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PheMT: A Phenomenon-wise Dataset for Machine Translation Robustness on User-Generated Contents.

, , , , , , and . COLING, page 5929-5943. International Committee on Computational Linguistics, (2020)

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PheMT: A Phenomenon-wise Dataset for Machine Translation Robustness on User-Generated Contents., , , , , , and . COLING, page 5929-5943. International Committee on Computational Linguistics, (2020)Overview of the 9th Workshop on Asian Translation., , , , , , , , , and 4 other author(s). WAT@COLING, page 1-36. International Conference on Computational Linguistics, (2022)Fashion Culture Database: Construction of Database for World-wide Fashion Analysis., , , , , , , , , and . ICARCV, page 1721-1726. IEEE, (2018)Chat Translation Error Detection for Assisting Cross-lingual Communications., , , , , , and . Eval4NLP, page 88-95. Association for Computational Linguistics, (2022)cvpaper.challenge in 2015 - A review of CVPR2015 and DeepSurvey., , , , , , , , , and 2 other author(s). CoRR, (2016)Changing Fashion Cultures., , , , , and . CoRR, (2017)Topicalization in Language Models: A Case Study on Japanese., , , , and . COLING, page 851-862. International Committee on Computational Linguistics, (2022)Ten-Million-Order Human Database for World-Wide Fashion Culture Analysis., , , , and . CVPR Workshops, page 305-312. Computer Vision Foundation / IEEE, (2019)Collaborative Descriptors: Convolutional Maps for Preprocessing., , , and . CoRR, (2017)Multi-dialect Neural Machine Translation and Dialectometry., , , and . PACLIC, Association for Computational Linguistics, (2018)