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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 Dynamic Knowledge Distillation for Pre-trained Language Models ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Li, Lei. - : Underline Science Inc., 2021 BASE Show details 2 Text AutoAugment: Learning Compositional Augmentation Policy for Text Classification ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Li, Lei; Ren, Shuhuai; Sun, Xu; Zhang, Jinchao; Zhou, Jie. - : Underline Science Inc., 2021 Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.711/ Abstract: Data augmentation aims to enrich training samples for alleviating the overfitting issue in low-resource or class-imbalanced situations. Traditional methods first devise task-specific operations such as Synonym Substitute, then preset the corresponding parameters such as the substitution rate artificially, which require a lot of prior knowledge and are prone to fall into the sub-optimum. Besides, the number of editing operations is limited in the previous methods, which decreases the diversity of the augmented data and thus restricts the performance gain. To overcome the above limitations, we propose a framework named Text AutoAugment (TAA) to establish a compositional and learnable paradigm for data augmentation. We regard a combination of various operations as an augmentation policy and utilize an efficient Bayesian Optimization algorithm to automatically search for the best policy, which substantially improves the generalization ... Keyword: Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Natural Language Processing URL: https://dx.doi.org/10.48448/a210-qg54 https://underline.io/lecture/37434-text-autoaugment-learning-compositional-augmentation-policy-for-text-classification BASE Hide details 3 Multilingual Translation via Grafting Pre-trained Language Models ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Li, Lei; Sun, Zewei. - : Underline Science Inc., 2021 BASE Show details 4 Counter-Interference Adapter for Multilingual Machine Translation ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Feng, Jiangtao; Li, Lei. - : Underline Science Inc., 2021 BASE Show details 5 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

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