BeHonest: Benchmarking Honesty in Large Language Models

Understand

Previous works on Large Language Models (LLMs) have mainly focused on evaluating their helpfulness or harmlessness.

• However, honesty, another crucial alignment criterion, has received relatively less attention.
• Dishonest behaviors in LLMs, such as spreading misinformation and defrauding users, present severe risks that intensify as these models approach superintelligent levels.
• Enhancing honesty in LLMs addresses critical limitations and helps uncover latent capabilities that are not readily expressed.