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Inferring modulators of genetic interactions with epistatic nested effects models., , , , , and . PLoS Computational Biology, (2017)Measuring the Effect of Conversational Aspects on Machine Translation Quality., , and . COLING, page 2571-2581. ACL, (2016)Five Shades of Noise: Analyzing Machine Translation Errors in User-Generated Text., , and . NUT@IJCNLP, page 28-37. Association for Computational Linguistics, (2015)A Simple but Effective Approach to Improve Arabizi-to-English Statistical Machine Translation., , and . NUT@COLING, page 43-50. The COLING 2016 Organizing Committee, (2016)Evaluation of Machine Translation Performance Across Multiple Genres and Languages., , and . LREC, European Language Resources Association (ELRA), (2018)Dynamic Data Selection for Neural Machine Translation., , and . EMNLP, page 1400-1410. Association for Computational Linguistics, (2017)Do Transformer Attention Heads Provide Transparency in Abstractive Summarization?, , , , and . CoRR, (2019)Translation Model Adaptation Using Genre-Revealing Text Features., , and . DiscoMT@EMNLP, page 132-141. Association for Computational Linguistics, (2015)What's in a Domain? Analyzing Genre and Topic Differences in Statistical Machine Translation., , , and . ACL (2), page 560-566. The Association for Computer Linguistics, (2015)Understanding Multi-Head Attention in Abstractive Summarization., , , , and . CoRR, (2019)