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We introduce clever, the first curated benchmark for evaluating the generation of specifications and formally verified code in lean Modeling the progression of such expertize in humans. The benchmark comprises of 161 programming problems

Biblical Tents

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 Our analysis yields a novel robustness metric called clever, which is short for cross lipschitz extreme value for network robustness It requires full formal specs and proofs

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A fundamental limitation of current ai agents is their inability to learn complex skills on the fly at test time, often behaving like “clever but clueless interns” in novel environments

Membership inference and memorization is a key challenge with diffusion models Mitigating such vulnerabilities is hence an important topic The idea of using an ensemble of model is clever.