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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
6131
Venue
SIGMOD
Year
2021
Pagerank
6.809685e-05
Overall Rank
4,240 | 70.92%
DOI
10.1145/3448016.3452788
Incoming Non-self Citations Over Time
BibTeX Citation
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@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}
}
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