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20112022

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  • Can Rationalization Improve Robustness?

    Chen, H., He, J., Narasimhan, K. & Chen, D., 2022, NAACL 2022 - 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference. Association for Computational Linguistics (ACL), p. 3792-3805 14 p. (NAACL 2022 - 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • A Frustratingly Easy Approach for Entity and Relation Extraction

    Zhong, Z. & Chen, D., 2021, NAACL-HLT 2021 - 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference. Association for Computational Linguistics (ACL), p. 50-61 12 p. (NAACL-HLT 2021 - 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    61 Scopus citations
  • Factual Probing Is [MASK]: Learning vs. Learning to Recall

    Zhong, Z., Friedman, D. & Chen, D., 2021, NAACL-HLT 2021 - 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference. Association for Computational Linguistics (ACL), p. 5017-5033 17 p. (NAACL-HLT 2021 - 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    24 Scopus citations
  • Learning dense representations of phrases at scale

    Lee, J., Sung, M., Kang, J. & Chen, D., 2021, ACL-IJCNLP 2021 - 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, Proceedings of the Conference. Association for Computational Linguistics (ACL), p. 6634-6647 14 p. (ACL-IJCNLP 2021 - 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, Proceedings of the Conference).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    15 Scopus citations
  • Making pre-trained language models better few-shot learners

    Gao, T., Fisch, A. & Chen, D., 2021, ACL-IJCNLP 2021 - 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, Proceedings of the Conference. Association for Computational Linguistics (ACL), p. 3816-3830 15 p. (ACL-IJCNLP 2021 - 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, Proceedings of the Conference).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    88 Scopus citations