1Cademy - RAG vs Graph-RAG Controlled Comparison (Han et al., 2025)

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RAG vs Graph-RAG Controlled Comparison (Han et al., 2025)

RAG vs GraphRAG: A Systematic Evaluation and Key Insights is a 2025 study by Han et al. that benchmarks Retrieval-Augmented Generation (RAG) against Graph Retrieval-Augmented Generation (GraphRAG) under a unified evaluation protocol. The protocol fixes data preprocessing, retrieval configurations, and generation settings across compared systems so that observed differences can be attributed to the retrieval paradigm rather than to interface mismatches. The benchmark covers question answering and query-based summarization on established text corpora, and the analysis additionally examines failure modes, efficiency trade-offs, and LLM-judge evaluation biases. The authors show that RAG and GraphRAG have distinct task-dependent strengths, and that hybrid selection and integration strategies can combine those strengths for more consistent performance. The work is cited as motivating evidence that fair graph-vs-flat comparisons require matched protocols.