Database Paper Browser

Back to papers

OpenForge: Probabilistic Metadata Integration

Summary: Two-stage prior–posterior framework for metadata-concept alignment: fine-tuned LLMs and ensemble scorers produce priors over candidate relationships. A Markov Random Field refines them by maximizing joint assignment probability and encoding constraints (e.g., transitivity), achieving ≈25 F1 gain over GPT‑4. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13930
Venue
VLDB
Year
2025
Pagerank
4.1945683e-05
Overall Rank
10,645 | 25.95%
DOI
10.14778/3746405.3746417

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 15 of 15 cited papers.

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

Previous Page 1 / 1 Next

Semantically Similar Papers