Graph-Augmented Retrieval for Cross-Entity Financial Sentiment Analysis: A Comparative Study

In three linesComparative study of a two-hop Graph-RAG architecture versus standard vector-only RAG for cross-entity financial sentiment analysis. On 100 queries (30 direct, 70 relational), Graph-RAG improves entity recall (+6.4%, p<0.001) and answer relevancy for complex queries (+11.7%), with no quality degradation, modest 22.6% latency increase but 80% variance reduction.

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