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  • Hyperbolic Attention Networks - OpenReview
    We propose to incorporate inductive biases and operations coming from hyperbolic geometry to improve the attention mechanism of the neural networks
  • AAAI 2027 Workshop MEDWM | OpenReview
    Welcome to the OpenReview homepage for AAAI 2027 Workshop MEDWM
  • Evaluating the Robustness of Neural Networks: An Extreme Value. . .
    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 and is computationally feasible for large neural networks
  • The Clever Hans Mirage: A Comprehensive Survey on Spurious. . .
    The Clever Hans Mirage: A Comprehensive Survey on Spurious Correlations in Machine Learning Wenqian Ye, Luyang Jiang, Eric Xie, Guangtao Zheng, Yunsheng Ma, Xu Cao, Dongliang Guo, Daiqing Qi, Zeyu He, Yijun Tian, Christopher W Porter, Megan Coffee, Zhe Zeng, Sheng Li, Ziran Wang, Ting-Hao Kenneth Huang, James Matthew Rehg, Henry Kautz, Aidong
  • 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 testbed for synthesis and formal reasoning
  • Clever: A Curated Benchmark for Formally Verified Code Generation
    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 both formal speci- fication generation and implementation synthesis from natural language, requiring formal correctness proofs for both
  • Djork-Arné Clevert - OpenReview
    Promoting openness in scientific communication and the peer-review process
  • On the Planning Abilities of Large Language Models : A Critical . . .
    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 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
  • CLEVER: A Curated Benchmark for Formally Verified Code Generation
    This paper introduces CLEVER, a benchmark dataset designed to evaluate LLMs on formally verified code generation It consists of 161 carefully crafted Lean specifications derived from programming problems in the existing HumanEval dataset
  • STAIR: Improving Safety Alignment with Introspective Reasoning
    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 Our method, STAIR (SafeTy Alignment with Introspective Reasoning), guides models to think more carefully before responding





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