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Alexander M. Rush
Associate Professor
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My research group studies data-driven, probabilistic systems for natural language processing and generation. We are interested in empirically accurate methods that, when possible, are rooted in data and guided by efficient inference. Our recent work has focused on the intersection of deep learning and structured prediction, with an application focus on text generation and document-level understanding.
Papers103 papers
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ACL, pp.2615-2635, (2020)
Thierry Tambe, Coleman Hooper, Lillian Pentecost, En-Yu Yang,Marco Donato, Victor Sanh,Alexander M. Rush,David Brooks,Gu-Yeon Wei
Journal of Chemical Information and Modeling, (2020)
empirical methods in natural language processing, pp.5547-5552, (2020)
NeurIPS, (2020)
NeurIPS, (2020)
ACL, pp.2731-2743, (2020)
Meeting of the Association for Computational Linguistics, (2019)
ACL (3), pp.111-116, (2019)
arXiv: Computation and Language, (2019)
Fritz Obermeyer, Eli Bingham,Martin Jankowiak, Justin Chiu, Neeraj Pradhan,Alexander M. Rush,Noah Goodman
arXiv: Machine Learning, (2019)
J. Chem. Inf. Model., no. 7 (2019): 3457-3462
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