Fetching the paper…
Reading the bibliography…
Storytelling plays a central role in human socializing and entertainment.
On structuring probabilistic dependences in stochastic language modelling
Hermann Ney, Ute Essen, and Reinhard Kneser. 1994 · 1994
Earlier work this paper cites.
A neural probabilistic language model
Yoshua Bengio, Réjean Ducharme, Pascal Vincent, and Christian Jauvin. 2003 · 2003
Earlier work this paper cites.
Word reordering and a dynamic programming beam search algorithm for statistical machine translation
Christoph Tillmann and Hermann Ney. 2003 · 2003
Earlier work this paper cites.
Extensions of recurrent neural network language model. In 2011 IEEE international conference on acoustics, speech and signal processing (ICASSP) . IEEE, 5528–5531
Tomáš Mikolov, Stefan Kombrink, Lukáš Burget, Jan Černockỳ, and Sanjeev Khudanpur. 2011 · 2011
Earlier work this paper cites.
Generating text with recurrent neural networks. In ICML
Ilya Sutskever, James Martens, and Geoffrey E Hinton. 2011 · 2011
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba. 2014 · 2014
Earlier work this paper cites.
Aligning books and movies: Towards story-like visual explanations by watching movies and reading books. In Proceedings of the IEEE international conference on computer vision . 19–27
Yukun Zhu, Ryan Kiros, Rich Zemel, Ruslan Salakhutdinov, Raquel Urtasun, Antonio Torralba, and Sanja Fidler. 2015 · 2015
Earlier work this paper cites.
Attention is all you need. In Advances in neural information processing systems . 5998–6008
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Earlier work this paper cites.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
Cited alongside, same era.
Hierarchical neural story generation
Angela Fan, Mike Lewis, and Yann Dauphin. 2018 · 2018
Cited alongside, same era.
Adafactor: Adaptive learning rates with sublinear memory cost
Noam Shazeer and Mitchell Stern. 2018 · 2018
Cited alongside, same era.
Approximating interactive human evaluation with self-play for open-domain dialog systems. In Advances in Neural Information Processing Systems . 13658–13669
Asma Ghandeharioun, Judy Hanwen Shen, Natasha Jaques, Craig Ferguson, Noah Jones, Agata Lapedriza, and Rosalind Picard. 2019 · 2019
Cited alongside, same era.
A model-free affective reinforcement learning approach to personalization of an autonomous social robot companion for early literacy education. In Proceedings of the AAAI Conference on Artificial Intelligence , Vol. 33. 687–694
Hae Won Park, Ishaan Grover, Samuel Spaulding, Louis Gomez, and Cynthia Breazeal. 2019 · 2019
Later among the works it cites.
Language Models are Unsupervised Multitask Learners
Alec Radford, Jeff Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
Later among the works it cites.
Do Massively Pretrained Language Models Make Better Storytellers?. In Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL) . 843–861
Abigail See, Aneesh Pappu, Rohun Saxena, Akhila Yerukola, and Christopher D Manning. 2019 · 2019
Later among the works it cites.
Bert has a mouth, and it must speak: Bert as a markov random field language model
Alex Wang and Kyunghyun Cho. 2019 · 2019
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
WriterForcing: Generating more interesting story endings. In Proceedings of the Second Workshop on Storytelling . Association for Computational Linguistics, Florence, Italy, 117–126
Prakhar Gupta, Vinayshekhar Bannihatti Kumar, Mukul Bhutani, and Alan W Black. 2019 · 2019
Cited alongside, same era.
The curious case of neural text degeneration
Ari Holtzman, Jan Buys, Li Du, Maxwell Forbes, and Yejin Choi. 2019 · 2019
Cited alongside, same era.
Acute-eval: Improved dialogue evaluation with optimized questions and multi-turn comparisons
Margaret Li, Jason Weston, and Stephen Roller. 2019 · 2019
Cited alongside, same era.
Learning to control the fine-grained sentiment for story ending generation. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics . 6020–6026
Fuli Luo, Damai Dai, Pengcheng Yang, Tianyu Liu, Baobao Chang, Zhifang Sui, and Xu Sun. 2019 · 2019
Cited alongside, same era.
Plan-and-write: Towards better automatic storytelling. In Proceedings of the AAAI Conference on Artificial Intelligence , Vol. 33. 7378–7385
Lili Yao, Nanyun Peng, Ralph Weischedel, Kevin Knight, Dongyan Zhao, and Rui Yan. 2019 · 2019
Later among the works it cites.
Dialogpt: Large-scale generative pre-training for conversational response generation
Yizhe Zhang, Siqi Sun, Michel Galley, Yen-Chun Chen, Chris Brockett, Xiang Gao, Jianfeng Gao, Jingjing Liu, and Bill Dolan. 2019 · 2019
Later among the works it cites.
Grounding Conversations with Improvised Dialogues
Hyundong Cho and Jonathan May. 2020 · 2020
Closest in time.
A Holistic Approach in Designing Tabletop Robot’s Expressivity. In Proceedings of the International Conference on Robotics and Automation
Randy Gomez, Keisuke Nakamura, Deborah Szapiro, and Luis Merino. 2020 · 2020
Closest in time.