论文标题
向我解释一下我五岁 - 使用变压器简化句子
Explain to me like I am five -- Sentence Simplification Using Transformers
论文作者
论文摘要
句子简化旨在使文本的结构在保持其原始含义的同时易于阅读和理解。这对残疾人，新语言学习者或识字率低的人可能有所帮助。简化通常涉及删除困难的单词并重新阐述句子。先前的研究重点是通过使用外部语言数据库来简化该任务，或者使用控制令牌进行所需的句子进行微调。但是，在本文中，我们纯粹使用了预训练的变压器模型。我们实验了GPT-2和BERT模型的组合，在机械TURK数据集上达到了46.80的最佳SARI评分，这比以前的最先进的结果要好得多。该代码可以在https://github.com/amanbasu/sentence-simplification上找到。
Sentence simplification aims at making the structure of text easier to read and understand while maintaining its original meaning. This can be helpful for people with disabilities, new language learners, or those with low literacy. Simplification often involves removing difficult words and rephrasing the sentence. Previous research have focused on tackling this task by either using external linguistic databases for simplification or by using control tokens for desired fine-tuning of sentences. However, in this paper we purely use pre-trained transformer models. We experiment with a combination of GPT-2 and BERT models, achieving the best SARI score of 46.80 on the Mechanical Turk dataset, which is significantly better than previous state-of-the-art results. The code can be found at https://github.com/amanbasu/sentence-simplification.
