Showing 501 - 520 results of 979 for search '"computational linguistics"', query time: 0.12s Refine Results
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    Graphie: A graph-based framework for information extraction by Qian, Y, Santus, E, Jin, Z, Guo, J, Barzilay, R

    Published 2021
    “…© 2019 Association for Computational Linguistics Most modern Information Extraction (IE) systems are implemented as sequential taggers and only model local dependencies. …”
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  4. 504

    Structural Supervision Improves Learning of Non-Local Grammatical Dependencies by Wilcox, Ethan, Qian, Peng, Futrell, Richard, Ballesteros, Miguel, Levy, Roger P

    Published 2022
    “…© 2019 Association for Computational Linguistics State-of-the-art LSTM language models trained on large corpora learn sequential contingencies in impressive detail and have been shown to acquire a number of non-local grammatical dependencies with some success. …”
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    Inferring Which Medical Treatments Work from Reports of Clinical Trials by Lehman, Eric, DeYoung, Jay, Barzilay, Regina, Wallace, Byron C

    Published 2022
    “…© 2019 Association for Computational Linguistics How do we know if a particular medical treatment actually works? …”
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    Semi-Automatic Construction of a Readability Corpus for the Vietnamese Language by An-Vinh Luong, Dien Dinh

    Published 2022-11-01
    “…While text readability has been a focus in research on computational linguistics for English and other resource-rich languages, there is still little work on this subject in understudied languages like Vietnamese. …”
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    Multi-Source Domain Adaptation with Mixture of Experts by Guo, Jiang, Shah, Darsh, Barzilay, Regina

    Published 2021
    “…© 2018 Association for Computational Linguistics We propose a mixture-of-experts approach for unsupervised domain adaptation from multiple sources. …”
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    Learning Personas from Dialogue with Attentive Memory Networks by Chu, Eric, Vijayaraghavan, Prashanth, Roy, Deb

    Published 2021
    “…© 2018 Association for Computational Linguistics The ability to infer persona from dialogue can have applications in areas ranging from computational narrative analysis to personalized dialogue generation. …”
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