Formal Methods Meet LLMs: Auditing, Monitoring, and Intervention for Compliance
arXiv:2603.26983v1 Announce Type: new Abstract: Art. 50 II of the EU Artificial Intelligence Act mandates dual transparency for AI-generated content: outputs must be labeled in
arXiv:2603.19715v1 Announce Type: new Abstract: Formal verification via interactive theorem proving is increasingly used to ensure the correctness of critical systems, yet
arXiv:2604.21103v1 Announce Type: new Abstract: Governments are increasingly interested in using AI to make administrative decisions cheaper, more scalable, and more consistent.
arXiv:2605.07002v1 Announce Type: new Abstract: A major bottleneck in characterizing the failure modes of generative AI systems is the cost and time of annotation and evaluation.
arXiv:2604.26233v1 Announce Type: new Abstract: As Large Language Models (LLMs) are proposed as legal decision assistants, and even first-instance decision-makers, across a range
arXiv:2603.19828v1 Announce Type: new Abstract: Autoformalization aims to translate natural-language mathematics into compilable, machine-checkable statements. However, semantic
arXiv:2603.26944v1 Announce Type: new Abstract: Predictive modeling on sequential event data is critical for fraud detection and healthcare monitoring. Existing data-driven
arXiv:2608.23817v1 Announce Type: new Abstract: SHAP and LIME are now standard tools for interpreting black-box predictions, yet their outputs can vary substantially when the
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