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Perception, Layout, and Validation: Calibrated Confidence for Reliable Straight-Through Processing of Financial Documents
Straight-through processing (STP) on extracted key-value fields from financial documents without human review requires a calibrated probability together with a bounded guarantee on the residual error of the auto-approved tier. The emergence of modern Vision Language Models (VLMs) provides an out-of-the-box capability for extracting the key-values, but their verbalized confidence signals are unreliable and weakly track field correctness. This paper introduces a decomposed confidence layer along three interpretable channels, including perception, layout, and validation. Together with a final con
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-17T12:09:21.000Z
- arXiv · Artificial Intelligence · 2026-09-17T12:09:21.000Z
First collected: 2026-09-19T20:26:32.566Z. This is not the publication date.