RaV-IDP: A Reconstruction-as-Validation Framework for Faithful Intelligent Document Processing
Intelligent document processing pipelines extract structured entities (tables, images, and text) from documents for use in downstream systems such as knowledge bases, retrieval-augmented generation, and analytics. A persistent limitation of existing pipelines is that extraction output is produced without any intrinsic mechanism to verify whether it faithfully represents the source. Model-internal confidence scores measure inference certainty, not correspondence to the document, and extraction errors pass silently into downstream consumers. We present Reconstruction as Validation (RaV-IDP), a document processing pipeline that introduces reconstruction as a first-class architectural compone...
| Authors | Pritesh Jha |
|---|---|
| Primary category | cs.CV |
| Published | 26 April 2026 |
| Last updated at source | 26 April 2026 |
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