Fetching the paper…
Reading the bibliography…
Neural dialog state trackers are generally limited due to the lack of quantity and diversity of annotated training data.
A joint many-task model: Growing a neural network for multiple nlp tasks
Kazuma Hashimoto, caiming xiong, Yoshimasa Tsuruoka, and Richard Socher. 2017 · 1933
Earlier work this paper cites.
Reinforcement learning for spoken dialogue systems
Satinder P Singh, Michael J Kearns, Diane J Litman, and Marilyn A Walker. 2000 · 2000
Earlier work this paper cites.
Juplter: a telephone-based conversational interface for weather information
Victor Zue, Stephanie Seneff, James R Glass, Joseph Polifroni, Christine Pao, Timothy J Hazen, and Lee Hetherington. 2000 · 2000
Earlier work this paper cites.
Managing ambiguities across utterances in dialogue
David DeVault and Matthew Stone. 2007 · 2007
Earlier work this paper cites.
Exploiting the asr n-best by tracking multiple dialog state hypotheses
Jason D Williams. 2008 · 2008
Earlier work this paper cites.
Application-driven statistical paraphrase generation
Shiqi Zhao, Xiang Lan, Ting Liu, and Sheng Li. 2009 · 2009
Earlier work this paper cites.
Efficient optimal learning for contextual bandits
Miroslav Dudik, Daniel Hsu, Satyen Kale, Nikos Karampatziakis, John Langford, Lev Reyzin, and Tong Zhang. 2011 · 2011
Earlier work this paper cites.
Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton. 2012 · 2012
Earlier work this paper cites.
Discriminative state tracking for spoken dialog systems
Angeliki Metallinou, Dan Bohus, and Jason Williams. 2013 · 2013
Earlier work this paper cites.
The dialog state tracking challenge
Jason Williams, Antoine Raux, Deepak Ramachandran, and Alan Black. 2013 · 2013
Earlier work this paper cites.
Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher D. Manning. 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.
Audio augmentation for speech recognition
Tom Ko, Vijayaditya Peddinti, Daniel Povey, and Sanjeev Khudanpur. 2015 · 2015
Earlier work this paper cites.
Sequence level training with recurrent neural networks
Marc’Aurelio Ranzato, Sumit Chopra, Michael Auli, and Wojciech Zaremba. 2015 · 2015
Earlier work this paper cites.
Character-level convolutional networks for text classification
Xiang Zhang, Junbo Zhao, and Yann LeCun. 2015 · 2015
Earlier work this paper cites.
Deep reinforcement learning for dialogue generation
Jiwei Li, Will Monroe, Alan Ritter, Dan Jurafsky, Michel Galley, and Jianfeng Gao. 2016 · 2016
Cited alongside, same era.
Improving information extraction by acquiring external evidence with reinforcement learning
Karthik Narasimhan, Adam Yala, and Regina Barzilay. 2016 · 2016
Cited alongside, same era.
The dialog state tracking challenge series: A review
Jason Williams, Antoine Raux, and Matthew Henderson. 2016 · 2016
Cited alongside, same era.
A structured self-attentive sentence embedding
Zhouhan Lin, Minwei Feng, Cicero Nogueira dos Santos, Mo Yu, Bing Xiang, Bowen Zhou, and Yoshua Bengio. 2017 · 2017
Cited alongside, same era.
Neural belief tracker: Data-driven dialogue state tracking
Nikola Mrkšić, Diarmuid Ó Séaghdha, Tsung-Hsien Wen, Blaise Thomson, and Steve Young. 2017 · 2017
Cited alongside, same era.
Co-teaching: Robust training of deep neural networks with extremely noisy labels
Bo Han, Quanming Yao, Xingrui Yu, Gang Niu, Miao Xu, Weihua Hu, Ivor Tsang, and Masashi Sugiyama. 2018 · 2018
Later among the works it cites.
Sequence-to-sequence data augmentation for dialogue language understanding
Yutai Hou, Yijia Liu, Wanxiang Che, and Ting Liu. 2018 · 2018
Later among the works it cites.
Adversarial training for textual entailment with knowledge-guided examples
Dongyeop Kang, Tushar Khot, Ashish Sabharwal, and Eduard Hovy. 2018 · 2018
Later among the works it cites.
Contextual augmentation: Data augmentation by words with paradigmatic relations
Sosuke Kobayashi. 2018 · 2018
Later among the works it cites.
Paraphrase generation with deep reinforcement learning
Zichao Li, Xin Jiang, Lifeng Shang, and Hang Li. 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…
Romain Paulus, Caiming Xiong, and Richard Socher. 2017 · 2017
Cited alongside, same era.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Cited alongside, same era.
A network-based end-to-end trainable task-oriented dialogue system
Tsung-Hsien Wen, David Vandyke, Nikola Mrkšić, Milica Gasic, Lina M Rojas Barahona, Pei-Hao Su, Stefan Ultes, and Steve Young. 2017 · 2017
Cited alongside, same era.
Deeppath: A reinforcement learning method for knowledge graph reasoning
Wenhan Xiong, Thien Hoang, and William Yang Wang. 2017 · 2017
Cited alongside, same era.
Multiwoz-a large-scale multi-domain wizard-of-oz dataset for task-oriented dialogue modelling
Paweł Budzianowski, Tsung-Hsien Wen, Bo-Hsiang Tseng, Iñigo Casanueva, Stefan Ultes, Osman Ramadan, and Milica Gasic. 2018 · 2018
Cited alongside, same era.
Deep communicating agents for abstractive summarization
Asli Celikyilmaz, Antoine Bosselut, Xiaodong He, and Yejin Choi. 2018 · 2018
Cited alongside, same era.
Autoaugment: Learning augmentation policies from data
Ekin D Cubuk, Barret Zoph, Dandelion Mane, Vijay Vasudevan, and Quoc V Le. 2018 · 2018
Cited alongside, same era.
Elnaz Nouri and Ehsan Hosseini-Asl. 2018 · 2018
Later among the works it cites.
Large-scale multi-domain belief tracking with knowledge sharing
Osman Ramadan, Paweł Budzianowski, and Milica Gasic. 2018 · 2018
Later among the works it cites.
Robust spoken language understanding via paraphrasing
Avik Ray, Yilin Shen, and Hongxia Jin. 2018 · 2018
Later among the works it cites.
Towards universal dialogue state tracking
Liliang Ren, Kaige Xie, Lu Chen, and Kai Yu. 2018 · 2018
Later among the works it cites.
Semantically equivalent adversarial rules for debugging NLP models
Marco Tulio Ribeiro, Sameer Singh, and Carlos Guestrin. 2018 · 2018
Later among the works it cites.
Reinforcement learning: An introduction , pages 329–331. MIT press
Richard S Sutton and Andrew G Barto. 2018 · 2018
Later among the works it cites.
Reinforced co-training
Jiawei Wu, Lei Li, and William Yang Wang. 2018 · 2018
Later among the works it cites.
Data augmentation for spoken language understanding via joint variational generation
Kang Min Yoo, Youhyun Shin, and Sang-goo Lee. 2018 · 2018
Later among the works it cites.
Global-locally self-attentive encoder for dialogue state tracking
Victor Zhong, Caiming Xiong, and Richard Socher. 2018 · 2018
Later among the works it cites.
Improving dialogue state tracking by discerning the relevant context
Sanuj Sharma, Prafulla Kumar Choubey, and Ruihong Huang. 2019 · 2019
Closest in time.