5 citations · 5 across the 3 of their papers we have counts for
4 papers
Who Else Is In? Multi-Agent Collusion Initation Via Strategic Vagueness
Pramod Kaushik, Sarath Sivaprasad, Laura Ferrarotti +4
Multi agent LLM systems raise the risk of collusion among agents pursuing objectives hidden from their overseers. When potential partners identities are unknown, collusion first re…
Do LLMs Take Care of Their Own? Similarity Signals Can Induce Cooperation
Akash Kundu, Emanuel Tewolde, Ratip Emin Berker +2
As LLM-based agents with user-instructed goals are becoming widely deployed, they increasingly encounter each other in strategic interactions, and face challenges of finding mutual…
SKATE, a Scalable Tournament Eval: Weaker LLMs differentiate between stronger ones using verifiable challenges
Dewi S. W. Gould, Bruno Mlodozeniec, Samuel F. Brown
Evaluating the capabilities and risks of foundation models is paramount, yet current methods demand extensive domain expertise, hindering their scalability as these models rapidly…
AI Sandbagging: Language Models can Strategically Underperform on Evaluations
Teun van der Weij, Felix Hofstätter, Ollie Jaffe +2
Trustworthy capability evaluations are crucial for ensuring the safety of AI systems, and are becoming a key component of AI regulation. However, the developers of an AI system, or…