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The post explores the reliability of jailbreak methods for LLMs, using a case study with Scots Gaelic prompts on GPT-4. It critiques existing benchmarks and introduces StrongREJECT, a new evaluation standard with a diverse dataset of forbidden prompts and advanced automated evaluators. The study finds that many reported jailbreak successes are less effective than claimed, highlighting a crucial trade-off between model willingness and capability. StrongREJECT aligns more closely with human judgments, offering a robust tool for assessing AI safety measures.

How to Evaluate Jailbreak Methods: A Case Study with the StrongREJECT Benchmark

Jailbreaks Are Less Effective Than Reported