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English(EN) FinSAgent: Corpus-Aligned Multi-Agent RAG Framework for Evidence-Grounded SEC Filing Question Answering

FinSAgent框架通过语料对齐检索增强SEC文件问答

作者 PulseAugur 编辑部 · [3 个来源] ·

研究人员推出FinSAgent，一个旨在改进SEC文件问答的新型多智能体框架。该系统通过根据金融文件的特定结构和术语来调整检索，解决了先前的语料不对齐问题。FinSAgent利用角色专业化智能体、数据库感知查询分解和学习型重排器来增强检索覆盖率和答案的正确性，在离线基准测试和在线用户评分中均优于现有基线。 AI

影响 该框架可以提高金融数据分析和合规的准确性和效率。

排序理由 该集群描述了在arXiv上发表的一篇学术论文中提出的一个新颖框架。

在 arXiv cs.IR (Information Retrieval) 阅读 →

AI 生成摘要 · Google Gemini · 来自 3 个来源。 我们如何撰写摘要 →

FinSAgent框架通过语料对齐检索增强SEC文件问答

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该集群描述了在arXiv上发表的一篇学术论文中提出的一个新颖框架。
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报道来源 [3]

  1. arXiv cs.CL TIER_1 English(EN) · Jijun Chi (University of Toronto), Zhenghan Tai (SimpleWay.AI, University of Toronto), Hanwei Wu (SimpleWay.AI, McMaster University), Tung Sum Thomas Kwok (SimpleWay.AI, University of California, Los Angeles), Hailin He (SimpleWay.AI), Zixing Liao (Simpl… ·

    FinSAgent：语料库对齐的多智能体RAG框架，用于基于证据的SEC文件问答

    arXiv:2607.18102v1 Announce Type: cross Abstract: Financial question answering over U.S. Securities and Exchange Commission (SEC) filings requires retrieving and synthesizing heterogeneous evidence dispersed across long, standardized, and highly redundant disclosures. Existing re…

  2. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Xinyu Wang ·

    FinSAgent：语料库对齐的多智能体RAG框架，用于基于证据的SEC文件问答

    Financial question answering over U.S. Securities and Exchange Commission (SEC) filings requires retrieving and synthesizing heterogeneous evidence dispersed across long, standardized, and highly redundant disclosures. Existing retrieval-augmented and multi-agent systems typicall…

  3. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Xinyu Wang ·

    FinSAgent：语料库对齐的多智能体RAG框架，用于基于证据的SEC文件问答

    Financial question answering over U.S. Securities and Exchange Commission (SEC) filings requires retrieving and synthesizing heterogeneous evidence dispersed across long, standardized, and highly redundant disclosures. Existing retrieval-augmented and multi-agent systems typicall…

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