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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 Page: 1 2 3 4 5 6 7 8...83 Hits 61 – 80 of 1.655 61 The Effect of Round-Trip Translation on Fairness in Sentiment Analysis ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Christiansen, Jonathan Gabel; Gammelgaard, Mathias Lykke. - : Underline Science Inc., 2021 BASE Show details 62 Multimodal Phased Transformer for Sentiment Analysis ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Cheng, Junyan; Fostiropoulos, Iordanis. - : Underline Science Inc., 2021 BASE Show details 63 MATE: Multi-view Attention for Table Transformer Efficiency ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Cohen, William; Eisenschlos, Julian. - : Underline Science Inc., 2021 BASE Show details 64 Argument Pair Extraction with Mutual Guidance and Inter-sentence Relation Graph ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Bao, Jianzhu; Liang, Bin. - : Underline Science Inc., 2021 BASE Show details 65 Classifying Dyads for Militarized Conflict Analysis ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Ahbab, Samin; Cotterell, Ryan. - : Underline Science Inc., 2021 BASE Show details 66 Joint Multi-modal Aspect-Sentiment Analysis with Auxiliary Cross-modal Relation Detection ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Ju, Xincheng. - : Underline Science Inc., 2021 BASE Show details 67 Comparative Opinion Quintuple Extraction from Product Reviews ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Liu, Ziheng; Xia, Rui. - : Underline Science Inc., 2021 BASE Show details 68 PASTE: A Tagging-Free Decoding Framework Using Pointer Networks for Aspect Sentiment Triplet Extraction ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Bhattacharya, Sourangshu; Butala, Yash. - : Underline Science Inc., 2021 BASE Show details 69 Natural language processing as a tool to identify the Reddit particularities of cancer survivors around the time of diagnosis and remission: A pilot study ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Diana; Boian, Rareș. - : Underline Science Inc., 2021 BASE Show details 70 Does Social Pressure Drive Persuasion in Online Fora? ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Jain, Ayush; Srivastava, Shashank. - : Underline Science Inc., 2021 BASE Show details 71 A Large-Scale Dataset for Empathetic Response Generation ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Pu, Pearl; Welivita, Kalpani Anuradha. - : Underline Science Inc., 2021 BASE Show details 72 YASO: A Targeted Sentiment Analysis Evaluation Dataset for Open-Domain Reviews ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Aharonov, Ranit; Katz, Yoav. - : Underline Science Inc., 2021 BASE Show details 73 Sample Selection Guided by Domain and Task for Cross-Domain Targeted Sentiment Analysis ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Bhattacharjee, Kasturi. - : Underline Science Inc., 2021 BASE Show details 74 Learning Implicit Sentiment in Aspect-based Sentiment Analysis with Supervised Contrastive Pre-Training ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Li, Zhengyan. - : Underline Science Inc., 2021 BASE Show details 75 Improving Multimodal Fusion with Hierarchical Mutual Information Maximization for Multimodal Sentiment Analysis ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Chen, Hui; Han, Wei. - : Underline Science Inc., 2021 BASE Show details 76 Dimensional Emotion Detection from Categorical Emotion ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Jeon, Jaeyeol; Kim, Jiseon. - : Underline Science Inc., 2021 BASE Show details 77 Beta Distribution Guided Aspect-aware Graph for Aspect Category Sentiment Analysis with Affective Knowledge ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Gui, Lin; Liang, Bin. - : Underline Science Inc., 2021 BASE Show details 78 Unimodal and Crossmodal Refinement Network for Multimodal Sequence Fusion ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Guo, Xiaobao. - : Underline Science Inc., 2021 BASE Show details 79 Reinforced Counterfactual Data Augmentation for Dual Sentiment Classification ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Chen, Hao; Xia, Rui. - : Underline Science Inc., 2021 BASE Show details 80 Seeking Common but Distinguishing Difference, A Joint Aspect-based Sentiment Analysis Model ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Jiang, Shu; Jing, Hongjiang; Li, Zuchao; Zhao, Hai. - : Underline Science Inc., 2021 Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.318/ Abstract: Aspect-based sentiment analysis (ABSA) task consists of several subtasks. Aspect sentiment triplet extraction (ASTE) subtask of ABSA was proposed recently which aims to formulate the relevant information into a triplet: target aspect object, opinion clue, and sentiment polarity orientation. However, most of the existing joint models only focus on the benefits of encoder sharing between subtasks but ignore the difference. Therefore, we propose a dual-encoder approach, in which a pair encoder especially focuses on candidate aspect-opinion pair classification, and the original encoder keeps attention on sequence labeling. Empirical results show that our proposed model significantly outperforms the previous state-of-the-art on 8 benchmark datasets. ... Keyword: Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Natural Language Processing; Sentiment Analysis URL: https://dx.doi.org/10.48448/0z51-tx72 https://underline.io/lecture/37639-seeking-common-but-distinguishing-difference,-a-joint-aspect-based-sentiment-analysis-model BASE Hide details Page: 1 2 3 4 5 6 7 8...83

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