SMARTFinRAG: Interactive Modularized Financial RAG Benchmark
Fuente:
arXiv
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| Autor principal: | |
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| Formato: | Preprint |
| Publicado: |
2025
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| Acceso en línea: | |
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| _version_ | 1866913807449718784 |
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| author | Zha, Yiwei |
| author_facet | Zha, Yiwei |
| contents | Financial sectors are rapidly adopting language model technologies, yet evaluating specialized RAG systems in this domain remains challenging. This paper introduces SMARTFinRAG, addressing three critical gaps in financial RAG assessment: (1) a fully modular architecture where components can be dynamically interchanged during runtime; (2) a document-centric evaluation paradigm generating domain-specific QA pairs from newly ingested financial documents; and (3) an intuitive interface bridging research-implementation divides. Our evaluation quantifies both retrieval efficacy and response quality, revealing significant performance variations across configurations. The platform's open-source architecture supports transparent, reproducible research while addressing practical deployment challenges faced by financial institutions implementing RAG systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_18024 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | SMARTFinRAG: Interactive Modularized Financial RAG Benchmark Zha, Yiwei Computational Engineering, Finance, and Science Computation and Language Information Retrieval Financial sectors are rapidly adopting language model technologies, yet evaluating specialized RAG systems in this domain remains challenging. This paper introduces SMARTFinRAG, addressing three critical gaps in financial RAG assessment: (1) a fully modular architecture where components can be dynamically interchanged during runtime; (2) a document-centric evaluation paradigm generating domain-specific QA pairs from newly ingested financial documents; and (3) an intuitive interface bridging research-implementation divides. Our evaluation quantifies both retrieval efficacy and response quality, revealing significant performance variations across configurations. The platform's open-source architecture supports transparent, reproducible research while addressing practical deployment challenges faced by financial institutions implementing RAG systems. |
| title | SMARTFinRAG: Interactive Modularized Financial RAG Benchmark |
| topic | Computational Engineering, Finance, and Science Computation and Language Information Retrieval |
| url | https://arxiv.org/abs/2504.18024 |