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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 Hits 1 – 20 of 23 1 Aspect-based sentiment analysis via affective knowledge enhanced graph convolutional networks Liang, Bin; Su, Hang; Gui, Lin. - : Elsevier, 2022 BASE Show details 2 Boosting Low-Resource Biomedical QA via Entity-Aware Masking Strategies ... Pergola, Gabriele; Kochkina, Elena; Gui, Lin. - : arXiv, 2021 BASE Show details 3 Position Bias Mitigation: A Knowledge-Aware Graph Model for Emotion Cause 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; Gui, Lin; He , Yulan. - : Underline Science Inc., 2021 BASE Show details 4 Topic-Driven and Knowledge-Aware Transformer for Dialogue Emotion Detection ... 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; Gui, Lin; He , Yulan. - : Underline Science Inc., 2021 BASE Show details 5 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 6 Topic-driven and knowledge-aware transformer for dialogue emotion detection Zhu, Lixing; Pergola, Gabriele; Gui, Lin. - : Association for Computational Linguistics, 2021 BASE Show details 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 BASE Show details 8 Multi-modal sarcasm detection with interactive in-modal and cross-modal graphs Liang, Bin; Lou, Chenwei; Li, Xiang. - : ACM, 2021 BASE Show details 9 A Disentangled Adversarial Neural Topic Model for Separating Opinions from Plots in User Reviews ... Pergola, Gabriele; Gui, Lin; He, Yulan. - : arXiv, 2020 BASE Show details 10 CHIME: Cross-passage Hierarchical Memory Network for Generative Review Question Answering ... The 28th International Conference on Computational Linguistics 2020; Gui, Lin; He , Yulan. - : Underline Science Inc., 2020 BASE Show details 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 BASE Show details 12 Commonsense knowledge enhanced memory network for stance classification Du, Jiachen; Gui, Lin; Xu, Ruifeng. - : IEEE Computer Society, 2020 BASE Show details 13 Transition-based directed graph construction for emotion-cause pair extraction Fan, Chuang; Yang, Min; Du, Jiachen. - : Association for Computational Linguistics, 2020 BASE Show details 14 A Knowledge Regularized Hierarchical Approach for Emotion Cause Analysis ... Fan, Chuang; Hongyu Yan; Jiachen Du. - : Zenodo, 2019 BASE Show details 15 A Knowledge Regularized Hierarchical Approach for Emotion Cause Analysis ... Fan, Chuang; Hongyu Yan; Jiachen Du. - : Zenodo, 2019 BASE Show details 16 TDAM: a topic-dependent attention model for sentiment analysis Pergola, Gabriele; Gui, Lin; He, Yulan. - : Elsevier, 2019 BASE Show details 17 A knowledge regularized hierarchical approach for emotion cause analysis Gui, Lin; Bing, Lidong; Xu, Ruifeng. - : Association for Computational Linguistics, 2019 BASE Show details 18 Neural topic model with reinforcement learning Zhou, Yu; Gui, Lin; Xu, Ruifeng; Leng, Jia; Pergola, Gabriele; He, Yulan. - : Association for Computational Linguistics, 2019 Abstract: In recent years, advances in neural variational inference have achieved many successes in text processing. Examples include neural topic models which are typically built upon variational autoencoder (VAE) with an objective of minimising the error of reconstructing original documents based on the learned latent topic vectors. However, minimising reconstruction errors does not necessarily lead to high quality topics. In this paper, we borrow the idea of reinforcement learning and incorporate topic coherence measures as reward signals to guide the learning of a VAE-based topic model. Furthermore, our proposed model is able to automatically separating background words dynamically from topic words, thus eliminating the pre-processing step of filtering infrequent and/or top frequent words, typically required for learning traditional topic models. Experimental results on the 20 Newsgroups and the NIPS datasets show superior performance both on perplexity and topic coherence measure compared to state-of-the-art neural topic models. Keyword: Q Science (General); QA Mathematics URL: https://doi.org/10.18653/v1/D19-1350 http://wrap.warwick.ac.uk/125718/ http://wrap.warwick.ac.uk/125718/7/WRAP-neural-topic-model-reinforcement-learning-Gui-2019.pdf http://wrap.warwick.ac.uk/125718/1/WRAP-neural-topic-model-reinforcement-learning-Gui-2019.pdf BASE Hide details 19 A Question Answering Approach to Emotion Cause Extraction ... Gui, Lin; Hu, Jiannan; He, Yulan. - : arXiv, 2017 BASE Show details 20 A question answering approach for emotion cause extraction Gui, Lin; Hu, Jiannan; He, Yulan. - : Association for Computational Linguistics, 2017 BASE Show details Page: 1 2

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