论文标题
进一步测量，更多的问题：基于变压器的语言模型的实验研究和补充胁迫
Measure More, Question More: Experimental Studies on Transformer-based Language Models and Complement Coercion
论文作者
论文摘要
基于变压器的语言模型在一系列自然语言理解任务上表现出强烈的表现。但是，这些模型如何对隐式含义的反应的问题在很大程度上尚未开发。我们使用补充胁迫现象进行了调查，该现象涉及诸如“学生完成帆船”的句子，其中“阅读”是隐含的。我们比较了LMS在具有和没有隐性含义的句子中在各个关键句子区域的惊人估计。在关键区域发现了与恢复隐式含义相关的效果，而句子差异很小。然后，我们使用后续实验来考虑潜在的混杂，揭示了不同的观点，这些观点提供了更丰富，更准确的图片。
Transformer-based language models have shown strong performance on an array of natural language understanding tasks. However, the question of how these models react to implicit meaning has been largely unexplored. We investigate this using the complement coercion phenomenon, which involves sentences like "The student finished the book about sailing" where the action "reading" is implicit. We compare LMs' surprisal estimates at various critical sentence regions in sentences with and without implicit meaning. Effects associated with recovering implicit meaning were found at a critical region other than where sentences minimally differ. We then use follow-up experiments to factor out potential confounds, revealing different perspectives that offer a richer and more accurate picture.
