Uncovering Inconsistencies and Contradictions in Financial Reports using Large Language Models.
2023 IEEE International Conference on Big Data (BigData)(2023)
摘要
Correct identification and correction of contradictions and inconsistencies within financial reports constitute a fundamental component of the audit process. To streamline and automate this critical task, we introduce a novel approach leveraging large language models and an embedding-based paragraph clustering methodology. This paper assesses our approach across three distinct datasets, including two annotated datasets and one unannotated dataset, all within a zero-shot framework. Our findings reveal highly promising results that significantly enhance the effectiveness and efficiency of the auditing process, ultimately reducing the time required for a thorough and reliable financial report audit.
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关键词
contradiction detection,natural language processing,large language models,financial reports,machine learning
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