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Evaluating Graph-RAG vs. Standard RAG: A Hallucination Benchmark on Fact-Dense Queries
A hands-on benchmark compares a deterministic 3-Tiered Graph-RAG system against standard vector RAG on fact-dense queries using a synthetic 50-player basketball dataset. The setup combines a QuadStore knowledge graph with a ChromaDB vector database and a local Flan-T5-base model (250M parameters). Results show the small local LLM handles the simpler standard RAG prompt well but slightly underperforms on the complex conflict-resolution prompt required by Graph-RAG, suggesting that enforcing graph-based rules via prompting needs a larger reasoning model such as Llama 3 or GPT-4. The key takeaway is that prompt complexity must be matched to model capacity when designing production RAG systems.
Nguồn: https://machinelearningmastery.com/evaluating-graph-rag-vs-standard-rag-a-hallucination-benchmark-on-fact-dense-queries. 8 Sync News chỉ tóm tắt và dẫn link; bản quyền nội dung thuộc tác giả và nguồn gốc.
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