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LIMA: Fine-grained Lineage Tracing and Reuse in Machine Learning Systems

Summary: Fine-grained lineage tracing and reuse in ML systems (LIMA) to break coarse, black-box limits. Multi-level traces, loop/function dedup, and cross-hierarchy reuse enable low-overhead provenance with versioning, compatible with task parallelism and operator fusion, delivering up to 12.4x speedups. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
h0a8564e76e97bc86
Venue
SIGMOD
Year
2021
Pagerank
6.6569314e-05
Overall Rank
4,334 | 70.87%
DOI
10.1145/3448016.3452788

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{phani_sigmod21,
        title = {{LIMA: Fine-grained Lineage Tracing and Reuse in Machine Learning Systems}},
        author = {Phani, Arnab and Rath, Benjamin and Boehm, Matthias},
        series = {{SIGMOD} '21},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3448016.3452788},
        url = {https://dl.acm.org/doi/10.1145/3448016.3452788},
        year = {2021}
}

Incoming Citations (Sorted by Pagerank)

Showing 16 of 16 citing papers.

Rank Citing Paper Year Venue Pagerank
5,572 Saga: A Scalable Framework for Optimizing Data Cleaning Pipelines for Machine Learning Applications 2023 SIGMOD 6.0802555e-05
6,662 UPLIFT: Parallelization Strategies for Feature Transformations in Machine Learning Workloads 2022 VLDB 5.7171651e-05
6,878 DAPHNE: An Open and Extensible System Infrastructure for Integrated Data Analysis Pipelines 2022 CIDR 5.657878e-05
7,809 Nautilus: An Optimized System for Deep Transfer Learning over Evolving Training Datasets 2022 SIGMOD 5.4490255e-05
7,839 ExDRa: Exploratory Data Science on Federated Raw Data 2021 SIGMOD 5.4432099e-05
8,076 Provenance-Enabled Explainable AI 2024 SIGMOD 5.3942942e-05
10,043 The Image Calculator: 10x Faster Image-AI Inference by Replacing JPEG with Self-designing Storage Format 2024 SIGMOD 5.0921006e-05
10,279 ElasticNotebook: Enabling Live Migration for Computational Notebooks 2024 VLDB 5.0455234e-05
10,722 CAPS: Cost-Aware ML Pipeline Selection 2026 VLDB 4.9793485e-05
10,898 stratum: A System Infrastructure for Massive Agent-Centric ML Workloads 2026 VLDB 4.9793485e-05
10,945 Morphing-based Compression for Data-centric ML Pipelines 2026 VLDB 4.9793485e-05
11,135 Unified Lineage System: Tracking Data Provenance at Scale 2025 SIGMOD 4.9793485e-05
11,176 Alsatian: Optimizing Model Search for Deep Transfer Learning 2025 SIGMOD 4.9793485e-05
11,284 CatDB: Data-catalog-guided, LLM-based Generation of Data-centric ML Pipelines 2025 VLDB 4.9793485e-05
11,426 ML-Asset Management: Curation, Discovery, and Utilization 2025 VLDB 4.9793485e-05
11,846 Redundancy Elimination in Distributed Matrix Computation 2022 SIGMOD 4.9793485e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 4 of 54 cited papers.

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

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