A Retrieval-Augmented Multi-Agent System for Financial Statement Analysis
Keywords:
.Abstract
We present a retrieval-augmented, multi-agent system (RAMAS) for machine-assistedanalysis of corporate financial statements. The system integrates dense and sparseretrieval over XBRL/iXBRL regulatory
References
• Lewis, P. et al. (2020). Retrieval-Augmented Generation for Knowledge-Intensive NLP. NeurIPS. (Paper + PDF). NeurIPS Proceedings+1
• Wu, Q. et al. (2023–2024). AutoGen: Enabling Next-Gen LLM Applications via MultiAgent Conversation Framework. (arXiv, Microsoft Research page, OpenReview).
arXiv+2Microsoft+2
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Published
2024-06-20
How to Cite
Sagar gupta. (2024). A Retrieval-Augmented Multi-Agent System for Financial Statement Analysis . Journal of Computational Analysis and Applications (JoCAAA), 33(06), 3032–3041. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/3777
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