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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 – 6 of 6 1 Correcting Chinese Spelling Errors with Phonetic Pre-training ... 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; He, Zhongjun; Pang, Chao. - : Underline Science Inc., 2021 BASE Show details 2 ERNIE 3.0: Large-scale Knowledge Enhanced Pre-training for Language Understanding and Generation ... Sun, Yu; Wang, Shuohuan; Feng, Shikun. - : arXiv, 2021 BASE Show details 3 ERNIE-M: Enhanced Multilingual Representation by Aligning Cross-lingual Semantics with Monolingual Corpora ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Ouyang, Xuan; Pang, Chao. - : Underline Science Inc., 2021 BASE Show details 4 ERNIE-M: Enhanced Multilingual Representation by Aligning Cross-lingual Semantics with Monolingual Corpora ... Ouyang, Xuan; Wang, Shuohuan; Pang, Chao; Sun, Yu; Tian, Hao; Wu, Hua; Wang, Haifeng. - : arXiv, 2020 Abstract: Recent studies have demonstrated that pre-trained cross-lingual models achieve impressive performance in downstream cross-lingual tasks. This improvement benefits from learning a large amount of monolingual and parallel corpora. Although it is generally acknowledged that parallel corpora are critical for improving the model performance, existing methods are often constrained by the size of parallel corpora, especially for low-resource languages. In this paper, we propose ERNIE-M, a new training method that encourages the model to align the representation of multiple languages with monolingual corpora, to overcome the constraint that the parallel corpus size places on the model performance. Our key insight is to integrate back-translation into the pre-training process. We generate pseudo-parallel sentence pairs on a monolingual corpus to enable the learning of semantic alignments between different languages, thereby enhancing the semantic modeling of cross-lingual models. Experimental results show that ... : Accepted by EMNLP 2021 (main conference, long paper) ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/2012.15674 https://dx.doi.org/10.48550/arxiv.2012.15674 BASE Hide details 5 BiobankConnect: software to rapidly connect data elements for pooled analysis across biobanks using ontological and lexical indexing Pang, Chao; Hendriksen, Dennis; Dijkstra, Martijn. - : Oxford University Press, 2015 BASE Show details 6 BiobankConnect: software to rapidly connect data elements for pooled analysis across biobanks using ontological and lexical indexing Pang, Chao; Hendriksen, Dennis; Dijkstra, Martijn. - : Oxford University Press, 2015 BASE Show details

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