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Plan-and-Write is a common hierarchical approach in long-form narrative text generation, which first creates a plan to guide the narrative writing.
Generating high-quality and informative conversation responses with sequence-to-sequence models
Yuanlong Shao, Stephan Gouws, Denny Britz, Anna Goldie, Brian Strope, and Ray Kurzweil. 2017 · 2017
Earlier work this paper cites.
Hierarchical neural story generation
Angela Fan, Mike Lewis, and Yann Dauphin. 2018 · 2018
Earlier work this paper cites.
Strategies for structuring story generation
Angela Fan, Mike Lewis, and Yann Dauphin. 2019 · 2019
Earlier work this paper cites.
Plan-and-write: Towards better automatic storytelling
Lili Yao, Nanyun Peng, Ralph Weischedel, Kevin Knight, Dongyan Zhao, and Rui Yan. 2019 · 2019
Earlier work this paper cites.
Content planning for neural story generation with aristotelian rescoring
Seraphina Goldfarb-Tarrant, Tuhin Chakrabarty, Ralph Weischedel, and Nanyun Peng. 2020 · 2020
Earlier work this paper cites.
Long text generation by modeling sentence-level and discourse-level coherence
Jian Guan, Xiaoxi Mao, Changjie Fan, Zitao Liu, Wenbiao Ding, and Minlie Huang. 2021 · 2021
Earlier work this paper cites.
DiscoDVT: Generating long text with discourse-aware discrete variational transformer
Haozhe Ji and Minlie Huang. 2021 · 2021
Earlier work this paper cites.
Talebrush: sketching stories with generative pretrained language models
John Joon Young Chung, Wooseok Kim, Kang Min Yoo, Hwaran Lee, Eytan Adar, and Minsuk Chang. 2022 · 2022
Cited alongside, same era.
LoRA: Low-rank adaptation of large language models
Edward J Hu, yelong shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2022 · 2022
Cited alongside, same era.
Coauthor: Designing a human-ai collaborative writing dataset for exploring language model capabilities
Mina Lee, Percy Liang, and Qian Yang. 2022 · 2022
Cited alongside, same era.
Re3: Generating longer stories with recursive reprompting and revision
Kevin Yang, Yuandong Tian, Nanyun Peng, and Dan Klein. 2022 · 2022
Cited alongside, same era.
Wordcraft: story writing with large language models
Ann Yuan, Andy Coenen, Emily Reif, and Daphne Ippolito. 2022 · 2022
Cited alongside, same era.
Sparks of artificial general intelligence: Early experiments with gpt-4
A survey on evaluation of large language models
Yupeng Chang, Xu Wang, Jindong Wang, Yuan Wu, Linyi Yang, Kaijie Zhu, Hao Chen, Xiaoyuan Yi, Cunxiang Wang, Yidong Wang, Wei Ye, Yue Zhang, Yi Chang, Philip S. Yu, Qiang Yang, and Xing Xie. 2023 · 2023
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Gpteval: Nlg evaluation using gpt-4 with better human alignment
Yang Liu, Dan Iter, Yichong Xu, Shuohang Wang, Ruochen Xu, and Chenguang Zhu. 2023 · 2023
Closest in time.
Co-writing screenplays and theatre scripts with language models: Evaluation by industry professionals
Piotr Mirowski, Kory W Mathewson, Jaylen Pittman, and Richard Evans. 2023 · 2023
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Llama: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, Aurelien Rodriguez, Armand Joulin, Edouard Grave, and Guillaume Lample. 2023 · 2023
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Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, Johannes Gehrke, Eric Horvitz, Ece Kamar, Peter Lee, Yin Tat Lee, Yuanzhi Li, Scott Lundberg, Harsha Nori, Hamid Palangi, Marco Tulio Ribeiro, and Yi Zhang. 2023 · 2023
Cited alongside, same era.
DOC: Improving long story coherence with detailed outline control
Kevin Yang, Dan Klein, Nanyun Peng, and Yuandong Tian. 2023 · 2023
Closest in time.
Recurrentgpt: Interactive generation of (arbitrarily) long text
Wangchunshu Zhou, Yuchen Eleanor Jiang, Peng Cui, Tiannan Wang, Zhenxin Xiao, Yifan Hou, Ryan Cotterell, and Mrinmaya Sachan. 2023 · 2023
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