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UCVE: Graph Structured Retrieval for Compliance Validation
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First public release: 2026-10-27 · Indexed by Pub-AI: 2026-10-28 UTC
UCVE: Graph Structured Retrieval for Compliance Validation
Preprint posted: 2026-10-27 · Original record ↗
- arxiv
- 2610.37323
Explicit source versions (1)
- v1 · 2026-10-27
- Preprint available
Source date: 2026-10-27 · First detected: 2026-10-28 UTC · Historical baseline
Source evidence (3)
- Official evidence ↗ · RSS guid=oai:arXiv.org:2610.37323v1; arxiv:announce_type=new; item pubDate (official metadata)
- Official evidence ↗ · atom:published (official metadata)
- Official evidence ↗ · atom:published (official metadata)
Abstract · arxiv
Structured compliance validation requires determining whether every obligation in a predefined requirement space is satisfied, violated, or unaddressed by a given document. This can be described as a coverage problem that existing retrieval and classification systems, by treating requirements as independent, are not designed to solve. We introduce \textbf{\ac{UCVE}}, a domain-agnostic framework that represents compliance requirement spaces as a \ac{CRG} and performs retrieval via spectral reranking over its reinforcement learning-weighted Laplacian. Edges between requirement nodes are learned via reinforcement learning with a traversal reward grounded in violation detection, reshaping the graph's community structure such that low-pass spectral filtering distinguishes relevant from irrelevant obligation clusters. Evaluating across three compliance domains, \ac{UCVE} averages 4.3\% matched-$K$ recall lift over flat cosine retrieval and consistently outperforms strong retrieval and graph-based baselines.