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Adversarial Learning for Discourse Rhetorical Structure Parsing ...
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XLPT-AMR: Cross-Lingual Pre-Training via Multi-Task Learning for Zero-Shot AMR Parsing and Text Generation ...
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Coupling Context Modeling with Zero Pronoun Recovering for Document-Level Natural Language Generation ...
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Breaking the Corpus Bottleneck for Context-Aware Neural Machine Translation with Cross-Task Pre-training ...
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Extraction of causal relations based on SBEL and BERT model
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In: Database (Oxford) (2021)
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Sentiment Forecasting in Dialog ...
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Abstract:
Sentiment forecasting in dialog aims to predict the polarity of next utterance to come, and can help speakers revise their utterances in sentimental utterances generation. However, the polarity of next utterance is normally hard to predict, due to the lack of content of next utterance (yet to come). In this study, we propose a Neural Sentiment Forecasting (NSF) model to address inherent challenges. In particular, we employ a neural simulation model to simulate the next utterance based on the context (previous utterances encountered). Moreover, we employ a sequence influence model to learn both pair-wise and seq-wise influence. Empirical studies illustrate the importance of proposed sentiment forecasting task, and justify the effectiveness of our NSF model over several strong baselines. ...
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Keyword:
Computer and Information Science; Natural Language Processing; Neural Network
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URL: https://underline.io/lecture/6228-sentiment-forecasting-in-dialog https://dx.doi.org/10.48448/xvhp-ye38
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Chemical-induced disease relation extraction with various linguistic features
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Natural Language Processing and Chinese Computing : Second CCF Conference, NLPCC 2013, Chongqing, China, November 15-19, 2013. Proceedings
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UB Frankfurt Linguistik
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Natural Language Processing and Chinese Computing : First CCF Conference, NLPCC 2012, Beijing, China, October 31-November 5, 2012. Proceedings
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UB Frankfurt Linguistik
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