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Conditional story generation and contextual text continuation have become increasingly popular topics in NLP community.
Simple statistical gradient-following algorithms for connectionist reinforcement learning
Ronald J Williams · 1992
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Skip-thought vectors
Ryan Kiros, Yukun Zhu, Russ R Salakhutdinov, Richard Zemel, Raquel Urtasun, Antonio Torralba, and Sanja Fidler · 2015
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Writing stories with help from recurrent neural networks
Melissa Roemmele · 2016
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Generating music by fine-tuning recurrent neural networks with reinforcement learning
Natasha Jaques, Shixiang Gu, Richard E Turner, and Douglas Eck · 2016
Earlier work this paper cites.
The wikitext long term dependency language modeling dataset
Stephen Merity · 2016
Cited alongside, same era.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
Cited alongside, same era.
Hierarchical neural story generation
Angela Fan, Mike Lewis, and Yann Dauphin · 2018
Cited alongside, same era.
Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
Cited alongside, same era.
Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever · 2018
Later among the works it cites.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever · 2019
Later among the works it cites.
Encoder-agnostic adaptation for conditional language generation
Zachary M Ziegler, Luke Melas-Kyriazi, Sebastian Gehrmann, and Alexander M Rush · 2019
Later among the works it cites.
Learning autocomplete systems as a communication game
Mina Lee, Tatsunori B Hashimoto, and Percy Liang · 2019
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