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    • Wu, Shijie (11)
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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 11 of 11 1 Differentiable Generative Phonology ... Wu, Shijie; Ponti, Edoardo Maria; Cotterell, Ryan. - : arXiv, 2021 BASE Show details 2 Applying the Transformer to Character-level Transduction ... Wu, Shijie; Cotterell, Ryan; Hulden, Mans. - : ETH Zurich, 2021 BASE Show details 3 Everything Is All It Takes: A Multipronged Strategy for Zero-Shot Cross-Lingual Information Extraction ... Yarmohammadi, Mahsa; Wu, Shijie; Marone, Marc; Xu, Haoran; Ebner, Seth; Qin, Guanghui; Chen, Yunmo; Guo, Jialiang; Harman, Craig; Murray, Kenton; White, Aaron Steven; Dredze, Mark; Van Durme, Benjamin. - : arXiv, 2021 Abstract: Zero-shot cross-lingual information extraction (IE) describes the construction of an IE model for some target language, given existing annotations exclusively in some other language, typically English. While the advance of pretrained multilingual encoders suggests an easy optimism of "train on English, run on any language", we find through a thorough exploration and extension of techniques that a combination of approaches, both new and old, leads to better performance than any one cross-lingual strategy in particular. We explore techniques including data projection and self-training, and how different pretrained encoders impact them. We use English-to-Arabic IE as our initial example, demonstrating strong performance in this setting for event extraction, named entity recognition, part-of-speech tagging, and dependency parsing. We then apply data projection and self-training to three tasks across eight target languages. Because no single set of techniques performs the best across all tasks, we encourage ... : EMNLP 2021 ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://dx.doi.org/10.48550/arxiv.2109.06798 https://arxiv.org/abs/2109.06798 BASE Hide details 4 Applying the Transformer to Character-level Transduction Cotterell, Ryan; Hulden, Mans; Wu, Shijie In: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume (2021) BASE Show details 5 Do Explicit Alignments Robustly Improve Multilingual Encoders? ... Wu, Shijie; Dredze, Mark. - : arXiv, 2020 BASE Show details 6 SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection ... Vylomova, Ekaterina; White, Jennifer; Salesky, Elizabeth. - : arXiv, 2020 BASE Show details 7 Are All Languages Created Equal in Multilingual BERT? ... Wu, Shijie; Dredze, Mark. - : arXiv, 2020 BASE Show details 8 The Paradigm Discovery Problem ... Erdmann, Alexander; Elsner, Micha; Wu, Shijie. - : ETH Zurich, 2020 BASE Show details 9 The Paradigm Discovery Problem Wu, Shijie; Habash, Nizar; Elsner, Micha... In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020) BASE Show details 10 Emerging Cross-lingual Structure in Pretrained Language Models ... Wu, Shijie; Conneau, Alexis; Li, Haoran. - : arXiv, 2019 BASE Show details 11 The SIGMORPHON 2019 Shared Task: Morphological Analysis in Context and Cross-Lingual Transfer for Inflection ... McCarthy, Arya D.; Vylomova, Ekaterina; Wu, Shijie. - : arXiv, 2019 BASE Show details

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