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1
Integrating Vectorized Lexical Constraints for Neural Machine Translation ...
Wang, Shuo; Tan, Zhixing; Liu, Yang. - : arXiv, 2022
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2
Contextual Semantic-Guided Entity-Centric GCN for Relation Extraction
In: Mathematics; Volume 10; Issue 8; Pages: 1344 (2022)
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3
Virtual Reality-Integrated Immersion-Based Teaching to English Language Learning Outcome
In: Front Psychol (2022)
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4
Unframing and reframing shanshui
Liu, Yang. - 2022
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5
Alternated Training with Synthetic and Authentic Data for Neural Machine Translation ...
Jiao, Rui; Yang, Zonghan; Sun, Maosong. - : arXiv, 2021
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6
CPM-2: Large-scale Cost-effective Pre-trained Language Models ...
Zhang, Zhengyan; Gu, Yuxian; Han, Xu. - : arXiv, 2021
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7
VISITRON: Visual Semantics-Aligned Interactively Trained Object-Navigator ...
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8
Assessing Multilingual Fairness in Pre-trained Multimodal Representations ...
Wang, Jialu; Liu, Yang; Wang, Xin Eric. - : arXiv, 2021
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9
Dialog{S}um: {A} Real-Life Scenario Dialogue Summarization Dataset ...
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10
Transfer Learning for Sequence Generation: from Single-source to Multi-source ...
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11
Mask-Align: Self-Supervised Neural Word Alignment ...
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12
Segment, Mask, and Predict: Augmenting Chinese Word Segmentation with Self-Supervision ...
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13
Learning to Selectively Learn for Weakly-supervised Paraphrase Generation ...
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14
SWSR: A Chinese Dataset and Lexicon for Online Sexism Detection ...
Abstract: Online sexism has become an increasing concern in social media platforms as it has affected the healthy development of the Internet and can have negative effects in society. While research in the sexism detection domain is growing, most of this research focuses on English as the language and on Twitter as the platform. Our objective here is to broaden the scope of this research by considering the Chinese language on Sina Weibo. We propose the first Chinese sexism dataset -- Sina Weibo Sexism Review (SWSR) dataset --, as well as a large Chinese lexicon SexHateLex made of abusive and gender-related terms. We introduce our data collection and annotation process, and provide an exploratory analysis of the dataset characteristics to validate its quality and to show how sexism is manifested in Chinese. The SWSR dataset provides labels at different levels of granularity including (i) sexism or non-sexism, (ii) sexism category and (iii) target type, which can be exploited, among others, for building computational ... : 44 pages, 5 figure, 9 tables ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://arxiv.org/abs/2108.03070
https://dx.doi.org/10.48550/arxiv.2108.03070
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15
Analyzing the Limits of Self-Supervision in Handling Bias in Language ...
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16
Statistically significant detection of semantic shifts using contextual word embeddings ...
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17
SWSR: A Chinese Dataset and Lexicon for Online Sexism Detection ...
Jiang, Aiqi; Xiaohan Yang; Liu, Yang. - : Zenodo, 2021
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18
Statistically Significant Detection of Semantic Shifts using Contextual Word Embeddings ...
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19
Leveraging Word-Formation Knowledge for Chinese Word Sense Disambiguation ...
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20
SWSR: A Chinese Dataset and Lexicon for Online Sexism Detection ...
Jiang, Aiqi; Xiaohan Yang; Liu, Yang. - : Zenodo, 2021
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