Unverified50% confidenceDecision RuleExact time
When evaluating OCR solutions, test sets should be specifically built with dirty data rather than only using clean digital PDFs to validate performance.
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9/11/2026
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UnverifiedThe quality of synthetic data is highly dependent on prompt design and the quality of the original documents; using the same model to generate data and serve as an evaluation benchmark carries the risk of self-reinforcing bias, and the best practice is to mix it with human-annotated data and validate through A/B testing.71% similarUnverifiedUsing coherence assessment as a detection method can provide a lightweight screening solution that does not rely on fact-checking databases.69% similarUnverifiedFor scenarios with extremely high accuracy requirements (such as financial data), a hybrid approach of "traditional OCR + LLM post-processing validation" is recommended.69% similarUnverifiedThrough ablation experiments, cross-dataset validation, theoretical analysis, and other means, it is possible to demonstrate that a method's effectiveness does not depend on data scale.69% similarUnverified测试用例应是可编辑、可检索的结构化数据，包含测试步骤、预期结果和变量定义，而非死板文档68% similar
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