MisDetect: Iterative Mislabel Detection using Early Loss

Summary: MisDetect identifies label noise during training by iteratively flagging high early-loss examples, applying influence-based verification, and auto-stopping when early-loss signals fade. For ambiguous instances it generates pseudo-labels to train a binary verifier; outperforms 10 baselines on 15 datasets. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: h13ce7a8fc1ebeb28
Venue: VLDB
Year: 2024
Pagerank: 5.4772833e-05
Overall Rank: 7,648 | 48.58%
DOI: 10.14778/3648160.3648161

Incoming Non-self Citations Over Time

Authors

1. Yuhao Deng (Beijing Institute of Technology)
2. Chengliang Chai (Beijing Institute of Technology)
3. Lei Cao (Massachusetts Institute of Technology; University of Arizona)
4. Nan Tang (Hong Kong University of Science and Technology)
5. Jiayi Wang (Tsinghua University)
6. Ju Fan (Renmin University of China)
7. Ye Yuan (Beijing Institute of Technology)
8. Guoren Wang (Beijing Institute of Technology)

BibTeX Citation

@article{deng_vldb24,
        title = {{MisDetect: Iterative Mislabel Detection using Early Loss}},
        author = {Deng, Yuhao and Chai, Chengliang and Cao, Lei and Tang, Nan and Wang, Jiayi and Fan, Ju and Yuan, Ye and Wang, Guoren},
        journal = {PVLDB},
        series = {{VLDB} '24},
        volume = {17},
        number = {6},
        pages = {1159--1172},
        doi = {10.14778/3648160.3648161},
        url = {https://doi.org/10.14778/3648160.3648161},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 5 of 5 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
4,409	LakeBench: A Benchmark for Discovering Joinable and Unionable Tables in Data Lakes	2024	VLDB	6.6120807e-05
7,924	Outlier Summarization via Human Interpretable Rules	2024	VLDB	5.425954e-05
11,001	ARGO: An Interactive Data Governance System for Machine Learning via Hierarchical Reinforcement Learning	2026	VLDB	4.9793485e-05
11,101	Agree to Disagree: Robust Anomaly Detection with Noisy Labels	2025	SIGMOD	4.9793485e-05
11,213	Two Birds with One Stone: Efficient Deep Learning over Mislabeled Data through Subset Selection	2025	SIGMOD	4.9793485e-05

Outgoing Citations (Sorted by Pagerank)

Showing 13 of 13 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
104	HoloClean: Holistic Data Repairs with Probabilistic Inference	2017	VLDB	0.00033690989
883	HoloDetect: Few-Shot Learning for Error Detection	2019	SIGMOD	0.00013268059
1,941	Interpretable Data-Based Explanations for Fairness Debugging	2022	SIGMOD	9.3297671e-05
2,598	Complaint-driven Training Data Debugging for Query 2.0	2020	SIGMOD	8.2385793e-05
3,307	Cleaning Crowdsourced Labels Using Oracles for Statistical Classification	2019	VLDB	7.4414303e-05
3,941	GoodCore: Data-effective and Data-efficient Machine Learning through Coreset Selection over Incomplete Data	2023	SIGMOD	6.9138042e-05
4,623	Cost-Effective Crowdsourced Entity Resolution: A Partial-Order Approach	2016	SIGMOD	6.4978811e-05
4,867	Selective Data Acquisition in the Wild for Model Charging	2022	VLDB	6.3749346e-05
5,061	CDB: A Crowd-Powered Database System	2018	VLDB	6.2912543e-05
7,042	Human-in-the-loop Outlier Detection	2020	SIGMOD	5.6142998e-05
7,201	Coresets over Multiple Tables for Feature-rich and Data-efficient Machine Learning	2023	VLDB	5.5871656e-05
7,876	CHEF: A Cheap and Fast Pipeline for Iteratively Cleaning Label Uncertainties	2021	VLDB	5.4348457e-05
9,470	VisClean: Interactive Cleaning for Progressive Visualization	2020	VLDB	5.1714419e-05

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