Diagnosing Fine-Grained Inconsistency Classification in Financial Disclosure Text
Researchers tested different AI models to classify 11 types of inconsistencies in financial text, such as numerical or factual errors. They found that fine-tuning a small model significantly improved performance compared to frozen models, and that correctly locating the conflicting evidence is crucial for accurate classification. The study highlights which inconsistency types are most sensitive to evidence quality.