The Archive

EU AI Act Q&A benchmark evaluates LLM assistants on regulatory compliance tasks with 110 expert-curated questions.

Fairness evaluation framework for compact decision models in high-stakes recruitment under EU AI Act requirements.

ComplianceAtlas automates EU AI Act compliance auditing for high-risk systems using agentic taxonomy-driven gap analysis and remediation.

VERA dashboard operationalizes EU AI Act compliance for LLM deployments, mapping 18 technical requirements to measurable benchmarks for non-engineer stakeholders.

Systemic Risk Index organizes 19 benchmarks under EU GPAI Code of Practice categories to transparently evaluate AI safety across CBRN, cyber, manipulation, and control loss.

Survey of LLM security, privacy, and reliability risks in mobility/automotive sector, covering 1.5B vehicles and EU AI Act compliance.

Framework translating EU AI Act technical requirements into 43 machine-checkable compliance criteria for generative AI systems, addressing seven gaps in original regulation.

Commentary on translating AI principles to protocols and standards (EU AI Act, NIST AI RMF, ISO 42001) as institutional repair mechanisms.

OpenAI outlines safety, security, and transparency practices aligned with EU AI Act compliance and responsible governance.

Cohere signs EU AI Content Transparency Code, demonstrating early compliance with EU AI Act requirements.

Empirical evaluation finds LLM watermarking methods fail forensic standards required by EU AI Act and California SB 942.

Overview of AI risk assessment and management methodologies across regulatory frameworks including EU AI Act with techniques for technical and ethical risks.

Large language models now produce legal text of at least median quality, yet no existing benchmark can evaluate whether they perform doctrinal legal reasoning, which forms the interpretive core of legal work, rather than the ancillary, paralegal tasks that most current legal-AI evaluations measure. This measurement gap is not only methodological but legal: the EU AI Act makes "appropriate accuracy" a binding requirement for high-risk AI used in the judicial domain, yet that requirement cannot acquire operational content without the very doctrinal-reasoning benchmark the field lacks.

As AI models grow in complexity and regulatory scrutiny intensifies under frameworks including California’s AB-2013 and the EU AI Act, software teams... As AI models grow in complexity and regulatory scrutiny intensifies under frameworks including California’s AB-2013 and the EU AI Act, software teams face a challenge beyond delivering great code: They need to produce comprehensive, auditable model documentation before the models are released. Model cards describe how a model works, its intended use and license, training data, performance… Source

FinGround detects computational and citation hallucinations in financial LLM systems via atomic claim verification before EU AI Act enforcement (Aug 2026).

Framework quantifies acceptable risk thresholds for high-risk AI systems under EU AI Act, NIST, and Council of Europe regulations.

OpenAI primer on EU AI Act compliance: deadlines, prohibited/high-risk use cases for AI providers and deployers.