Glean: Structured Extractions from Templatic Documents

Summary: Glean extracts structured data from templatic documents and generalizes to unseen layouts. Data-management focus: high-quality ground truth, efficient training-data generation, and rapid tooling; yields ~5 F1-point gain on the same model. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 12612
Venue: VLDB
Year: 2021
Pagerank: 4.3690661e-05
Overall Rank: 9,253 | 35.63%
DOI: 10.14778/3447689.3447703

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
10,126	Visual Template Inference for Data Extraction from Documents	2026	SIGMOD	4.1945683e-05

Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
254	Snorkel: Rapid Training Data Creation with Weak Supervision	2018	VLDB	0.00030540555
1,277	The Data Civilizer System	2017	CIDR	0.00012879695
1,317	Harvesting Relational Tables from Lists on the Web	2009	VLDB	0.00012625853
3,303	Fonduer: Knowledge Base Construction from Richly Formatted Data	2018	SIGMOD	7.2487486e-05
5,684	Dagger: A Data (not code) Debugger	2020	CIDR	5.3720749e-05
7,397	A Probabilistic Approach for Automatically Filling Form-Based Web Interfaces	2011	VLDB	4.7417648e-05
8,461	Visual Segmentation for Information Extraction from Heterogeneous Visually Rich Documents	2019	SIGMOD	4.5061205e-05

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