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Context-aware machine translation models are designed to leverage contextual information, but often fail to do so.
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Earlier work this paper cites.
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Yujia Bao, Shiyu Chang, Mo Yu, and Regina Barzilay. 2018 · 1913
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Bei Li, Hui Liu, Ziyang Wang, Yufan Jiang, Tong Xiao, Jingbo Zhu, Tongran Liu, and Changliang Li. 2020a · 2005
Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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