AI RESEARCH
Verifying Machine Learning Interpretability Requirements through Provenance
arXiv CS.LG
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ArXi:2604.21599v1 Announce Type: cross Machine Learning (ML) Engineering is a growing field that necessitates an increase in the rigor of ML development. It draws many ideas from software engineering and specifically, from requirements engineering. Existing literature on ML Engineering defines quality models and Non-Functional Requirements (NFRs) specific to ML, in particular interpretability being one such NFR. However, a major challenge occurs in verifying ML NFRs, including interpretability.