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Horses to Zebras: Ontology-Guided Data Augmentation and Synthesis for ICD-9 Coding.

, , , and . BioNLP@ACL, page 389-401. Association for Computational Linguistics, (2022)

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Prosody in Cascade and Direct Speech-to-Text Translation: a case study on Korean Wh-Phrases., , , and . EACL (Findings), page 674-683. Association for Computational Linguistics, (2024)Modeling Selectional Preferences of Verbs and Nouns in String-to-Tree Machine Translation., , and . WMT, page 32-42. The Association for Computer Linguistics, (2016)Controlling Politeness in Neural Machine Translation via Side Constraints., , and . HLT-NAACL, page 35-40. The Association for Computational Linguistics, (2016)Toward Making the Most of Context in Neural Machine Translation., , , , and . CoRR, (2020)Exploring Unsupervised Pretraining Objectives for Machine Translation., , , and . ACL/IJCNLP (Findings), volume ACL/IJCNLP 2021 of Findings of ACL, page 2956-2971. Association for Computational Linguistics, (2021)Improving Neural Machine Translation Models with Monolingual Data., , and . ACL (1), The Association for Computer Linguistics, (2016)Cache & Distil: Optimising API Calls to Large Language Models., , , and . ACL (Findings), page 11838-11853. Association for Computational Linguistics, (2024)Document-Level Machine Translation with Large-Scale Public Parallel Corpora., , and . ACL (1), page 13185-13197. Association for Computational Linguistics, (2024)A Latent Morphology Model for Open-Vocabulary Neural Machine Translation., , and . ICLR, OpenReview.net, (2020)Evaluating Discourse Phenomena in Neural Machine Translation., , , and . CoRR, (2017)