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The Copy Ceiling: An Input-Exposure Control for Ontology-Grounded Generation over Curated Corpora

arXiv · AI, language, vision and robotics · article · Sep 21, 2026 · UTC

When a language model answers from a curated corpus via graph-based retrieval, a large grounding uplift does not establish reasoning over the retrieved structure: the context may already expose the gold answers. We propose exposure accounting, which classifies each gold item by whether the shown context exposes it and whether the answer recovers it. Its scalar reference is the copy ceiling, the recall a verbatim copy of the context achieves; signed gain over copy measures the model's recall relative to this deterministic, judge-free baseline. Across ten models, unaided recall averages 0.26 and

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