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A Feasibility Study of Answer-Agnostic Question Generation for Education ...
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BiSECT: Learning to Split and Rephrase Sentences with Bitexts ...
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"Wikily" Supervised Neural Translation Tailored to Cross-Lingual Tasks ...
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Is "my favorite new movie" my favorite movie? Probing the Understanding of Recursive Noun Phrases ...
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Bilingual is At Least Monolingual (BALM): A Novel Translation Algorithm that Encodes Monolingual Priors ...
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Seeing Things from a Different Angle: Discovering Diverse Perspectives about Claims ...
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Complexity-Weighted Loss and Diverse Reranking for Sentence Simplification ...
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Comparison of Diverse Decoding Methods from Conditional Language Models ...
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Use of Modality and Negation in Semantically-Informed Syntactic MT ...
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Bucking the Trend: Large-Scale Cost-Focused Active Learning for Statistical Machine Translation ...
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Semantically-Informed Syntactic Machine Translation: A Tree-Grafting Approach ...
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Abstract:
We describe a unified and coherent syntactic framework for supporting a semantically-informed syntactic approach to statistical machine translation. Semantically enriched syntactic tags assigned to the target-language training texts improved translation quality. The resulting system significantly outperformed a linguistically naive baseline model (Hiero), and reached the highest scores yet reported on the NIST 2009 Urdu-English translation task. This finding supports the hypothesis (posed by many researchers in the MT community, e.g., in DARPA GALE) that both syntactic and semantic information are critical for improving translation quality---and further demonstrates that large gains can be achieved for low-resource languages with different word order than English. ... : 10 pages, 7 figures, 3 tables; appeared in Proceedings of the Ninth Conference of the Association for Machine Translation in the Americas (AMTA), October 2010 ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences; I.2.7; I.2.6; I.5.1; I.5.4; Machine Learning cs.LG; Machine Learning stat.ML
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URL: https://arxiv.org/abs/1409.7085 https://dx.doi.org/10.48550/arxiv.1409.7085
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