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Witan: Unsupervised Labelling Function Generation for Assisted Data Programming

Summary: Witan generates labelling functions without supervision, enabling unsupervised data programming. It supports interactive modes from exploration to class definition, delivering accurate binary and multiclass labeling with efficient weak supervision. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12726
Venue
VLDB
Year
2022
Pagerank
4.7762276e-05
Overall Rank
7,288 | 49.30%
DOI
10.14778/3551793.3551797

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
10,533 WeShap: Weak Supervision Source Evaluation with Shapley Values 2025 VLDB 4.1945683e-05
11,205 Steered Training Data Generation for Learned Semantic Type Detection 2023 SIGMOD 4.1945683e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 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
1,215 Snuba: Automating Weak Supervision to Label Training Data 2019 VLDB 0.0001323375
5,347 Adaptive Rule Discovery for Labeling Text Data 2021 SIGMOD 5.5560452e-05
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