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The paper introduces temporal dependency graphs extracted from legal documents to compute filing deadlines, showing a pipeline approach outperforms direct language model answering in accuracy.
This paper proposes a governance model for autonomous AI agents based on institutional attestation, where actions are governed through independently attested evidence rather than monitoring agent reasoning. It formalizes this approach with a proof-of-concept implementation for high-risk actions like clinical prescribing and software deployment.