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  1. CLEVER: A Curated Benchmark for Formally Verified Code …

    8 jul. 2025 · TL;DR: We introduce CLEVER, a hand-curated benchmark for verified code generation in Lean. It requires full formal specs and proofs. No few-shot method solves all stages, making …

  2. Clever: A Curated Benchmark for Formally Verified Code Generation

    We introduce CLEVER, the first curated benchmark for evaluating the generation of specifications and formally verified code in Lean. The benchmark comprises of 161 programming problems; it …

  3. Evaluating the Robustness of Neural Networks: An Extreme Value...

    15 feb. 2018 · Our analysis yields a novel robustness metric called CLEVER, which is short for Cross Lipschitz Extreme Value for nEtwork Robustness. The proposed CLEVER score is attack …

  4. Submissions | OpenReview

    22 jan. 2025 · Leaving the barn door open for Clever Hans: Simple features predict LLM benchmark answers Lorenzo Pacchiardi, Marko Tesic, Lucy G Cheke, Jose Hernandez-Orallo 27 …

  5. Contrastive Learning Via Equivariant Representation - OpenReview

    25 sep. 2024 · In this paper, we revisit the roles of augmentation strategies and equivariance in improving CL's efficacy. We propose CLeVER (Contrastive Learning Via Equivariant …

  6. STAIR: Improving Safety Alignment with Introspective Reasoning

    1 mei 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 …

  7. KnowTrace: Explicit Knowledge Tracing for Structured...

    13 sep. 2024 · TL;DR: We introduce a structured RAG paradigm (KnowTrace) that seamlessly integrates knowledge structuring and multi-step reasoning for improved MHQA performance.

  8. Counterfactual Debiasing for Fact Verification

    579 In this paper, we have proposed a novel counter- factual framework CLEVER for debiasing fact- checking models. Unlike existing works, CLEVER is augmentation-free and mitigates …

  9. Do Histopathological Foundation Models Eliminate Batch Effects?

    11 okt. 2024 · Deep learning has led to remarkable advancements in computational histopathology, e.g., in diagnostics, biomarker prediction, and outcome prognosis. Yet, the lack …

  10. EvoTest: Evolutionary Test-Time Learning for Self-Improving …

    16 sep. 2025 · 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 …