Automated Data Visualization from Natural Language via Large Language Models: An Exploratory Study
Summary: Empirical NL2Vis study showing LLMs can outperform prior deep models on unseen/multi-table tables, especially with schema-aware prompt serialization and few-shot in-context learning. Also probes failure modes and iterative refinement (CoT/role-play/code interpreter) to improve generated visualizations. (summarized by gpt-5.4-mini on May 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yang Wu
- 2. Yao Wan
- 3. Hongyu Zhang
- 4. Yulei Sui
- 5. Wucai Wei
- 6. Wei Zhao
- 7. Guandong Xu
- 8. Hai Jin
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,488 | Can Large Language Models Be Query Optimizer for Relational Databases? | 2026 | SIGMOD | 4.4998609e-05 |
| 10,155 | DIVER: A Robust Text-to-SQL System with Dynamic Interactive Value Linking and Evidence Reasoning | 2026 | SIGMOD | 4.1945683e-05 |
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 984 | Natural language to SQL: Where are we today? | 2020 | VLDB | 0.00014857465 |
| 4,825 | Synthesizing Natural Language to Visualization (NL2VIS) Benchmarks from NL2SQL Benchmarks | 2021 | SIGMOD | 5.8946721e-05 |
| 5,484 | DeepEye: Creating Good Data Visualizations by Keyword Search | 2018 | SIGMOD | 5.4826544e-05 |
Previous
Page 1 / 1
Next