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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 – 5 of 5 1 FALCON: Fast Visual Concept Learning by Integrating Images, Linguistic descriptions, and Conceptual Relations ... Mei, Lingjie; Mao, Jiayuan; Wang, Ziqi. - : arXiv, 2022 BASE Show details 2 CLEVE: Contrastive Pre-training for Event Extraction ... 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; Han, Xu; Hou, Lei; Li, Juanzi; Li, Peng; Lin, Yankai; Liu, Zhiyuan; Wang, Ziqi; Wang, Xiaozhi; Zhou, Jie. - : Underline Science Inc., 2021 Abstract: Read paper: https://www.aclanthology.org/2021.acl-long.491 Abstract: Event extraction (EE) has considerably benefited from pre-trained language models (PLMs) by fine-tuning. However, existing pre-training methods have not involved modeling event characteristics, resulting in the developed EE models cannot take full advantage of large-scale unsupervised data. To this end, we propose CLEVE, a contrastive pre-training framework for EE to better learn event knowledge from large unsupervised data and their semantic structures (e.g. AMR) obtained with automatic parsers. CLEVE contains a text encoder to learn event semantics and a graph encoder to learn event structures respectively. Specifically, the text encoder learns event semantic representations by self-supervised contrastive learning to represent the words of the same events closer than those unrelated words; the graph encoder learns event structure representations by graph contrastive pre-training on parsed event-related semantic structures. The two ... Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics URL: https://underline.io/lecture/25941-cleve-contrastive-pre-training-for-event-extraction https://dx.doi.org/10.48448/pjm0-5118 BASE Hide details 3 Review on the Application of Metalearning in Artificial Intelligence Ma, Pengfei; Zhang, Zunqian; Wang, Jiahao... In: Comput Intell Neurosci (2021) BASE Show details 4 Learning from Explanations with Neural Execution Tree ... Wang, Ziqi; Qin, Yujia; Zhou, Wenxuan. - : arXiv, 2019 BASE Show details 5 A Python-based Interface for Wide Coverage Lexicalized Tree-adjoining Grammars Wang Ziqi; Zhang Haotian; Sarkar Anoop In: Prague Bulletin of Mathematical Linguistics , Vol 103, Iss 1, Pp 139-159 (2015) (2015) BASE Show details

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