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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 – 3 of 3 1 Cross-lingual Aspect-based Sentiment Analysis with Aspect Term Code-Switching ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Wai; Bing, Lidong. - : Underline Science Inc., 2021 BASE Show details 2 Towards Generative Aspect-Based Sentiment Analysis ... 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; ., Wai; Bing, Lidong; Deng, Yang; Li, Xin; Zhang, Wenxuan. - : Underline Science Inc., 2021 Abstract: Read paper: https://www.aclanthology.org/2021.acl-short.64 Abstract: Aspect-based sentiment analysis (ABSA) has received increasing attention recently. Most existing work tackles ABSA in a discriminative manner, designing various task-specific classification networks for the prediction. Despite their effectiveness, these methods ignore the rich label semantics in ABSA problems and require extensive task-specific designs. In this paper, we propose to tackle various ABSA tasks in a unified generative framework. Two types of paradigms, namely annotation-style and extraction-style modeling, are designed to enable the training process by formulating each ABSA task as a text generation problem. We conduct experiments on four ABSA tasks across multiple benchmark datasets where our proposed generative approach achieves new state-of-the-art results in almost all cases. This also validates the strong generality of the proposed framework which can be easily adapted to arbitrary ABSA task without additional ... Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics URL: https://dx.doi.org/10.48448/kr6a-6s64 https://underline.io/lecture/25603-towards-generative-aspect-based-sentiment-analysis BASE Hide details 3 Unsupervised Cross-lingual Adaptation for Sequence Tagging and Beyond ... Li, Xin; Bing, Lidong; Zhang, Wenxuan. - : arXiv, 2020 BASE Show details

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