44 citations · 62 across the 6 of their papers we have counts for
6 papers
Prioritization of Risks from Artificial Intelligence: A Delphi Study of 272 International Experts
Alexander K. Saeri, Jess Graham, Michael Noetel +185
Artificial intelligence poses many risks, ranging from familiar present-day harms to unprecedented and potentially catastrophic ones. Effective risk management requires prioritizat…
OpenSanctions Pairs: Large-Scale Entity Matching with LLMs
Chandler Smith, Magnus Sesodia, Friedrich Lindenberg +1
We release OpenSanctions Pairs, the first large-scale public benchmark for entity matching on sanctions and OSINT data. The dataset includes 755,540 expert-labeled pairs over 1 mil…
Multi-Agent Risks from Advanced AI
Lewis Hammond, Alan Chan, Jesse Clifton +41
The rapid development of advanced AI agents and the imminent deployment of many instances of these agents will give rise to multi-agent systems of unprecedented complexity. These s…
MALT: Improving Reasoning with Multi-Agent LLM Training
Sumeet Ramesh Motwani, Chandler Smith, Rocktim Jyoti Das +6
Large Language Models (LLMs) often produce answers with a single chain-of-thought, which restricts their ability to explore reasoning paths or self-correct flawed outputs in comple…
BetterBench: Assessing AI Benchmarks, Uncovering Issues, and Establishing Best Practices
Anka Reuel, Amelia Hardy, Chandler Smith +3
AI models are increasingly prevalent in high-stakes environments, necessitating thorough assessment of their capabilities and risks. Benchmarks are popular for measuring these attr…
Escalation Risks from Language Models in Military and Diplomatic Decision-Making
Juan-Pablo Rivera, Gabriel Mukobi, Anka Reuel +3
Governments are increasingly considering integrating autonomous AI agents in high-stakes military and foreign-policy decision-making, especially with the emergence of advanced gene…