Papers by YuHong Sun
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. |
Benchmarking Hallucination in Large Language Models Based on Unanswerable Math Word Problem (2024.lrec-main)
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| Challenge: | Large language models (LLMs) are highly effective in various natural language processing tasks, but can produce unreliable conjectures in ambiguous contexts, which is known as hallucination. |
| Approach: | They propose a method to evaluate LLM hallucination in Question Answering based on the unanswerable math word problem (UMWP) . they combine text similarity and mathematical expression detection to determine whether LLM considers the question unanswered. |
| Outcome: | The proposed method combines text similarity and mathematical expression detection to determine whether the LLM considers the question unanswerable. |