Knowledge Graph-Augmented Few-Shot Learning vs RAG in DocVQA for Qwen2.5

This report synthesises findings from 11 peer-reviewed papers addressing the following research question: To what extent do knowledge graph-augmented few-shot learning methods improve DocVQA benchmarks for Qwen2.5, and how does this compare to retrieval-augmented generation (RAG) approaches. 7 claims were extracted from source literature; 7 were independently verified against retrieved documents. An automated multi-reviewer quality assessment produced a score of 8.3/10. This report is a machine-generated literature synthesis and does not constitute original research.

Research goal: To what extent do knowledge graph-augmented few-shot learning methods improve DocVQA benchmarks for Qwen2.5, and how does this compare to retrieval-augmented generation (RAG) approaches?

Autonomous literature synthesis. Automated review score: 8.3/10. Full text and citation available at Assignee Research.