mlsanityData to 14 Oct 2026

Assessing High-Risk AI Systems under the EU AI Act: From Legal Requirements to Technical Verification

arXiv 2512.13907 ↗First posted 15 Dec 2025cs.CY cs.AIcited by 4

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Abstract (arXiv)

The implementation of the AI Act requires practical mechanisms to verify compliance with legal obligations, yet concrete and operational mappings from high-level requirements to verifiable assessment activities remain limited, contributing to uneven readiness across Member States. This paper presents a structured mapping that translates high-level AI Act requirements into concrete, implementable verification activities applicable across the AI lifecycle. The mapping is derived through a systematic process in which legal requirements are decomposed into operational sub-requirements and grounded in authoritative standards and recognised practices. From this basis, verification activities are identified and characterised along two dimensions: the type of verification performed and the lifecycle target to which it applies. By making explicit the link between regulatory intent and technical and organisational assurance practices, the proposed mapping reduces interpretive uncertainty and provides a reusable reference for consistent, technology-agnostic compliance verification under the AI Act.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 6 of its 41 references that are in the map. First posted on arXiv 15 Dec 2025.

Builds on

6 of 41 references.

References · 6

  1. 2020Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claimscited by 165
  2. 2019Efficient Saliency Maps for Explainable AIcited by 30
  3. 2017Chaos Engineeringcited by 19
  4. 2023Generative Models as a Complex Systems Science: How can we make sense of large language model behavior?cited by 19
  5. 2021An Artificial Intelligence Life Cycle: From Conception to Productioncited by 11
  6. 2025Mapping the Regulatory Learning Space for the EU AI Actcited by 3

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 4.

4 papers.