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Paraphrase Lattice for Statistical Machine Translation.

, , and . ACL (2), page 1-5. The Association for Computer Linguistics, (2010)

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Burmese (Myanmar) Name Romanization: A Sub-syllabic Segmentation Scheme for Statistical Solutions., , , and . PACLING, volume 781 of Communications in Computer and Information Science, page 191-202. Springer, (2017)Question Answering System Using Syntactic Information, , and . NCSTRL archive xxx.cs.CL/9911006, (1999)Universal Multimodal Representation for Language Understanding., , , , , , and . IEEE Trans. Pattern Anal. Mach. Intell., 45 (7): 9169-9185 (July 2023)Japanese Word Sense Disambiguation using the Simple Bayes and Support Vector Machine Methods., , , , and . SENSEVAL@ACL, page 135-138. Association for Computational Linguistics, (2001)Context-Aware Smoothing for Neural Machine Translation., , , , and . IJCNLP(1), page 11-20. Asian Federation of Natural Language Processing, (2017)Integrating Prior Translation Knowledge Into Neural Machine Translation., , , and . IEEE ACM Trans. Audio Speech Lang. Process., (2022)Empircal dependency-based head finalization for statistical Chinese-, English-, and French-to-Myanmar (Burmese) machine translation., , , , and . IWSLT, (2014)Risk-aware distribution of SMT outputs for translation of documents targeting many anonymous readers., , and . IWSLT, (2015)Language Model Pre-training on True Negatives., , , and . AAAI, page 14002-14010. AAAI Press, (2023)Multi-Source Cross-Lingual Constituency Parsing., , , , , and . ICON, page 341-346. NLP Association of India (NLPAI), (2021)