AI article
The Document Parsing Bottleneck: LlamaParse, AST Layout Engines, and Table Reconstruction in Production RAG
Community description: Quantitative benchmark comparing OCR heuristics vs. multimodal AST layout parsers on SEC 10-K tables, featuring our open-source pgvector pipeline and benchmark dataset.
Dev.to | Nov 7, 2026 | Soham Sharma
Automated excerpt
Standard document ingestion architectures rely on naive text extractors or heuristic OCR pipelines that linearize two-dimensional page geometries into one-dimensional character sequences. We formalize the document reconstruction problem through three mathematical metrics: Table Cell Intersection-over-Union ($IoU_{cell}$), Heading Hierarchy Tree Edit Distance ($TED_{hier}$), and Reciprocal Rank Fusion ($RRF$) degradation under layout perturbation. Mitigation Protocol: LlamaParse implements Cross-Page Table Tracking.
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