most citedComputational Compliance for AI Regulation: Blueprint for a New Research Domain

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.AI20261 cited

Computational Compliance for AI Regulation: Blueprint for a New Research Domain

Bill Marino, Nicholas D. Lane

The era of AI regulation (AIR) is upon us. But AI systems, we argue, will not be able to comply with these regulations at the necessary speed and scale by continuing to rely on tra…

cs.AI2025

AIReg-Bench: Benchmarking Language Models That Assess AI Regulation Compliance

Bill Marino, Rosco Hunter, Christoph Schnabl +9

As governments move to regulate AI, there is growing interest in using Large Language Models (LLMs) to assess whether or not an AI system complies with a given AI Regulation (AIR).…

cs.AI2025

Attestable Audits: Verifiable AI Safety Benchmarks Using Trusted Execution Environments

Christoph Schnabl, Daniel Hugenroth, Bill Marino +1

Benchmarks are important measures to evaluate safety and compliance of AI models at scale. However, they typically do not offer verifiable results and lack confidentiality for mode…

cs.CY2025

Red Teaming AI Policy: A Taxonomy of Avoision and the EU AI Act

Rui-Jie Yew, Bill Marino, Suresh Venkatasubramanian

The shape of AI regulation is beginning to emerge, most prominently through the EU AI Act (the "AIA"). By 2027, the AIA will be in full effect, and firms are starting to adjust the…

cs.LG2025

Position: Bridge the Gaps between Machine Unlearning and AI Regulation

Bill Marino, Meghdad Kurmanji, Nicholas D. Lane

The ''right to be forgotten'' and the data privacy laws that encode it have motivated machine unlearning since its earliest days. Now, some argue that an inbound wave of artificial…