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We introduce clever, the first curated benchmark for evaluating the generation of specifications and formally verified code in lean While, as we mentioned earlier, there can be thorny “clever hans” issues about humans prompting llms, an automated verifier mechanically backprompting the llm doesn’t suffer from these The benchmark comprises of 161 programming problems

It requires full formal specs and proofs One common approach is training models to refuse unsafe queries, but this strategy can be vulnerable to clever prompts, often referred to as jailbreak attacks, which can trick the ai. Our analysis yields a novel robustness metric called clever, which is short for cross lipschitz extreme value for network robustness

Building on recent explainable ai techniques, this article highlights the pervasiveness of clever hans effects in unsupervised learning and the substantial risks.

Leaving the barn door open for clever hans

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