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1
Aspect-based sentiment analysis via affective knowledge enhanced graph convolutional networks
Liang, Bin; Su, Hang; Gui, Lin. - : Elsevier, 2022
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2
Boosting Low-Resource Biomedical QA via Entity-Aware Masking Strategies ...
Abstract: Biomedical question-answering (QA) has gained increased attention for its capability to provide users with high-quality information from a vast scientific literature. Although an increasing number of biomedical QA datasets has been recently made available, those resources are still rather limited and expensive to produce. Transfer learning via pre-trained language models (LMs) has been shown as a promising approach to leverage existing general-purpose knowledge. However, finetuning these large models can be costly and time consuming, often yielding limited benefits when adapting to specific themes of specialised domains, such as the COVID-19 literature. To bootstrap further their domain adaptation, we propose a simple yet unexplored approach, which we call biomedical entity-aware masking (BEM). We encourage masked language models to learn entity-centric knowledge based on the pivotal entities characterizing the domain at hand, and employ those entities to drive the LM fine-tuning. The resulting strategy is a ... : EACL 2021 - Short Paper - European Chapter of the Association for Computational Linguistics ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences; Information Retrieval cs.IR; Machine Learning cs.LG
URL: https://arxiv.org/abs/2102.08366
https://dx.doi.org/10.48550/arxiv.2102.08366
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3
Position Bias Mitigation: A Knowledge-Aware Graph Model for Emotion Cause Extraction ...
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4
Topic-Driven and Knowledge-Aware Transformer for Dialogue Emotion Detection ...
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5
Beta Distribution Guided Aspect-aware Graph for Aspect Category Sentiment Analysis with Affective Knowledge ...
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6
Topic-driven and knowledge-aware transformer for dialogue emotion detection
Zhu, Lixing; Pergola, Gabriele; Gui, Lin. - : Association for Computational Linguistics, 2021
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7
A disentangled adversarial neural topic model for separating opinions from plots in user reviews
Pergola, Gabriele; Gui, Lin; He, Yulan. - : Association for Computational Linguistics, 2021
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8
Multi-modal sarcasm detection with interactive in-modal and cross-modal graphs
Liang, Bin; Lou, Chenwei; Li, Xiang. - : ACM, 2021
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9
A Disentangled Adversarial Neural Topic Model for Separating Opinions from Plots in User Reviews ...
Pergola, Gabriele; Gui, Lin; He, Yulan. - : arXiv, 2020
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10
CHIME: Cross-passage Hierarchical Memory Network for Generative Review Question Answering ...
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11
Jointly learning aspect-focused and inter-aspect relations with graph convolutional networks for aspect sentiment analysis
Liang, Bin; Yin, Rongdi; Gui, Lin. - : International Committee on Computational Linguistics, 2020
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12
Commonsense knowledge enhanced memory network for stance classification
Du, Jiachen; Gui, Lin; Xu, Ruifeng. - : IEEE Computer Society, 2020
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13
Transition-based directed graph construction for emotion-cause pair extraction
Fan, Chuang; Yang, Min; Du, Jiachen. - : Association for Computational Linguistics, 2020
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14
A Knowledge Regularized Hierarchical Approach for Emotion Cause Analysis ...
Fan, Chuang; Hongyu Yan; Jiachen Du. - : Zenodo, 2019
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15
A Knowledge Regularized Hierarchical Approach for Emotion Cause Analysis ...
Fan, Chuang; Hongyu Yan; Jiachen Du. - : Zenodo, 2019
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16
TDAM: a topic-dependent attention model for sentiment analysis
Pergola, Gabriele; Gui, Lin; He, Yulan. - : Elsevier, 2019
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17
A knowledge regularized hierarchical approach for emotion cause analysis
Gui, Lin; Bing, Lidong; Xu, Ruifeng. - : Association for Computational Linguistics, 2019
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18
Neural topic model with reinforcement learning
Zhou, Yu; Gui, Lin; Xu, Ruifeng. - : Association for Computational Linguistics, 2019
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19
A Question Answering Approach to Emotion Cause Extraction ...
Gui, Lin; Hu, Jiannan; He, Yulan. - : arXiv, 2017
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20
A question answering approach for emotion cause extraction
Gui, Lin; Hu, Jiannan; He, Yulan. - : Association for Computational Linguistics, 2017
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