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20242026
most citedAdvancing Science- and Evidence-based AI Policy

20 citations · 26 across the 8 of their papers we have counts for

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Showing 2025Show all

6 papers · 1 filter

cs.AI2025

Comparing AI Agents to Cybersecurity Professionals in Real-World Penetration Testing

Justin W. Lin, Eliot Krzysztof Jones, Donovan Julian Jasper +10

We present the first comprehensive evaluation of AI agents against human cybersecurity professionals in a live enterprise environment. We evaluate ten cybersecurity professionals a…

cs.CY2025

Audits Under Resource, Data, and Access Constraints: Scaling Laws For Less Discriminatory Alternatives

Sarah H. Cen, Salil Goyal, Zaynah Javed +3

AI audits play a critical role in AI accountability and safety. One branch of the law for which AI audits are particularly salient is anti-discrimination law. Several areas of anti…

cs.CY2025★ 20 cited

Advancing Science- and Evidence-based AI Policy

Rishi Bommasani, Sanjeev Arora, Jennifer Chayes +17

AI policy should advance AI innovation by ensuring that its potential benefits are responsibly realized and widely shared. To achieve this, AI policymaking should place a premium o…

cs.CY2025

The California Report on Frontier AI Policy

Rishi Bommasani, Scott R. Singer, Ruth E. Appel +20

The innovations emerging at the frontier of artificial intelligence (AI) are poised to create historic opportunities for humanity but also raise complex policy challenges. Continue…

cs.CR2025

BountyBench: Dollar Impact of AI Agent Attackers and Defenders on Real-World Cybersecurity Systems

Andy K. Zhang, Joey Ji, Celeste Menders +31

AI agents have the potential to significantly alter the cybersecurity landscape. Here, we introduce the first framework to capture offensive and defensive cyber-capabilities in evo…

cs.CL2025★ 2 cited

Extracting memorized pieces of (copyrighted) books from open-weight language models

A. Feder Cooper, Mark A. Lemley, Allison Casasola +6

Plaintiffs and defendants in copyright lawsuits over generative AI often make sweeping, opposing claims about the extent to which large language models (LLMs) memorize protected ex…