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CHEF: A Cheap and Fast Pipeline for Iteratively Cleaning Label Uncertainties

Summary: CHEF cuts label-cleaning costs under weak supervision by prioritizing influential samples and feeding cleaned labels. It adds Increm-INFL and DeltaGrad-L, incremental selection and model updates, plus compact small-batch iteration enabling early stopping. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12605
Venue
VLDB
Year
2021
Pagerank
5.5277527e-05
Overall Rank
7,868 | 46.02%
DOI
10.14778/3476249.3476290

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{wu_vldb21,
        title = {{CHEF: A Cheap and Fast Pipeline for Iteratively Cleaning Label Uncertainties}},
        author = {Wu, Yinjun and Weimer, James and Davidson, Susan B.},
        journal = {PVLDB},
        series = {{VLDB} '21},
        volume = {14},
        number = {11},
        pages = {2410--2418},
        doi = {10.14778/3476249.3476290},
        url = {https://doi.org/10.14778/3476249.3476290},
        year = {2021}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
10,324 Outliers: The Good, the Bad and the Ugly 2026 SIGMOD 5.093636e-05
11,211 MisDetect: Iterative Mislabel Detection using Early Loss 2024 VLDB 5.093636e-05
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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.

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