HIT在SemEval-2022任务2：用于习语检测的预训练语言模型
HIT at SemEval-2022 Task 2: Pre-trained Language Model for Idioms Detection
摘要：
同样的多词表达在不同的句子中可能有不同的含义。它们主要分为字面意义和习语意义两大类。非基于上下文的方法在这个问题上表现不佳，我们需要上下文嵌入来正确理解多词表达的习惯意义。我们使用一个预先训练好的语言模型，它可以提供一个上下文感知的句子嵌入，以检测句子中的多词表达是否是惯用用法。
英文摘要：
The same multi-word expressions may have different meanings in different sentences. They can be mainly divided into two categories, which are literal meaning and idiomatic meaning. Non-contextual-based methods perform poorly on this problem, and we need contextual embedding to understand the idiomatic meaning of multi-word expressions correctly. We use a pre-trained language model, which can provide a context-aware sentence embedding, to detect whether multi-word expression in the sentence is idiomatic usage.
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。
