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1
A Multi-Level Optimization Framework for End-to-End Text Augmentation
In: Transactions of the Association for Computational Linguistics, Vol 10, Pp 343-358 (2022) (2022)
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2
Syntactic smt using a discriminative text generation model
In: http://aclweb.org/anthology/D/D14/D14-1021.pdf (2014)
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3
Syntactic SMT Using a Discriminative Text Generation Model
In: http://emnlp2014.org/papers/pdf/EMNLP2014021.pdf
Abstract: We study a novel architecture for syntactic SMT. In contrast to the dominant approach in the literature, the system does not rely on translation rules, but treat translation as an unconstrained target sentence gen-eration task, using soft features to cap-ture lexical and syntactic correspondences between the source and target languages. Target syntax features and bilingual trans-lation features are trained consistently in a discriminative model. Experiments us-ing the IWSLT 2010 dataset show that the system achieves BLEU comparable to the state-of-the-art syntactic SMT systems. 1
URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.673.6632
http://emnlp2014.org/papers/pdf/EMNLP2014021.pdf
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4
The ICT ’s Patent MT System Description for NTCIR-9
In: http://research.nii.ac.jp/ntcir/workshop/OnlineProceedings9/NTCIR/19-NTCIR9-PATENTMT-XiongH.pdf
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