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        <title>Breaking NLI Systems with Sentences that Require Simple Lexical Inferences</title>
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        <namePart type="given">Max</namePart>
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            <title>Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)</title>
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            <namePart type="given">Yusuke</namePart>
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    <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.</abstract>
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    <identifier type="doi">10.18653/v1/P18-2103</identifier>
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%0 Conference Proceedings
%T Breaking NLI Systems with Sentences that Require Simple Lexical Inferences
%A Glockner, Max
%A Shwartz, Vered
%A Goldberg, Yoav
%Y Gurevych, Iryna
%Y Miyao, Yusuke
%S Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
%D 2018
%8 July
%I Association for Computational Linguistics
%C Melbourne, Australia
%F glockner-etal-2018-breaking
%X 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.
%R 10.18653/v1/P18-2103
%U https://aclanthology.org/P18-2103/
%U https://doi.org/10.18653/v1/P18-2103
%P 650-655

Markdown (Informal)

[Breaking NLI Systems with Sentences that Require Simple Lexical Inferences](https://aclanthology.org/P18-2103/) (Glockner et al., ACL 2018)

• Breaking NLI Systems with Sentences that Require Simple Lexical Inferences (Glockner et al., ACL 2018)

ACL

• Max Glockner, Vered Shwartz, and Yoav Goldberg. 2018. Breaking NLI Systems with Sentences that Require Simple Lexical Inferences. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 650–655, Melbourne, Australia. Association for Computational Linguistics.