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Evidence record 5756 · automatically gathered

PolicyBank: Evolving Policy Understanding for LLM Agents

LLM agents operating under organizational policies must comply with authorization constraints typically specified in natural language. In practice, such specifications inevitably contain ambiguities and logical or semantic gaps that cause the agent's behavior to systematically diverge from the true requirements. We ask: by letting an agent evolve its policy understanding through interaction and corrective feedback from pre-deployment testing, can it autonomously refine its interpretation to clos

Record details

Published: 16 April 2026
Source: arXiv
Category: Research
Topics: Regulation · Agents & autonomy
Retrieved: 14 July 2026

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These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

Shared topic: Regulation · Shared topic: Agents & autonomy

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Shared topic: Regulation · Shared topic: Agents & autonomy

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How to cite this record

ethics.ai (16 April 2026), “PolicyBank: Evolving Policy Understanding for LLM Agents,” evidence record 5756, https://ethics.ai/record/5756 (originally published by arXiv).

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