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Canada-0-MEDITATION Azienda Directories
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Azienda News:
- 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 evaluates both formal speci-fication generation and implementation synthesis from natural language, requiring formal correctness proofs for both
- 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
- 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
- Contrastive Learning Via Equivariant Representation - OpenReview
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
- Evaluating the Robustness of Neural Networks: An Extreme Value. . .
We propose the first attack-independent robustness metric, a k a CLEVER, that can be applied to any neural network classifier
- 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 biases on infer- ence stage In CLEVER, the claim-evidence fusion model and the claim-only model are independently trained to capture the corresponding information
- 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
- KnowTrace: Explicit Knowledge Tracing for Structured. . .
" This paper introduces a clever incorporation of knowledge graph operation for structured RAG " (Reviewer ifaQ) " The proposed method is straightforward, intuitive, and easy to implement "; " It is innovative that the paper leverages the structured nature of reasoning paths to filter and refine generated trajectories for model training
- 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
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