A coarse-to-fine LLM framework for document-level numerical semantic matching achieves about 90% F1 on financial disclosure documents, outperforming the prior AutoCheck system by roughly ten points.
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Document-Level Tabular Numerical Cross-Checking: A Coarse-to-Fine Approach
A coarse-to-fine LLM framework for document-level numerical semantic matching achieves about 90% F1 on financial disclosure documents, outperforming the prior AutoCheck system by roughly ten points.