Text2SQL is Not Enough: Unifying AI and Databases with TAG
Summary: Introduce Table‑Augmented Generation (TAG), a unified paradigm that generalizes Text2SQL and RAG to capture broader LM–DB interactions beyond relational‑algebra and point lookups. New TAG benchmarks show standard methods solve ≤20% of queries, evidencing the need for research on tightly integrating LM reasoning/knowledge with DBMS execution. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Asim Biswal
- 2. Liana Patel
- 3. Joseph E. Gonzalez
- 4. Siddharth Jha
- 5. Amog Kamsetty
- 6. Shu Liu
- 7. Carlos Guestrin
- 8. Matei Zaharia
Incoming Citations (Sorted by Pagerank)
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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 |
|---|---|---|---|---|
| 140 | The MADlib Analytics Library or MAD Skills, the SQL | 2012 | VLDB | 0.00042270404 |
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