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• A two-stage pipeline combining hybrid retrieval with neural reranking achieves Recall@5 of 0.816 and MRR@3 of 0.605, outperforming all single-stage methods by a large margin.result 95%
• BM25 outperforms state-of-the-art dense retrieval on financial documents containing mixed text-and-table content.result 90%
• Query expansion methods (HyDE, multi-query) provide limited benefit for precise numerical queries in financial QA.limitation 85%
• Contextual retrieval yields consistent gains for retrieval over heterogeneous documents containing both text and tabular data.result 80%
• The paper benchmarks ten retrieval strategies spanning sparse, dense, hybrid fusion, cross-encoder reranking, query expansion, index augmentation, and adaptive retrieval.method 95%
• The evaluation uses a challenging financial QA benchmark of 23,088 queries over 7,318 documents with mixed text-and-table content.method 95%
• The paper provides actionable cost-accuracy recommendations for retrieval strategy selection.technical 85%
• No systematic comparison of modern retrieval methods exists for heterogeneous documents containing both text and tabular data prior to this work.limitation 80%

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