@inproceedings{0c3aa174353c4cb0be34722c2f95a6e4,
title = "Breaking NLI systems with sentences that require simple lexical inferences",
abstract = "We create a new NLI test set that shows the deficiency of state-of-the-art models in inferences that require lexical and world knowledge. The new examples are simpler than the SNLI test set, containing sentences that differ by at most one word from sentences in the training set. Yet, the performance on the new test set is substantially worse across systems trained on SNLI, demonstrating that these systems are limited in their generalization ability, failing to capture many simple inferences.",
author = "Max Glockner and Vered Shwartz and Yoav Goldberg",
note = "Publisher Copyright: {\textcopyright} 2018 Association for Computational Linguistics; 56th Annual Meeting of the Association for Computational Linguistics, ACL 2018 ; Conference date: 15-07-2018 Through 20-07-2018",
year = "2018",
month = jan,
day = "1",
doi = "10.18653/v1/p18-2103",
language = "الإنجليزيّة",
series = "ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers)",
publisher = "Association for Computational Linguistics (ACL)",
pages = "650--655",
booktitle = "ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Short Papers)",
address = "الولايات المتّحدة",
}