TAI Scan Tool: A RAG-Based Tool With Minimalistic Input for Trustworthy AI Self-Assessment
Not on the map. Why?
Abstract (arXiv)
This paper introduces the TAI Scan Tool, a RAG-based TAI self-assessment tool with minimalistic input. The current version of the tool supports the legal TAI assessment, with a particular emphasis on facilitating compliance with the AI Act. It involves a two-step approach with a pre-screening and an assessment phase. The assessment output of the system includes insight regarding the risk-level of the AI system according to the AI Act, while at the same time retrieving relevant articles to aid with compliance and notify on their obligations. Our qualitative evaluation using use-case scenarios yields promising results, correctly predicting risk levels while retrieving relevant articles across three distinct semantic groups. Furthermore, interpretation of results shows that the tool's reasoning relies on comparison with the setting of high-risk systems, a behaviour attributed to their deployment requiring careful consideration, and therefore frequently presented within the AI Act.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 6 of its 22 references that are in the map. First posted on arXiv 23 Jul 2025.
Builds on
6 of 22 references.
References · 6
- 2023Retrieval-Augmented Generation for Large Language Models: A Surveycited by 2,212
- 2023A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questionscited by 1,601
- 2020MPNet: Masked and Permuted Pre-training for Language Understandingcited by 981
- 2021Trustworthy AI: From Principles to Practicescited by 207
- 2024CBR-RAG: Case-Based Reasoning for Retrieval Augmented Generation in LLMs for Legal Question Answeringcited by 72
- 2024HyPA-RAG: A Hybrid Parameter Adaptive Retrieval-Augmented Generation System for AI Legal and Policy Applicationscited by 22
Built on by
Citing papers per year: 2025: 1.
1 paper.
Similar, not cited
Close in wording, no citation either way
- 2025Let's have a chat with the EU AI Act
- 2026AGO AI Quality Gate: Evidence-First Release Decisions for Retrieval-Augmented Generation
- 2025Gobernanza y trazabilidad "a prueba de AI Act" para casos de uso legales: un marco t'ecnico-jur'idico, m'etricas forenses y evidencias auditables
- 2026AI Act Evaluation Benchmark: An Open, Transparent, and Reproducible Evaluation Dataset for NLP and RAG Systems
- 2026Benchmarking Legal RAG: The Promise and Limits of AI Statutory Surveys
- 2025Towards a rigorous evaluation of RAG systems: the challenge of due diligence
- 2026LegalHalluLens: Typed Hallucination Auditing and Calibrated Multi-Agent Debate for Trustworthy Legal AI
- 2025AI Agents-as-Judge: Automated Assessment of Accuracy, Consistency, Completeness and Clarity for Enterprise Documents