COMMA: Modeling Relationship among Motivations, Emotions and Actions in Language-based Human Activities
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 23 of its 53 references that are in the map. First posted on arXiv 14 Sep 2022.
Builds on
23 of 53 references.
References · 23
- 2017Attention Is All You Needcited by 60,361
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
- 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,305
- 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
- 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,893
- 2014Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modelingcited by 2,367
- 2015A Diversity-Promoting Objective Function for Neural Conversation Modelscited by 1,077
- 2019Adversarial NLI: A New Benchmark for Natural Language Understandingcited by 807
- 2016A Corpus and Evaluation Framework for Deeper Understanding of Commonsense Storiescited by 417
- 2020Social Chemistry 101: Learning to Reason about Social and Moral Normscited by 255
- 2020COMET-ATOMIC 2020: On Symbolic and Neural Commonsense Knowledge Graphscited by 254
- 2013Crowdsourcing a Word-Emotion Association Lexiconcited by 196
11 more
- 2018Deep Learning for Sentiment Analysis : A Surveycited by 139
- 2018Event2Mind: Commonsense Inference on Events, Intents, and Reactionscited by 82
- 2020MEGATRON-CNTRL: Controllable Story Generation with External Knowledge Using Large-Scale Language Modelscited by 74
- 2018Modeling Naive Psychology of Characters in Simple Commonsense Storiescited by 60
- 2022Control Globally, Understand Locally: A Global-to-Local Hierarchical Graph Network for Emotional Support Conversationcited by 56
- 2020Modeling Protagonist Emotions for Emotion-Aware Storytellingcited by 42
- 2020Automated Storytelling via Causal, Commonsense Plot Orderingcited by 38
- 2016Inducing Domain-Specific Sentiment Lexicons from Unlabeled Corporacited by 19
- 2019Modeling Event Background for If-Then Commonsense Reasoning Using Context-aware Variational Autoencodercited by 4
- 2015Reflections on Sentiment/Opinion Analysiscited by 3
- 2022CogIntAc: Modeling the Relationships between Intention, Emotion and Action in Interactive Process from Cognitive Perspectivecited by 2
Built on by
Citing papers per year: 2022: 1; 2023: 1; 2024: 1; 2025: 0; 2026: 1.
4 papers.
- 2023DiffusEmp: A Diffusion Model-Based Framework with Multi-Grained Control for Empathetic Response Generationcited by 9
- 2024MLD-EA: Check and Complete Narrative Coherence by Introducing Emotions and Actionscited by 4
- 2022Psychology-guided Controllable Story Generationcited by 2
- 2026StoryTR: Narrative-Centric Video Temporal Retrieval with Theory of Mind Reasoningcited by 0
- 2026StoryTR: Narrative-Centric Video Temporal Retrieval with Theory of Mind Reasoning25 Apr 2026
- 2024MLD-EA: Check and Complete Narrative Coherence by Introducing Emotions and Actions3 Dec 2024
- 2023DiffusEmp: A Diffusion Model-Based Framework with Multi-Grained Control for Empathetic Response Generation2 Jun 2023
- 2022Psychology-guided Controllable Story Generation14 Oct 2022