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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 6 Hits 1 – 20 of 110 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) Abstract: Relation extraction tasks aim to predict potential relations between entities in a target sentence. As entity mentions have ambiguity in sentences, some important contextual information can guide the semantic representation of entity mentions to improve the accuracy of relation extraction. However, most existing relation extraction models ignore the semantic guidance of contextual information to entity mentions and treat entity mentions in and the textual context of a sentence equally. This results in low-accuracy relation extractions. To address this problem, we propose a contextual semantic-guided entity-centric graph convolutional network (CEGCN) model that enables entity mentions to obtain semantic-guided contextual information for more accurate relational representations. This model develops a self-attention enhanced neural network to concentrate on the importance and relevance of different words to obtain semantic-guided contextual information. Then, we employ a dependency tree with entities as global nodes and add virtual edges to construct an entity-centric logical adjacency matrix (ELAM). This matrix can enable entities to aggregate the semantic-guided contextual information with a one-layer GCN calculation. The experimental results on the TACRED and SemEval-2010 Task 8 datasets show that our model can efficiently use semantic-guided contextual information to enrich semantic entity representations and outperform previous models. Keyword: graph convolutional network; machine learning; natural language processing; relation extraction URL: https://doi.org/10.3390/math10081344 BASE Hide 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 BASE Show 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 6

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