Impact of Document Preprocessing Pipelines on Multi-Hop QA Reasoning Accuracy in Qwen2.5 and CLIP-Based Models

Abstract

Abstract: This report synthesises findings from 15 peer-reviewed papers addressing the following research question: What is the effect of different document preprocessing pipelines (OCR, layout encoding) on the reasoning accuracy of Qwen2.5 in multi-hop QA tasks like DocHop-QA, and how does it compare to. 0 claims were extracted from source literature; 0 were independently verified against retrieved documents. An automated multi-reviewer quality assessment produced a score of 5.0/10. This report is a machine-generated literature synthesis and does not constitute original research.

Research Question

What is the effect of different document preprocessing pipelines (OCR, layout encoding) on the reasoning accuracy of Qwen2.5 in multi-hop QA tasks like DocHop-QA, and how does it compare to CLIP-based models?

Verification Level

Descriptive public verification status only; aggregate claim counts are public, but individual claim records are not exposed here.

Quality Tier

Descriptive public triage only; this tier does not alter current publication or DOI behavior.

Quality Dimensions

Automated triage signals derived from public fields; not human peer review or independent validation.

Correction Record

Public corrections are additive records. Current status does not claim the synthesis is error-free.

Provenance