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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 Page: 1 2 3 4 5...7 Hits 1 – 20 of 131 1 Integrating Vectorized Lexical Constraints for Neural Machine Translation ... Wang, Shuo; Tan, Zhixing; Liu, Yang. - : arXiv, 2022 BASE Show details 2 Contextual Semantic-Guided Entity-Centric GCN for Relation Extraction Jun Long; Lei Liu; Hongxiao Fei; Yiping Xiang; Haoran Li; Wenti Huang; Liu Yang In: Mathematics; Volume 10; Issue 8; Pages: 1344 (2022) BASE Show details 3 Virtual Reality-Integrated Immersion-Based Teaching to English Language Learning Outcome Xie, Yu; Liu, Yang; Zhang, Fengrui... In: Front Psychol (2022) BASE Show details 4 Unframing and reframing shanshui Liu, Yang. - 2022 BASE Show details 5 Alternated Training with Synthetic and Authentic Data for Neural Machine Translation ... Jiao, Rui; Yang, Zonghan; Sun, Maosong. - : arXiv, 2021 BASE Show details 6 CPM-2: Large-scale Cost-effective Pre-trained Language Models ... Zhang, Zhengyan; Gu, Yuxian; Han, Xu. - : arXiv, 2021 BASE Show details 7 VISITRON: Visual Semantics-Aligned Interactively Trained Object-Navigator ... Shrivastava, Ayush; Gopalakrishnan, Karthik; Liu, Yang. - : arXiv, 2021 BASE Show details 8 Assessing Multilingual Fairness in Pre-trained Multimodal Representations ... Wang, Jialu; Liu, Yang; Wang, Xin Eric. - : arXiv, 2021 BASE Show details 9 Dialog{S}um: {A} Real-Life Scenario Dialogue Summarization Dataset ... 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; Chen, Yulong; Chen, Liang. - : Underline Science Inc., 2021 BASE Show details 10 Transfer Learning for Sequence Generation: from Single-source to Multi-source ... 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; Huang, Xuancheng; Liu, Yang. - : Underline Science Inc., 2021 BASE Show details 11 Mask-Align: Self-Supervised Neural Word Alignment ... 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; Chen, Chi; Liu, Yang. - : Underline Science Inc., 2021 BASE Show details 12 Segment, Mask, and Predict: Augmenting Chinese Word Segmentation with Self-Supervision ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Chen, Gang; Huang, Kaiyu. - : Underline Science Inc., 2021 BASE Show details 13 Learning to Selectively Learn for Weakly-supervised Paraphrase Generation ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Ding , Kaize; Fan, Xing. - : Underline Science Inc., 2021 BASE Show details 14 SWSR: A Chinese Dataset and Lexicon for Online Sexism Detection ... Jiang, Aiqi; Yang, Xiaohan; Liu, Yang. - : arXiv, 2021 BASE Show details 15 Analyzing the Limits of Self-Supervision in Handling Bias in Language ... Bauer, Lisa; Gopalakrishnan, Karthik; Gella, Spandana. - : arXiv, 2021 BASE Show details 16 Statistically significant detection of semantic shifts using contextual word embeddings ... Liu, Yang; Medlar, Alan; Glowacka, Dorota. - : arXiv, 2021 Abstract: Detecting lexical semantic change in smaller data sets, e.g. in historical linguistics and digital humanities, is challenging due to a lack of statistical power. This issue is exacerbated by non-contextual embedding models that produce one embedding per word and, therefore, mask the variability present in the data. In this article, we propose an approach to estimate semantic shift by combining contextual word embeddings with permutation-based statistical tests. We use the false discovery rate procedure to address the large number of hypothesis tests being conducted simultaneously. We demonstrate the performance of this approach in simulation where it achieves consistently high precision by suppressing false positives. We additionally analyze real-world data from SemEval-2020 Task 1 and the Liverpool FC subreddit corpus. We show that by taking sample variation into account, we can improve the robustness of individual semantic shift estimates without degrading overall performance. ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://dx.doi.org/10.48550/arxiv.2104.03776 https://arxiv.org/abs/2104.03776 BASE Hide details 17 SWSR: A Chinese Dataset and Lexicon for Online Sexism Detection ... Jiang, Aiqi; Xiaohan Yang; Liu, Yang. - : Zenodo, 2021 BASE Show details 18 Statistically Significant Detection of Semantic Shifts using Contextual Word Embeddings ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Dorota; Liu, Yang. - : Underline Science Inc., 2021 BASE Show details 19 Leveraging Word-Formation Knowledge for Chinese Word Sense Disambiguation ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Chen, Deli; Dai, Damai. - : Underline Science Inc., 2021 BASE Show details 20 SWSR: A Chinese Dataset and Lexicon for Online Sexism Detection ... Jiang, Aiqi; Xiaohan Yang; Liu, Yang. - : Zenodo, 2021 BASE Show details Page: 1 2 3 4 5...7

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