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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 – 6 of 6 1 Multi-perspective Coherent Reasoning for Helpfulness Prediction of Multimodal Reviews ... 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; Bing, Lidong; Hai, Zhen. - : Underline Science Inc., 2021 BASE Show details 2 On the Effectiveness of Adapter-based Tuning for Pretrained Language Model Adaptation ... 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; Bing, Lidong; Cheng, liying.cheng@alibaba-inc.com. - : Underline Science Inc., 2021 BASE Show details 3 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. - : Underline Science Inc., 2021 BASE Show details 4 Argument Pair Extraction via Attention-guided Multi-Layer Multi-Cross Encoding ... 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; Bing, Lidong; Cheng, Liying; Si, Luo; Wu, Tianyu. - : Underline Science Inc., 2021 Abstract: Read paper: https://www.aclanthology.org/2021.acl-long.496 Abstract: Argument pair extraction (APE) is a research task for extracting arguments from two passages and identifying potential argument pairs. Prior research work treats this task as a sequence labeling problem and a binary classification problem on two passages that are directly concatenated together, which has a limitation of not fully utilizing the unique characteristics and inherent relations of two different passages. This paper proposes a novel attention-guided multi-layer multi-cross encoding scheme to address the challenges. The new model processes two passages with two individual sequence encoders and updates their representations using each other’s representations through attention. In addition, the pair prediction part is formulated as a table-filling problem by updating the representations of two sequences’ Cartesian product. Furthermore, an auxiliary attention loss is introduced to guide each argument to align to its paired argument. ... Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics URL: https://underline.io/lecture/25947-argument-pair-extraction-via-attention-guided-multi-layer-multi-cross-encoding https://dx.doi.org/10.48448/4zy3-v919 BASE Hide details 5 Learning Span-Level Interactions for Aspect Sentiment Triplet 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; Bing, Lidong; Chia, Yew Ken. - : Underline Science Inc., 2021 BASE Show details 6 MulDA: A Multilingual Data Augmentation Framework for Low-Resource Cross-Lingual NER ... 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; Bing, Lidong; Ding, Bosheng. - : Underline Science Inc., 2021 BASE Show details

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