论文标题
暂时的单词意思是使用时间段的歧义
Temporal Word Meaning Disambiguation using TimeLMs
论文作者
论文摘要
鉴于现代文明中的事件，单词的含义不断变化。大型语言模型使用单词嵌入，通常是静态的，因此无法应对这种语义变化。因此，解决单词含义的歧义很重要。本文是在这个方向上的努力，我们探讨了EVONLP共享任务的单词感官歧义方法。我们为解决此问题的两种解决方案进行严格的消融。我们看到，使用时刻语言模型的方法有助于这项任务。此外，我们探讨了这一问题的未来方向。
Meaning of words constantly changes given the events in modern civilization. Large Language Models use word embeddings, which are often static and thus cannot cope with this semantic change. Thus,it is important to resolve ambiguity in word meanings. This paper is an effort in this direction, where we explore methods for word sense disambiguation for the EvoNLP shared task. We conduct rigorous ablations for two solutions to this problem. We see that an approach using time-aware language models helps this task. Furthermore, we explore possible future directions to this problem.
