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arXiv · 2610.05989

H-CRSPV: Preventing Semantic Omission in Late-Bound Large Language Model Releases

Abstract

Large-language-model release pipelines increasingly combine commitments, signatures, provenance records, and heterogeneous verification backends. Yet validating every submitted object does not establish that a release realizes every requirement of its registered transformation. An untrusted realization proposer may omit a required relation, propose an unauthorized evidence-sharing assignment, or bind valid evidence to the wrong object. This verification-boundary failure is termed Semantic Omission under Valid Evidence (SOVE). Hybrid Cryptographic Relation-based Semantic Plan Verification (H-CRSPV) is a replicated admission layer that enforces required-set completeness before release consumption. Before evidence selection, an authorized registration entity commits an authenticated authority record. Validators independently derive the required-obligation multiset, check exact entry-occurrence coverage, validate proposal-induced evidence sharing, and bind admissible groups one-to-one to keeper-resolved objects. Evidence remains provisional until the challenge window closes and an atomic finalizer activates the release. The analysis establishes structural exactness and conditional semantic guarantees under explicit assumptions. Across 36 omission artifacts, submitted-object validation accepts all 36 because every submitted object passes its backend-specific verifier. H-CRSPV rejects all 36 while accepting all six honest releases. The prototype also validates six restricted source-to-RelationIR bindings and rejects all 60 tested mutations. In a continuous four-validator Qwen2.5-1.5B workflow, the same authority record remains fixed across three legal releases with different post-registration availability states. These results show that per-object validity does not establish complete, correctly bound, and finalized release evidence.

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BibTeXRIS

Weijie Miao, Henry Hong-Ning Dai, Ming Li. 2026-10-05. H-CRSPV: Preventing Semantic Omission in Late-Bound Large Language Model Releases. https://arxiv.org/abs/2610.05989

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