COMMA: Modeling Relationship among Motivations, Emotions and Actions in Language-based Human Activities

September 14, 2022 ยท Declared Dead ยท ๐Ÿ› International Conference on Computational Linguistics

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Authors Yuqiang Xie, Yue Hu, Wei Peng, Guanqun Bi, Luxi Xing arXiv ID 2209.06470 Category cs.CL: Computation & Language Cross-listed cs.AI Citations 6 Venue International Conference on Computational Linguistics Last Checked 4 months ago
Abstract
Motivations, emotions, and actions are inter-related essential factors in human activities. While motivations and emotions have long been considered at the core of exploring how people take actions in human activities, there has been relatively little research supporting analyzing the relationship between human mental states and actions. We present the first study that investigates the viability of modeling motivations, emotions, and actions in language-based human activities, named COMMA (Cognitive Framework of Human Activities). Guided by COMMA, we define three natural language processing tasks (emotion understanding, motivation understanding and conditioned action generation), and build a challenging dataset Hail through automatically extracting samples from Story Commonsense. Experimental results on NLP applications prove the effectiveness of modeling the relationship. Furthermore, our models inspired by COMMA can better reveal the essential relationship among motivations, emotions and actions than existing methods.
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