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The semantic reconstruction game is introduced, a training-free evaluator that decomposes compliance judgments into constrained semantic comparisons and achieves the lowest mean error against human labels among evaluated methods and reduces variation in reported ASR.
This work presents a general recipe to integrate lookahead into any branch-and-bound verifier and demonstrates how one of the current state-of-the-art branching heuristics, FSB, can be viewed as a special instantiation of the lookahead branching strategy.
An inprocessing framework for neural network verification driven by the lookahead procedure is introduced, which derives new lemmas over the phases of unstable ReLUs, which are collected into an implication graph that is used to prune the search space and vivify boolean cuts.
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