LieCraft: A Multi-Agent Framework for Evaluating Deceptive Capabilities in Language Models
Large Language Models (LLMs) exhibit impressive general-purpose capabilities but also introduce serious safety risks, particularly the potential for deception as models acquire increased agency and human oversight diminishes. In this work, we present LieCraft: a novel evaluation framework and sandbox for measuring LLM deception that addresses key limitations of prior game-based evaluations. At its core, LieCraft is a novel multiplayer hidden-role game in which players select an ethical alignment and execute strategies over a long time-horizon to accomplish missions. Cooperators work together to solve event challenges and expose bad actors, while Defectors evade suspicion while secretly sa...
| Authors | Matthew Lyle Olson, Neale Ratzlaff, Musashi Hinck et al. |
|---|---|
| Primary category | cs.AI |
| Published | 6 March 2026 |
| Last updated at source | 6 March 2026 |
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