2 citations · 2 across the 6 of their papers we have counts for
6 papers
Can AI agents conduct open-ended AI research? Early evidence from two case studies
Peter Kirgis, Sayash Kapoor, Andrew Schwartz +21
Forecasts of explosive AI progress hinge on AI agents automating AI research. But evidence on whether agents can carry out open-ended AI research is thin. Current evaluations eithe…
Are LLMs Bad at Moral Reasoning?
Menghang Zhu, Seth Lazar
For highly capable AI systems to operate safely in dynamic, open-ended environments, they must be able to identify, understand, and respond to moral reasons for action, and constra…
NoRA: Evaluating Grounded Reasonableness in Visual First-person Normative Action Reasoning
Sichao Li, Sai Ma, Daniel Kilov +3
LLMs and agentic systems are increasingly deployed in social environments, making normative competence critical for safe and appropriate behavior. However, existing approaches eith…
Open-World Evaluations for Measuring Frontier AI Capabilities
Sayash Kapoor, Peter Kirgis, Andrew Schwartz +15
Benchmark-based evaluation remains important for tracking frontier AI progress. But it can both overstate and understate deployed capability because it privileges tasks that can be…
Legal Alignment for Safe and Ethical AI
Noam Kolt, Nicholas Caputo, Jack Boeglin +14
Alignment of artificial intelligence (AI) encompasses the normative problem of specifying how AI systems should act and the technical problem of ensuring AI systems comply with tho…
Infrastructure for AI Agents
Alan Chan, Kevin Wei, Sihao Huang +5
AI agents plan and execute interactions in open-ended environments. For example, OpenAI's Operator can use a web browser to do product comparisons and buy online goods. Much resear…