mlsanityData to 14 Oct 2026

Evidence-Grounded Constraint Checking in Construction Documents

arXiv 2607.29058 ↗First posted 31 Jul 2026cs.AIcited by 0

Not on the map. Why?

Abstract (arXiv)

Professional-document review is a constraint-checking problem in which decisions depend on relations among text, geometry, pages, and document revisions. We present an evidence-grounded pipeline that normalizes extracted facts, executes four-state rules deterministically, retains source spans, and escalates unresolved cases. We evaluate its PDF evidence allocator on 160 reference-based tasks from 29 construction projects using a repeated four-system test and a disjoint two-system breadth extension. In the repeated test, reallocating a four-image budget from retrieved page overviews to one overview and three overlapping tiles improves project-family standardized decision accuracy by 10.6 percentage points (95% project-cluster bootstrap CI: 4.3 to 18.0; exact p = 0.031). This effect does not persist in the broader block: Region-RAG changes accuracy by -4.1 points (95% CI: -10.2 to 1.9; exact p = 0.209), while an equal-image sensitivity favors page breadth. Exact finding-set recovery remains low, false passes remain common, and repeated-run agreement is poorly calibrated. The results identify a resolution-breadth trade-off rather than a universal advantage for region-focused evidence, motivating rule-aware evidence routing and expert review.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 10 of its 15 references that are in the map. First posted on arXiv 31 Jul 2026.

Builds on

10 of 15 references.

References · 10

  1. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
  2. 2017On Calibration of Modern Neural Networkscited by 4,960
  3. 2020DocVQA: A Dataset for VQA on Document Imagescited by 1,317
  4. 2017Selective Classification for Deep Neural Networkscited by 852
  5. 2022LayoutLMv3: Pre-training for Document AI with Unified Text and Image Maskingcited by 485
  6. 2021OCR-free Document Understanding Transformercited by 407
  7. 2024MMLongBench-Doc: Benchmarking Long-context Document Understanding with Visualizationscited by 183
  8. 2024M3DocRAG: Multi-modal Retrieval is What You Need for Multi-page Multi-document Understandingcited by 111
  9. 2026AEC-Bench: A Multimodal Benchmark for Agentic Systems in Architecture, Engineering, and Constructioncited by 6
  10. 2026DrawingVQA: A Real-World Benchmark for Multi-Depth Visual-Textual Reasoning on Construction Drawingscited by 3

Built on by

Not cited yet.

Similar, not cited

Close in wording, no citation either way

  1. 2026From PDF to Evidence: Structure-Aware Retrieval for Clinical Practice Guidelines
  2. 2026ExtractBench: A Benchmark for Schema-Guided Enterprise Document Extraction
  3. 2026ContraVis: Evidence-Grounded Visual Analytics for Contradiction Review in Legal Contracts
  4. 2026Locating Failure in Multi-Page Visually Rich Document Understanding: An Empirical Attribution
  5. 2026WildTrace: Benchmarking Natural Evidence Trails in Long-Context Reasoning
  6. 2026SciDocBench: A Workflow-Centered Benchmark and Data Pipeline for Scientific Document Understanding
  7. 2026Terminal Symmetry as a Carrier of Asymmetric Process Knowledge: Statewise Refinement for Anytime Verified Construction
  8. 2026TopoGraphRAG-Bench: Evaluating Multimodal GraphRAG on Layout-Grounded Evidence Reasoning