The MASK benchmark introduces a rigorous framework to evaluate honesty in large language models, separate from accuracy.

• Addresses the critical gap between model capabilities and trustworthiness
• Provides a standardized way to detect deceptive behaviors in AI systems
• Enables developers to create more transparent and reliable AI assistants
• Establishes metrics to assess if models are truthful under various pressures

As AI systems become more powerful and autonomous, ensuring they provide honest information is vital for security and safe deployment. This benchmark provides the tools needed to identify and mitigate potentially harmful deception in AI systems.

The MASK Benchmark: Disentangling Honesty From Accuracy in AI Systems