2 citations · 5 across the 9 of their papers we have counts for
13 papers
Articulation Upper Bounds for Language Models
Alexander Spangher, Daniel E. Ho, Diyi Yang +2
Language captures only a subset of the perceptions, intuitions and intents that form meaning between speakers. What, then, are the limits of language? We take steps towards measuri…
Verifiable, Articulable, and Tacit Components of Preference
Alexander Spangher, Sheldon S. Huang, Sheldon Huang +5
What makes a short story gripping; a news article newsworthy; or a math proof elegant? These constructs resist articulation or verification; their meaning is at least partially tac…
MobileCybench: Evaluating Agent Vulnerability Discovery via Executable Probes
Andy K. Zhang, Ava Huang, Joey Ji +21
AI agents now report vulnerabilities faster than maintainers can review them. Reports often depend on security properties specific to the application, and require considerable huma…
API Benchmark Scores Do Not Reliably Transfer to Chatbot Interfaces
Jennifer Wang, Joachim Baumann, Daniel E. Ho +1
Benchmark scores are a central currency in model releases: they inform purchasing decisions, shape public trust, and influence policy. Yet, a key assumption underlying benchmark sc…
What AI Benchmarks Actually Measure: Adapting Convergent and Discriminant Validity to Interrogate Fifty-Six AI Benchmarks
Meera Desai, Sang T. Truong, Hanna Wallach +8
Benchmarks play a central role in the development and governance of models, yet it is often unclear whether they actually measure the concepts they purport to measure (e.g., reason…
Extractable Memorization From First Principles
A. Feder Cooper, Marika Swanberg, Jamie Hayes +6
Recent work on extractable memorization in language models suffers from two contrasting validity problems. Some studies overstate extraction, for example, by using sequences too sh…
Estimating near-verbatim extraction risk in language models with decoding-constrained beam search
A. Feder Cooper, Mark A. Lemley, Christopher De Sa +6
Recent work shows that standard greedy-decoding extraction methods for quantifying memorization in LLMs miss how extraction risk varies across sequences. Probabilistic extraction -…
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…
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…
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…
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…
Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy and Research
A. Feder Cooper, Christopher A. Choquette-Choo, Miranda Bogen +34
"Machine unlearning" is a popular proposed solution for mitigating the existence of content in an AI model that is problematic for legal or moral reasons, including privacy, copyri…
Cybench: A Framework for Evaluating Cybersecurity Capabilities and Risks of Language Models
Andy K. Zhang, Neil Perry, Riya Dulepet +24
Language Model (LM) agents for cybersecurity that are capable of autonomously identifying vulnerabilities and executing exploits have potential to cause real-world impact. Policyma…