SOURCE-LINKED INTELLIGENCE
Clinical Reasoning Under a Partially Observed Objective in Cone Beam CT Report Generation
Maxillofacial report generation from cone beam computed tomography is scored here by a composite objective placing 80% of its weight on a large language model judgement of factual entailment and 20% on lexical overlap, of which only the lexical fifth is visible during development. The grader's BLEU-4 and METEOR routines are reproduced in pure Python and match the reference to machine precision, and an offline entailment surrogate, which tells a report written for one patient from one written for another at an area under the curve of 0.987, makes the composite objective cheap enough to optimise
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-02T15:06:06.000Z
First collected: 2026-09-21T05:32:15.665Z. This is not the publication date.