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A central focus of my research is on how we can teach computers question answering in the form of passing standardized science exams, as written, using a combination of scientific knowledge and common-sense reasoning skills. In particular, I focus on methods of automated inference that generate explanations for why the answer is correct. The Explanation Bank contains many such resources for explanation-centered inference, including WorldTree and EntailmentBank (book), that help power some of the highest-performing language models available, including the Allen Institute for Artificial Intelligence’s GPT3 competitor, MACAW.
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论文共 49 篇作者统计合作学者相似作者
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17TH CONFERENCE OF THE EUROPEAN CHAPTER OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, EACL 2023pp.2777-2788, (2023)
CoRR (2023): 12972-12990
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Conference on Empirical Methods in Natural Language Processing (2023): 5555-5565
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International Conference on Language Resources and Evaluation (LREC)pp.6077-6082, (2022)
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Bhavana Dalvi,Peter Jansen,Oyvind Tafjord, Zhengnan Xie,Hannah Smith, Leighanna Pipatanangkura,Peter E. Clark
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021)
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graph based methods for natural language processingpp.156-165, (2021)
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