Clever juice names, We tested this setup on a subset of the failed instances in the one-shot natural language prompt configuration using GPT-4, given its larger context window. 579 In this paper, we have proposed a novel counter- factual framework CLEVER for debiasing fact- checking models. No few-shot method solves all stages, making it a strong testbed for synthesis and formal reasoning. 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. Mitigating such vulnerabilities is hence an important topic. We introduce CLEVER, the first curated benchmark for evaluating the generation of specifications and formally verified code in Lean. Feb 15, 2018 · Our analysis yields a novel robustness metric called CLEVER, which is short for Cross Lipschitz Extreme Value for nEtwork Robustness. Sep 25, 2024 · In this paper, we revisit the roles of augmentation strategies and equivariance in improving CL's efficacy. We introduce CLEVER, the first curated benchmark for evaluating the generation of specifications and formally verified code in Lean. Sep 27, 2024 · Membership inference and memorization is a key challenge with diffusion models. Our method, STAIR (SafeTy Alignment with Introspective Reasoning), guides models to think more carefully before responding. We propose CLeVER (Contrastive Learning Via Equivariant Representation), a novel equivariant contrastive learning framework compatible with augmentation strategies of arbitrary complexity for various mainstream CL backbone models. The idea of using an ensemble of model is clever. It requires full formal specs and proofs. In CLEVER, the claim-evidence fusion model and the claim-only model are independently trained to capture the corresponding information. The benchmark comprises of 161 programming problems; it evaluates both formal speci-fication generation and implementation synthesis from natural language, requiring formal correctness proofs for both. Feb 21, 2026 · This survey on spurious correlations uses the Clever Hans metaphor to motivate the problem, formalizes a group-based setup g=(y,a) with core metrics (worst-group, average-group, bias-conflicting), and explains why models latch onto shortcuts (simplicity bias, training dynamics). . Jan 22, 2025 · Promoting openness in scientific communication and the peer-review process May 1, 2025 · 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 into providing harmful responses. Jul 8, 2025 · TL;DR: We introduce CLEVER, a hand-curated benchmark for verified code generation in Lean. Unlike existing works, CLEVER is augmentation-free and mitigates biases on infer- ence stage. The proposed CLEVER score is attack-agnostic and is computationally feasible for large neural networks.
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