Fighting Numerical Hallucinations via Data-centric Compilation for Online Financial QA 事件

Fighting Numerical Hallucinations via Data-centric Compilation for Online Financial QA arXiv:2605.31064v1 Announce Type: cross Abstract: Large Language Models (LLMs) have significantly advanced online data services, particularly in the domain of financial question answering (FinQA). However, such systems remain susceptible to numerical reasoning hallucinations, which critically undermine reliability in high-stakes financial applications. Although retrieval-augmented generation (RAG) has been wi