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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 12 of 12 1 Building Robust Spoken Language Understanding by Cross Attention between Phoneme Sequence and ASR Hypothesis ... Wang, Zexun; Le, Yuquan; Zhu, Yi. - : arXiv, 2022 BASE Show details 2 An Unsupervised Method for Building Sentence Simplification Corpora in Multiple Languages ... Lu, Xinyu; Qiang, Jipeng; Li, Yun. - : arXiv, 2021 BASE Show details 3 An Unsupervised Method for Building Sentence Simplification Corpora in Multiple Languages ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Li, Yun; Lu, Xinyu; Qiang, Jipeng; Yuan, Yunhao; Zhu, Yi. - : Underline Science Inc., 2021 Abstract: The availability of parallel sentence simplification (SS) is scarce for neural SS modelings. We propose an unsupervised method to build SS corpora from large-scale bilingual translation corpora, alleviating the need for SS supervised corpora. Our method is motivated by the following two findings: neural machine translation model usually tends to generate more high-frequency tokens and the difference of text complexity levels exists between the source and target language of a translation corpus. By taking the pair of the source sentences of translation corpus and the translations of their references in a bridge language, we can construct large-scale pseudo parallel SS data. Then, we keep these sentence pairs with a higher complexity difference as SS sentence pairs. The building SS corpora with an unsupervised approach can satisfy the expectations that the aligned sentences preserve the same meanings and have difference in text complexity levels. Experimental results show that SS methods trained by our corpora ... URL: https://dx.doi.org/10.48448/bsjw-4x44 https://underline.io/lecture/38344-an-unsupervised-method-for-building-sentence-simplification-corpora-in-multiple-languages BASE Hide details 4 Combining Deep Generative Models and Multi-lingual Pretraining for Semi-supervised Document Classification ... Zhu, Yi; Shareghi, Ehsan; Li, Yingzhen. - : arXiv, 2021 BASE Show details 5 A Closer Look at Few-Shot Crosslingual Transfer: The Choice of Shots Matters ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; ., Hinrich; Korhonen, Anna. - : Underline Science Inc., 2021 BASE Show details 6 A Closer Look at Few-Shot Crosslingual Transfer: The Choice of Shots Matters ... Zhao, Mengjie; Zhu, Yi; Shareghi, Ehsan. - : arXiv, 2020 BASE Show details 7 LSBert: A Simple Framework for Lexical Simplification ... Qiang, Jipeng; Li, Yun; Zhu, Yi. - : arXiv, 2020 BASE Show details 8 Assessment of a biofluid mechanics-based model for calculating portal pressure in canines Lin, Jia-Yun; Zhang, Chi-Hao; Zheng, Lei... In: BMC Vet Res (2020) BASE Show details 9 Facing the challenges in ophthalmology clerkship teaching: Is flipped classroom the answer? Lin, Ying; Zhu, Yi; Chen, Chuan. - : Public Library of Science, 2017 BASE Show details 10 Dependency Parsing for Tweets Zhu, Yi. - 2017 BASE Show details 11 The Interpretation of Chinese Couplets' Syntactic Features: A Comparative Study of Two English Translation Versions of Xiyou Ji** Zhu, Yi. - : The University of Queensland, School of Languages and Cultures, 2015 BASE Show details 12 OntoPDF: using a text mining pipeline to generate enriched PDF versions of scientific papers Zhu, Yi; Rinaldi, Fabio In: Zhu, Yi; Rinaldi, Fabio (2014). OntoPDF: using a text mining pipeline to generate enriched PDF versions of scientific papers. In: 6th International Symposium on Semantic Mining in Biomedicine, Aveiro, Portugal, 6 October 2014 - 7 October 2014, 85-89. (2014) BASE Show details

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