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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 Chase: A Large-Scale and Pragmatic Chinese Dataset for Cross-Database Context-Dependent Text-to-SQL ... 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; Fan, mingfan@mail.xjtu.edu.cn; Guo, Jiaqi. - : Underline Science Inc., 2021 BASE Show details 2 GL-GIN: Fast and Accurate Non-Autoregressive Model for Joint Multiple Intent Detection and Slot Filling ... 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; Che, Wanxiang; Liu, Ting. - : Underline Science Inc., 2021 BASE Show details 3 A Closer Look into the Robustness of Neural Dependency Parsers Using Better Adversarial Examples ... 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; Che, Wanxiang; Cohen, Shay B.. - : Underline Science Inc., 2021 BASE Show details 4 Dynamic Connected Networks for Chinese Spelling Check ... 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; Che, Wanxiang; Hu , Guoping; Liu, Ting; Wang, Shijin; Wang, Baoxin; Wu, Dayong. - : Underline Science Inc., 2021 Abstract: Read paper: https://www.aclanthology.org/2021.findings-acl.216 Abstract: Chinese spelling check (CSC) is a task to detect and correct spelling errors in Chinese text. Most state-of-the-art works on the CSC task adopt a BERT-based non-autoregressive language model, which relies on the output independence assumption. The inappropriate independence assumption prevents BERT-based models from learning the dependencies among target tokens, resulting in an incoherent problem. To address the above issue, we propose a novel architecture named Dynamic Connected Networks (DCN), which generates the candidate Chinese characters via a Pinyin Enhanced Candidate Generator and then utilizes an attention-based network to model the dependencies between two adjacent Chinese characters. The experimental results show that our proposed method achieves a new state-of-the-art performance on three human-annotated datasets. ... Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics URL: https://underline.io/lecture/26307-dynamic-connected-networks-for-chinese-spelling-check https://dx.doi.org/10.48448/k2y4-6q18 BASE Hide details 5 Learning to Bridge Metric Spaces: Few-shot Joint Learning of Intent Detection and Slot Filling ... 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; Che, Wanxiang; Chen, Cheng. - : Underline Science Inc., 2021 BASE Show details

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