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  1. 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 evaluates …

  2. Submissions | OpenReview

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

  3. STAIR: Improving Safety Alignment with Introspective Reasoning

    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 …

  4. Jonathan Gratch - OpenReview

    ACII 2021 CaSiNo: A Corpus of Campsite Negotiation Dialogues for Automatic Negotiation Systems Kushal Chawla, Jaysa Ramirez, Rene Clever, Gale M. Lucas, Jonathan May, Jonathan Gratch 2021 …

  5. Forum - OpenReview

    Promoting openness in scientific communication and the peer-review process

  6. 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 attack-agnostic …

  7. EvoTest: Evolutionary Test-Time Learning for Self-Improving Agentic ...

    Sep 16, 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 environments. This …

  8. Contrastive Learning Via Equivariant Representation - OpenReview

    Sep 25, 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 …

  9. Do Histopathological Foundation Models Eliminate Batch Effects? A ...

    Oct 12, 2024 · Keywords: histopathology, foundation models, batch effects, Clever Hans effect, robustness, generalization Abstract: Deep learning has led to remarkable advancements in …

  10. 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 biases on infer- …