwei and Song, Yuanfeng and Zhang, Chen and Wong, Raymond Chi-Wing},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3786670},
url = {https://dl.acm.org/doi/10.1145/3786670},
year = {2026}
}
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| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 13,600 | QueryCraft: A Natural Language-Driven NoSQL Database Querying System Powered by Large Language Models | 2026 | VLDB | - |
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