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Titlebook: AI Verification; First International Guy Avni,Mirco Giacobbe,Christian Schilling Conference proceedings 2024 The Editor(s) (if applicable)

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,A Preliminary Study to Examining Per-class Performance Bias via Robustness Distributions,of instances. We observed that the robustness of the same class over the same data can significantly differ from each other for different neural networks; this means that even when a neural network appears to be unbiased, it might be easier to perturb instances of a given class so that they are misc
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Clover: ,sed-Loop ,ifiable Code Generation,vel of difficulty. Experimental results show that for this dataset: (i) LLMs are reasonably successful at automatically generating formal specifications; and (ii) our consistency checker achieves a promising acceptance rate (up to .) for correct instances while maintaining zero tolerance for adversa
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0302-9743 uring July 2024...The scope of the topics was broadly categorized into two groups. The first group, formal methods for artificial intelligence, comprised: formal specifications for systems with AI components; formal methods for analyzing systems with AI components; formal synthesis methods of AI com
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Conference proceedings 2024plainability of systems with AI components. The second group, artificial intelligence for formal methods, comprised: AI methods for formal verification; AI methods for formal synthesis; AI methods for safe control; and AI methods for falsification..
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