Fetching the paper…
Reading the bibliography…
Modeling human language requires the ability to not only generate fluent text but also encode factual knowledge.
Dropout: a simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov. 2014 · 1958
Earlier work this paper cites.
Analysing a simple language model·some general conclusions for language models for speech recognition
Joerg Ueberla. 1994 · 1994
Earlier work this paper cites.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
Earlier work this paper cites.
Building applied natural language generation systems
Ehud Reiter and Robert Dale. 1997 · 1997
Earlier work this paper cites.
Recurrent neural network based language model
Tomáš Mikolov, Martin Karafiát, Lukáš Burget, Jan Černockỳ, and Sanjeev Khudanpur. 2010 · 2010
Earlier work this paper cites.
Translating embeddings for modeling multi-relational data
Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran, Jason Weston, and Oksana Yakhnenko. 2013 · 2013
Earlier work this paper cites.
Regularization of neural networks using dropconnect
Li Wan, Matthew Zeiler, Sixin Zhang, Yann LeCun, and Rob Fergus. 2013 · 2013
Earlier work this paper cites.
Wikidata: A free collaborative knowledgebase
Denny Vrandečić and Markus Krötzsch. 2014 · 2014
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba. 2015 · 2015
Earlier work this paper cites.
A neural conversational model
Oriol Vinyals and Quoc V. Le. 2015 · 2015
Earlier work this paper cites.
A neural knowledge language model
Sungjin Ahn, Heeyoul Choi, Tanel Pärnamaa, and Yoshua Bengio. 2016 · 2016
Cited alongside, same era.
Recurrent neural network grammars
Chris Dyer, Adhiguna Kuncoro, Miguel Ballesteros, and Noah A. Smith. 2016 · 2016
Cited alongside, same era.
Incorporating copying mechanism in sequence-to-sequence learning
Jiatao Gu, Zhengdong Lu, Hang Li, and Victor O.K. Li. 2016 · 2016
Cited alongside, same era.
Neural text generation from structured data with application to the biography domain
Rémi Lebret, David Grangier, and Michael Auli. 2016 · 2016
Cited alongside, same era.
Building end-to-end dialogue systems using generative hierarchical neural network models
Iulian V. Serban, Alessandro Sordoni, Yoshua Bengio, Aaron Courville, and Joelle Pineau. 2016 · 2016
Cited alongside, same era.
Reference-aware language models
Zichao Yang, Phil Blunsom, Chris Dyer, and Wang Ling. 2017 · 2017
Later among the works it cites.
Enriching the WebNLG corpus
Thiago Castro Ferreira, Diego Moussallem, Emiel Krahmer, and Sander Wubben. 2018 · 2018
Later among the works it cites.
Frage: frequency-agnostic word representation
Chengyue Gong, Di He, Xu Tan, Tao Qin, Liwei Wang, and Tie-Yan Liu. 2018 · 2018
Later among the works it cites.
Dynamic evaluation of neural sequence models
Ben Krause, Emmanuel Kahembwe, Iain Murray, and Steve Renals. 2018 · 2018
Later among the works it cites.
Regularizing and optimizing LSTM language models
Stephen Merity, Nitish Shirish Keskar, and Richard Socher. 2018 · 2018
Later among the works it cites.
Numeracy for language models: Evaluating and improving their ability to predict numbers
Georgios P. Spithourakis and Sebastian Riedel. 2018 · 2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Claire Gardent, Anastasia Shimorina, Shashi Narayan, and Laura Perez-Beltrachini. 2017 · 2017
Cited alongside, same era.
Entity linking via joint encoding of types, descriptions, and context
Nitish Gupta, Sameer Singh, and Dan Roth. 2017 · 2017
Cited alongside, same era.
Dynamic entity representations in neural language models
Yangfeng Ji, Chenhao Tan, Sebastian Martschat, Yejin Choi, and Noah A. Smith. 2017 · 2017
Cited alongside, same era.
Pointer sentinel mixture models
Stephen Merity, Caiming Xiong, James Bradbury, and Richard Socher. 2017 · 2017
Cited alongside, same era.
Challenges in data-to-document generation
Sam Wiseman, Stuart M. Shieber, and Alexander M. Rush. 2017 · 2017
Cited alongside, same era.
Breaking the softmax bottleneck: A high-rank RNN language model
Zhilin Yang, Zihang Dai, Ruslan Salakhutdinov, and William W Cohen. 2018 · 2018
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
Closest in time.
Do language models have common sense?
Trieu H. Trinh and Quoc V. Le. 2019 · 2019
Closest in time.