Papers with fine-grained analysis of error patterns

1 papers
Error Classification of Large Language Models on Math Word Problems: A Dynamically Adaptive Framework (2025.findings-emnlp)

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Challenge: Current error classification methods rely on static and predefined categories to capture error patterns.
Approach: They propose a framework for automated dynamic error classification in mathematical reasoning that incorporates common error patterns as explicit guidance.
Outcome: The proposed framework reduces human bias and fine-grained analysis of error patterns.

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