Database Paper Browser

Back to papers

Will LLMs reshape, supercharge, or kill data science? (VLDB 2023 Panel)

Summary: Examines how LLMs can be applied to structured data and data‑science workflows, potentially transforming long‑standing DB problems and automating modeling, cleaning, and query tasks. Contrasts augmentation vs. disruptive scenarios, grounded in prototypes and deployments. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13279
Venue
VLDB
Year
2023
Pagerank
-
Overall Rank
13,197 | 8.20%
DOI
10.14778/3611540.3611634

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

Incoming Citations (Sorted by Pagerank)

Showing 0 of 0 citing papers.

Rank Citing Paper Year Venue Pagerank
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 0 of 0 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
Previous Page 1 / 1 Next

Semantically Similar Papers