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Efficient Large Scale Language Modeling with Mixtures of Experts., , , , , , , , , and 14 other author(s). EMNLP, page 11699-11732. Association for Computational Linguistics, (2022)Efficient Large Scale Language Modeling with Mixtures of Experts, , , , , , , , , and 14 other author(s). (2021)cite arxiv:2112.10684Comment: EMNLP 2022.Facebook AI's WMT21 News Translation Task Submission., , , , , and . WMT@EMNLP, page 205-215. Association for Computational Linguistics, (2021)Language Models not just for Pre-training: Fast Online Neural Noisy Channel Modeling., , , and . WMT@EMNLP, page 584-593. Association for Computational Linguistics, (2020)Data Selection Curriculum for Neural Machine Translation., , , , , and . EMNLP (Findings), page 1569-1582. Association for Computational Linguistics, (2022)Few-shot Learning with Multilingual Generative Language Models., , , , , , , , , and 11 other author(s). EMNLP, page 9019-9052. Association for Computational Linguistics, (2022)Causes and Cures for Interference in Multilingual Translation., , , , and . ACL (1), page 15849-15863. Association for Computational Linguistics, (2023)Effective Long-Context Scaling of Foundation Models., , , , , , , , , and 11 other author(s). NAACL-HLT, page 4643-4663. Association for Computational Linguistics, (2024)No Language Left Behind: Scaling Human-Centered Machine Translation., , , , , , , , , and 28 other author(s). CoRR, (2022)The Llama 3 Herd of Models, , , , , , , , , and 523 other author(s). (2024)