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WeaverBird: Empowering Financial Decision-Making with Large Language Model, Knowledge Base, and Search Engine

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arxiv 2308.05361 v4 pith:EWNIFOAB submitted 2023-08-10 cs.CL

classification cs.CL
keywords systemsearchweaverbirdbaseenginefinance-relatedfinancialhttps
verification ladder T0 review T1 audit T2 compute T3 formal
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We present WeaverBird, an intelligent dialogue system designed specifically for the finance domain. Our system harnesses a large language model of GPT architecture that has been tuned using extensive corpora of finance-related text. As a result, our system possesses the capability to understand complex financial queries, such as "How should I manage my investments during inflation?", and provide informed responses. Furthermore, our system incorporates a local knowledge base and a search engine to retrieve relevant information. The final responses are conditioned on the search results and include proper citations to the sources, thus enjoying an enhanced credibility. Through a range of finance-related questions, we have demonstrated the superior performance of our system compared to other models. To experience our system firsthand, users can interact with our live demo at https://weaverbird.ttic.edu, as well as watch our 2-min video illustration at https://www.youtube.com/watch?v=yofgeqnlrMc.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. MetaGraph: A Large-Scale Meta-Analysis of GenAI in Financial NLP (2022-2025)

    cs.CL 2025-09 unverdicted novelty 5.0 of 10

    Using LLM extraction on 681 papers, the authors build a public knowledge graph showing financial NLP moved from LLM adoption to limitation-aware, modular system design between 2022 and 2025.

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