Measuring and Improving Consistency in Pretrained Language Models

• Published in: Transactions of the Association for Computational Linguistics Vol. 9; pp. 1012 - 1031
• Main Authors: Elazar, Yanai, Kassner, Nora, Ravfogel, Shauli, Ravichander, Abhilasha, Hovy, Eduard, Schütze, Hinrich, Goldberg, Yoav
• Format: Journal Article
• Language: English
• Published: One Rogers Street, Cambridge, MA 02142-1209, USA MIT Press 01.01.2021; MIT Press Journals, The; The MIT Press
• Subjects: Accuracy; Alternations; Consistency; Knowledge; Knowledge representation; Language; Language modeling; Linguistics; Natural language; Natural language processing; Paraphrase; Queries; Variance analysis

of a model—that is, the invariance of its behavior under meaning-preserving alternations in its input—is a highly desirable property in natural language processing. In this paper we study the question: Are Pretrained Language Models (PLMs) consistent with respect to factual knowledge? To this end, w...