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This paper proposes a cycle-consistent neural architecture that generates faithful natural language explanations of formal verification certificates, achieving 90% soundness and 860x faster inference than LLM baselines.
This article argues that the accountability infrastructure developed for automated financial trading over decades provides a blueprint for governing AI agents, drawing on specific regulatory mechanisms like FINRA Rule 5310 and SEC Rule 17a-4.