TeXBLEU：用于评估LaTeX格式的自动指标
TeXBLEU: Automatic Metric for Evaluate LaTeX Format
AI总结：
针对LaTeX格式数学表达式缺乏合适评估指标的问题，本研究提出基于n元语法BLEU构建的TeXBLEU指标，结合预定义分词器与带位置编码的微调嵌入模型，在MathBridge数据集上较传统指标实现显著提升。
摘要：
LaTeX适用于创建科学、技术、数学和计算机科学领域的特殊格式文档。尽管LaTeX格式的数学表达式与语言模型结合使用的情况日益增多，但目前尚无合适的评估指标来对其进行评价。本研究中，我们提出TeXBLEU——一种基于翻译任务中广泛使用的n元语法BLEU指标构建的、用于评估LaTeX格式数学表达式的指标。所提出的TeXBLEU由在arXiv论文数据集上训练的预定义分词器，以及带有位置编码的微调嵌入模型组成。TeXBLEU分数通过将BLEU的修正精确率分数替换为基于n元语法的词元相似度计算得出。在包含1000个数据点的MathBridge数据集上，TeXBLEU相较于BLEU、sacreBLEU、Rouge等传统评估指标，分别提升了86%、121%和610%。代码可在https://github.com/KyuDan1/TeXBLEU获取。
英文摘要：
LaTeX is suitable for creating specially formatted documents in science, technology, mathematics, and computer science. Although the use of mathematical expressions in LaTeX format along with language models is increasing, there are no proper evaluation matrices to evaluate them. In this study, we propose TeXBLEU, a metric for evaluating mathematical expressions in the LaTeX format built on the n-gram-based BLEU metric widely used in translation tasks. The proposed TeXBLEU consists of a predefined tokenizer trained on the arXiv paper dataset and a fine-tuned embedding model with positional encoding. The TeXBLEU score was calculated by replacing BLUE's modified precision score with the similarity of n-gram-based tokens. TeXBLEU showed improvements of 86\%, 121\%, and 610\% over traditional evaluation metrics, such as BLEU, sacreBLEU, and Rouge, respectively, on the MathBridge dataset with 1,000 data points. The code is available at https://github.com/KyuDan1/TeXBLEU.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
