44 citations · 62 across the 6 of their papers we have counts for
3 papers · 1 filter
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…