Are Large Language Models a Good Replacement of Taxonomies?
Summary: TaxoGlimpse: a benchmark of 10 representative taxonomies spanning common→specialized domains and root→leaf levels to evaluate LLMs on taxonomy discovery. Evaluation of 18 LLMs (3 prompting styles) reveals poor handling of specialized taxonomies and leaf nodes, with QA accuracy dropping up to 30%. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yushi Sun
- 2. Hao Xin
- 3. Kai Sun
- 4. Yifan Ethan Xu
- 5. Xiao Yang
- 6. Xin Luna Dong
- 7. Nan Tang
- 8. Lei Chen
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,235 | ThriftLLM: On Cost-Effective Selection of Large Language Models for Classification Queries | 2025 | VLDB | 4.3690661e-05 |
| 10,713 | CoLA: Model Collaboration for Log-based Anomaly Detection | 2025 | VLDB | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,094 | Common Sense: the Dark Matter of Language and Intelligence (VLDB 2023 Keynote) | 2023 | VLDB | 6.455716e-05 |
| 8,579 | RECA: Related Tables Enhanced Column Semantic Type Annotation Framework | 2023 | VLDB | 4.4922446e-05 |
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