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Automated story generation has been one of the long-standing challenges in NLP.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al. 2020 · 1901
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Measuring nominal scale agreement among many raters
Joseph L Fleiss. 1971 · 1971
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The Metanovel: Writing Stories by Computer
James Richard Meehan. 1976 · 1976
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Development of story liking: Character identification, suspense, and outcome resolution
Paul E Jose and William F Brewer. 1984 · 1984
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Planning stories
Michael Lebowitz. 1987 · 1987
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The Cognitive Structure of Emotions
Andrew Ortony, Gerald L. Clore, and Allan Collins. 1988 · 1988
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Experiencing narrative worlds: On the psychological activities of reading
Richard J Gerrig. 1993 · 1993
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Readers as problem-solvers in the experience of suspense
Richard J Gerrig and Allan BI Bernardo. 1994 · 1994
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Interacting with virtual agents in mixed reality interactive storytelling
Marc Cavazza, Olivier Martin, Fred Charles, Steven J Mead, and Xavier Marichal. 2003 · 2003
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Evaluation of text generation: A survey
Asli Celikyilmaz, Elizabeth Clark, and Jianfeng Gao. 2020 · 2006
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Controlling narrative generation with planning trajectories: the role of constraints
Julie Porteous and Marc Cavazza. 2009 · 2009
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Narrative planning: balancing plot and character
Mark O Riedl and R Michael Young. 2010 · 2010
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Modeling narrative conflict to generate interesting stories
Stephen Ware and R Young. 2010 · 2010
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Toward a computational framework of suspense and dramatic arc
Brian O’Neill and Mark Riedl. 2011 · 2011
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Narrative comprehension and film
Edward Branigan. 2013 · 2013
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Suspenser: A story generation system for suspense
Yun-Gyung Cheong and R Michael Young. 2014 · 2014
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Dramatis: A computational model of suspense
Brian O’Neill and Mark Riedl. 2014 · 2014
Cited alongside, same era.
Leveraging intention revision in narrative planning to create suspenseful stories
Matthew William Fendt and R Michael Young. 2016 · 2016
Cited alongside, same era.
Writing stories with help from recurrent neural networks
Melissa Roemmele. 2016 · 2016
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A model of suspense for narrative generation
Richard Doust and Paul Piwek. 2017 · 2017
Cited alongside, same era.
Ahmed Khalifa, Gabriella AB Barros, and Julian Togelius. 2017 · 2017
Cited alongside, same era.
Neural text generation in stories using entity representations as context
Elizabeth Clark, Yangfeng Ji, and Noah A. Smith. 2018 · 2018
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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PlotMachines: Outline-conditioned generation with dynamic plot state tracking
Hannah Rashkin, Asli Celikyilmaz, Yejin Choi, and Jianfeng Gao. 2020 · 2020
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Modelling suspense in short stories as uncertainty reduction over neural representation
David Wilmot and Frank Keller. 2020 · 2020
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Automated storytelling via causal, commonsense plot ordering
Prithviraj Ammanabrolu, Wesley Cheung, William Broniec, and Mark O Riedl. 2021 · 2021
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Improving the fitness function of an evolutionary suspense generator through sentiment analysis
Pablo Delatorre, Carlos Leon, and Alberto Salguero Hidalgo. 2021 · 2021
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Cited alongside, same era.
Hierarchical neural story generation
Angela Fan, Mike Lewis, and Yann Dauphin. 2018 · 2018
Cited alongside, same era.
Event representations for automated story generation with deep neural nets
Lara Martin, Prithviraj Ammanabrolu, Xinyu Wang, William Hancock, Shruti Singh, Brent Harrison, and Mark Riedl. 2018 · 2018
Cited alongside, same era.
Towards controllable story generation
Nanyun Peng, Marjan Ghazvininejad, Jonathan May, and Kevin Knight. 2018 · 2018
Cited alongside, same era.
Strategies for structuring story generation
Angela Fan, Mike Lewis, and Yann Dauphin. 2019 · 2019
Cited alongside, same era.
Story ending generation with incremental encoding and commonsense knowledge
Jian Guan, Yansen Wang, and Minlie Huang. 2019 · 2019
Cited alongside, same era.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al. 2019 · 2019
Cited alongside, same era.
Plug-and-blend: a framework for plug-and-play controllable story generation with sketches
Zhiyu Lin and Mark O Riedl. 2021 · 2021
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Human evaluation of automatically generated text: Current trends and best practice guidelines
Chris van der Lee, Albert Gatt, Emiel van Miltenburg, and Emiel Krahmer. 2021 · 2021
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Sabre: A narrative planner supporting intention and deep theory of mind
Stephen G Ware and Cory Siler. 2021 · 2021
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Go back in time: Generating flashbacks in stories with event temporal prompts
Rujun Han, Hong Chen, Yufei Tian, and Nanyun Peng. 2022 · 2022
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Plot writing from pre-trained language models
Yiping Jin, Vishakha Kadam, and Dittaya Wanvarie. 2022 · 2022
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Chatgpt: A large-scale opendomain chatbot
OpenAI. 2022 · 2022
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Guiding neural story generation with reader models
Xiangyu Peng, Kaige Xie, Amal Alabdulkarim, Harshith Kayam, Samihan Dani, and Mark Riedl. 2022 · 2022
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Re3: Generating longer stories with recursive reprompting and revision
Kevin Yang, Yuandong Tian, Nanyun Peng, and Dan Klein. 2022b · 2022
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Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al. 2023 · 2023
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Towards a computational analysis of suspense: Detecting dangerous situations
Albin Zehe, Julian Schröter, and Andreas Hotho. 2023 · 2023
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