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Exposure bias describes the phenomenon that a language model trained under the teacher forcing schema may perform poorly at the inference stage when its predictions are conditioned on its previous predictions unseen from the training corpus.
Quantifying exposure bias for neural language generation
Tianxing He, Jingzhao Zhang, Zhiming Zhou, and James Glass. 2019 · 1905
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Neural program synthesis by self-learning
Yifan Xu, Lu Dai, Udaikaran Singh, Kening Zhang, and Zhuowen Tu. 2019 · 1910
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Asynchronous methods for deep reinforcement learning
Volodymyr Mnih, Adria Puigdomenech Badia, Mehdi Mirza, Alex Graves, Timothy Lillicrap, Tim Harley, David Silver, and Koray Kavukcuoglu. 2016 · 1937
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A learning algorithm for continually running fully recurrent neural networks
Ronald J Williams and David Zipser. 1989 · 1989
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Actor-critic algorithms
Vijay R Konda and John N Tsitsiklis. 2000 · 2000
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Policy gradient methods for reinforcement learning with function approximation
Richard S Sutton, David A McAllester, Satinder P Singh, and Yishay Mansour. 2000 · 2000
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Information theory, inference and learning algorithms
David JC MacKay. 2003 · 2003
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Speech recognition with deep recurrent neural networks
Alex Graves, Abdel-rahman Mohamed, and Geoffrey Hinton. 2013 · 2013
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Playing atari with deep reinforcement learning
Mnih Volodymyr, Koray Kavukcuoglu, David Silver, Alex Graves, and Ioannis Antonoglou. 2013 · 2013
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Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2014 · 2014
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2014 · 2014
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Scheduled sampling for sequence prediction with recurrent neural networks
Samy Bengio, Oriol Vinyals, Navdeep Jaitly, and Noam Shazeer. 2015 · 2015
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How (not) to train your generative model: Scheduled sampling, likelihood, adversary?
Ferenc Huszár. 2015 · 2015
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Deep visual-semantic alignments for generating image descriptions
Andrej Karpathy and Li Fei-Fei. 2015 · 2015
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Long text generation via adversarial training with leaked information
Jiaxian Guo, Sidi Lu, Han Cai, Weinan Zhang, Yong Yu, and Jun Wang. 2017 · 2017
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Adversarial ranking for language generation
Kevin Lin, Dianqi Li, Xiaodong He, Zhengyou Zhang, and Ming-Ting Sun. 2017 · 2017
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Seqgan: Sequence generative adversarial nets with policy gradient
Lantao Yu, Weinan Zhang, Jun Wang, and Yong Yu. 2017 · 2017
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Massimo Caccia, Lucas Caccia, William Fedus, Hugo Larochelle, Joelle Pineau, and Laurent Charlin. 2018 · 2018
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Towards diverse text generation with inverse reinforcement learning
Zhan Shi, Xinchi Chen, Xipeng Qiu, and Xuanjing Huang. 2018 · 2018
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Jointly measuring diversity and quality in text generation models
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