Difference between revisions of "2019 DialogueNaturalLanguageInferenc"
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Revision as of 01:23, 13 September 2019
- (Welleck et al., 2019) ⇒ Sean Welleck, Jason Weston, Arthur Szlam, and Kyunghyun Cho. (2019). “Dialogue Natural Language Inference.” In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019).
Consistency is a long standing issue faced by dialogue models. In this paper, we frame the consistency of dialogue agents as natural language inference (NLI) and create a new natural language inference dataset called Dialogue NLI. We propose a method which demonstrates that a model trained on Dialogue NLI can be used to improve the consistency of a dialogue model, and evaluate the method with human evaluation and with automatic metrics on a suite of evaluation sets designed to measure a dialogue modelâs consistency.
|2019 DialogueNaturalLanguageInferenc||Sean Welleck|
|Dialogue Natural Language Inference||2019|