MLINSPECT: A Data Distribution Debugger for Machine Learning Pipelines

Summary: MLINSPECT: a data distribution debugger for ML pipelines, using lightweight lineage-based inspection to pinpoint distribution bugs in preprocessing. It operates on declarative estimator/transformer abstractions, handles relational and matrix data, and requires no manual code instrumentation. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 6041
Venue: SIGMOD
Year: 2021
Pagerank: 5.9615384e-05
Overall Rank: 4,734 | 67.07%
DOI: 10.1145/3448016.3452759

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 9 of 9 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
1,867	Interpretable Data-Based Explanations for Fairness Debugging	2022	SIGMOD	0.00010272055
6,643	Query Refinement for Diversity Constraint Satisfaction	2024	VLDB	4.9786132e-05
8,114	mlwhatif: What If You Could Stop Re-Implementing Your Machine Learning Pipeline Analyses Over and Over?	2023	VLDB	4.5823351e-05
8,182	SHiFT: An Efficient, Flexible Search Engine for Transfer Learning	2023	VLDB	4.5659133e-05
8,257	Automating and Optimizing Data-Centric What-If Analyses on Native Machine Learning Pipelines	2023	SIGMOD	4.5487511e-05
9,118	Towards Observability for Production Machine Learning Pipelines	2022	VLDB	4.3928288e-05
10,277	Efficient Query Repair for Aggregate Constraints	2026	VLDB	4.1945683e-05
10,820	APEX-DAG: Library and Language independent Pipeline EXtraction	2025	VLDB	4.1945683e-05
11,313	Towards Observability for Machine Learning Pipelines	2022	CIDR	4.1945683e-05

Outgoing Citations (Sorted by Pagerank)

Showing 2 of 2 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
1,404	Responsible Data Management	2020	VLDB	0.00012174977
6,291	Lightweight Inspection of Data Preprocessing in Native Machine Learning Pipelines	2021	CIDR	5.1269764e-05

Semantically Similar Papers

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4,003	Data Platform for Machine Learning	2019	SIGMOD	6.54347e-05
9,306	Debugging Large-Scale Data Science Pipelines using Dagger	2020	VLDB	4.3572942e-05
10,816	mlidea: Interactively Improving ML Data Preparation Code via "Shadow Pipelines"	2025	VLDB	4.1945683e-05
10,820	APEX-DAG: Library and Language independent Pipeline EXtraction	2025	VLDB	4.1945683e-05
8,257	Automating and Optimizing Data-Centric What-If Analyses on Native Machine Learning Pipelines	2023	SIGMOD	4.5487511e-05
9,118	Towards Observability for Production Machine Learning Pipelines	2022	VLDB	4.3928288e-05
8,114	mlwhatif: What If You Could Stop Re-Implementing Your Machine Learning Pipeline Analyses Over and Over?	2023	VLDB	4.5823351e-05
11,313	Towards Observability for Machine Learning Pipelines	2022	CIDR	4.1945683e-05
11,147	Reconstructing and Querying ML Pipeline Intermediates	2023	CIDR	4.1945683e-05
6,291	Lightweight Inspection of Data Preprocessing in Native Machine Learning Pipelines	2021	CIDR	5.1269764e-05