1. Evaluating Document Coherence Modeling
- Author
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Aili Shen, Meladel Mistica, Bahar Salehi, Hang Li, Timothy Baldwin, and Jianzhong Qi
- Subjects
Computational linguistics. Natural language processing ,P98-98.5 - Abstract
AbstractWhile pretrained language models (LMs) have driven impressive gains over morpho-syntactic and semantic tasks, their ability to model discourse and pragmatic phenomena is less clear. As a step towards a better understanding of their discourse modeling capabilities, we propose a sentence intrusion detection task. We examine the performance of a broad range of pretrained LMs on this detection task for English. Lacking a dataset for the task, we introduce INSteD, a novel intruder sentence detection dataset, containing 170,000+ documents constructed from English Wikipedia and CNN news articles. Our experiments show that pretrained LMs perform impressively in in-domain evaluation, but experience a substantial drop in the cross-domain setting, indicating limited generalization capacity. Further results over a novel linguistic probe dataset show that there is substantial room for improvement, especially in the cross- domain setting.
- Published
- 2021
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