BeHonest

Overview

BeHonest is a benchmarking framework that evaluates how honestly large language models express uncertainty or admit ignorance. It provides a standardized leaderboard where models are tested on their tendency to give correct answers versus making up information.

Best for

Best for
Researchers and developers who need to evaluate or improve the truthfulness of LLMs.

Use cases

• Assessing a model's calibration and truthfulness before deployment
• Comparing different LLMs on honesty metrics for research or selection
• Identifying specific failure modes where models fabricate answers

Notes

BeHonest is a benchmarking framework that evaluates how honestly large language models express uncertainty or admit ignorance. It provides a standardized leaderboard where models are tested on their tendency to give correct answers versus making up information.

Use cases

• Assessing a model’s calibration and truthfulness before deployment
• Comparing different LLMs on honesty metrics for research or selection
• Identifying specific failure modes where models fabricate answers

Pros

• Offers a clear, reproducible benchmark for a critical safety dimension
• Public leaderboard enables direct model comparison
• Focuses on an under-tested aspect of LLM behavior

Cons

• Limited to the specific honesty scenarios defined by the benchmark
• Does not measure other important qualities like helpfulness or safety
• Leaderboard results may not generalize to all real-world use cases

Indexed from awesome-llm and enriched against its public facts.