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

    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 it a strong …

  2. 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; …

  3. Submissions | OpenReview

    Jan 22, 2025 · Promoting openness in scientific communication and the peer-review process

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

    Feb 15, 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 …

  5. 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 …

  6. Provably Mitigating Overoptimization in RLHF: Your SFT Loss is...

    Jun 18, 2024 · With a clever usage of the equivalence between reward models and the corresponding optimal policy, the algorithm features a simple objective that combines (i) a …

  7. Weakly-Supervised Affordance Grounding Guided by Part-Level...

    Jan 22, 2025 · In this work, we focus on the task of weakly supervised affordance grounding, where a model is trained to identify affordance regions on objects using human-object …

  8. Contrastive Learning Via Equivariant Representation - OpenReview

    Sep 25, 2024 · TL;DR: This paper proposes CLeVER, a novel equivariant-based contrastive learning framework that improves training efficiency and robustness in downstream tasks by …

  9. 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. …

  10. Do Histopathological Foundation Models Eliminate Batch Effects?

    Abstract:Deep learning has led to remarkable advancements in computational histopathology, e.g., in diagnostics, biomarker prediction, and outcome prognosis. Yet, the lack of annotated …