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Controllable story generation is a challenging task in the field of NLP, which has attracted increasing research interest in recent years.
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Melissa Roemmele. 2016 · 2016
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Story generation from sequence of independent short descriptions
Parag Jain, Priyanka Agrawal, Abhijit Mishra, Mohak Sukhwani, Anirban Laha, and Karthik Sankaranarayanan. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Steering output style and topic in neural response generation
Di Wang, Nebojsa Jojic, Chris Brockett, and Eric Nyberg. 2017 · 2017
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Neural text generation in stories using entity representations as context
Elizabeth Clark, Yangfeng Ji, and Noah A. Smith. 2018 · 2018
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Automatic dialogue generation with expressed emotions
Chenyang Huang, Osmar Zaïane, Amine Trabelsi, and Nouha Dziri. 2018 · 2018
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Event representations for automated story generation with deep neural nets
Lara J. Martin, Prithviraj Ammanabrolu, Xinyu Wang, William Hancock, Shruti Singh, Brent Harrison, and Mark O. Riedl. 2018 · 2018
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Towards controllable story generation
Nanyun Peng, Marjan Ghazvininejad, Jonathan May, and Kevin Knight. 2018 · 2018
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Modeling naive psychology of characters in simple commonsense stories
Plan-and-write: Towards better automatic storytelling
Lili Yao, Nanyun Peng, R. Weischedel, Kevin Knight, Dongyan Zhao, and Rui Yan. 2019 · 2019
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Modeling protagonist emotions for emotion-aware storytelling
Faeze Brahman and Snigdha Chaturvedi. 2020 · 2020
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Plug and play language models: A simple approach to controlled text generation
Sumanth Dathathri, Andrea Madotto, Janice Lan, Jane Hung, Eric Frank, Piero Molino, Jason Yosinski, and Rosanne Liu. 2020 · 2020
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A knowledge-enhanced pretraining model for commonsense story generation
Jian Guan, Fei Huang, Zhihao Zhao, Xiaoyan Zhu, and Minlie Huang. 2020 · 2020
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BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer. 2020 · 2020
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Hannah Rashkin, Antoine Bosselut, Maarten Sap, Kevin Knight, and Yejin Choi. 2018 · 2018
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A skeleton-based model for promoting coherence among sentences in narrative story generation
Jingjing Xu, Xuancheng Ren, Yi Zhang, Qi Zeng, Xiaoyan Cai, and Xu Sun. 2018 · 2018
Cited alongside, same era.
Emotional chatting machine: Emotional conversation generation with internal and external memory
Hao Zhou, Minlie Huang, Tianyang Zhang, Xiaoyan Zhu, and Bing Liu. 2018 · 2018
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MojiTalk: Generating emotional responses at scale
Xianda Zhou and William Yang Wang. 2018 · 2018
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COMET: Commonsense transformers for automatic knowledge graph construction
Antoine Bosselut, Hannah Rashkin, Maarten Sap, Chaitanya Malaviya, Asli Celikyilmaz, and Yejin Choi. 2019 · 2019
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Hello, it’s GPT-2 - how can I help you? towards the use of pretrained language models for task-oriented dialogue systems
Paweł Budzianowski and Ivan Vulić. 2019 · 2019
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Strategies for structuring story generation
Angela Fan, Mike Lewis, and Yann Dauphin. 2019 · 2019
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A character-centric neural model for automated story generation
Danyang Liu, Juntao Li, Meng-Hsuan Yu, Ziming Huang, Gongshen Liu, Dongyan Zhao, and Rui Yan. 2020 · 2020
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PlotMachines: Outline-conditioned generation with dynamic plot state tracking
Hannah Rashkin, Asli Celikyilmaz, Yejin Choi, and Jianfeng Gao. 2020 · 2020
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Generating narrative text in a switching dynamical system
Noah Weber, Leena Shekhar, Heeyoung Kwon, Niranjan Balasubramanian, and Nathanael Chambers. 2020 · 2020
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Transformers: State-of-the-art natural language processing
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Controllable multi-character psychology-oriented story generation
Feifei Xu, Xinpeng Wang, Yunpu Ma, Volker Tresp, Yuyi Wang, Shanlin Zhou, and Haizhou Du. 2020a · 2020
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MEGATRON-CNTRL: Controllable story generation with external knowledge using large-scale language models
Peng Xu, Mostofa Patwary, Mohammad Shoeybi, Raul Puri, Pascale Fung, Anima Anandkumar, and Bryan Catanzaro. 2020b · 2020
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Automatic story generation: Challenges and attempts
Amal Alabdulkarim, Siyan Li, and Xiangyu Peng. 2021 · 2021
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Automated storytelling via causal, commonsense plot ordering
Prithviraj Ammanabrolu, W. Cheung, William Broniec, and Mark O. Riedl. 2021 · 2021
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Stylized story generation with style-guided planning
Xiangzhe Kong, Jialiang Huang, Ziquan Tung, Jian Guan, and Minlie Huang. 2021 · 2021
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COINS: Dynamically generating COntextualized inference rules for narrative story completion
Debjit Paul and Anette Frank. 2021 · 2021
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Control globally, understand locally: A global-to-local hierarchical graph network for emotional support conversation
Wei Peng, Yue Hu, Luxi Xing, Yuqiang Xie, Yajing Sun, and Yunpeng Li. 2022 · 2022
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Clseg: Contrastive learning of story ending generation
Yuqiang Xie, Yue Hu, Luxi Xing, Yunpeng Li, Wei Peng, and Ping Guo. 2022b · 2022
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TSAM: A two-stream attention model for causal emotion entailment
Duzhen Zhang, Zhen Yang, Fandong Meng, Xiuyi Chen, and Jie Zhou. 2022 · 2022
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