This paper reviews 24 EU AI regulatory documents from 2024-2025 to clarify definitions and provisions related to security, privacy, and agentic AI. It aims to resolve ambiguities and align regulatory obligations with the evolving capabilities of AI, particularly autonomous agents.

This paper introduces UnSLU-BENCH, the first benchmark for machine unlearning in spoken language understanding (SLU), evaluating eight unlearning techniques across various datasets and models. It also proposes the Global Unlearning Metric (GUM) to comprehensively assess efficacy, utility, and efficiency in unlearning requests, particularly concerning speaker-specific data for privacy.