Fetching the paper…
Reading the bibliography…
End-to-end Task-oriented Dialogue Systems (TDSs) have attracted a lot of attention for their superiority (e.g., in terms of global optimization) over pipeline modularized TDSs.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
Earlier work this paper cites.
Ensemble methods in machine learning. In Proceedings of the First International Workshop on Multiple Classifier Systems (MCS ’00) . 1–15
Thomas G Dietterich. 2000 · 2000
Earlier work this paper cites.
On the difficulty of training recurrent neural networks. In Proceedings of the 30th International Conference on Machine Learning (ICML ’13) . 1310–1318
Razvan Pascanu, Tomas Mikolov, and Yoshua Bengio. 2013 · 2013
Earlier work this paper cites.
POMDP-based statistical spoken dialog systems: A review
Steve Young, Milica Gašić, Blaise Thomson, and Jason D Williams. 2013 · 2013
Earlier work this paper cites.
Mixture of experts: a literature survey
Saeed Masoudnia and Reza Ebrahimpour. 2014 · 2014
Earlier work this paper cites.
Neural machine translation by jointly learning to align and translate. In International Conference on Learning Representations (ICLR ’15) . –
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2015 · 2015
Earlier work this paper cites.
Adam: A method for stochastic optimization. In International Conference on Learning Representations (ICLR ’15) . –
Diederik Kingma and Jimmy Ba. 2015 · 2015
Earlier work this paper cites.
Effective approaches to attention-based neural machine translation. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing (EMNLP ’15) . 1412–1421
Thang Luong, Hieu Pham, and Christopher D. Manning. 2015 · 2015
Earlier work this paper cites.
A neural network approach to context-sensitive generation of conversational responses. In Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT ’15) . 196–205
Alessandro Sordoni, Michel Galley, Michael Auli, Chris Brockett, Yangfeng Ji, Margaret Mitchell, Jian-Yun Nie, Jianfeng Gao, and Bill Dolan. 2015 · 2015
Earlier work this paper cites.
A neural conversational model. In ICML Deep Learning Workshop . –
Oriol Vinyals and Quoc Le. 2015 · 2015
Earlier work this paper cites.
Semantically conditioned lstm-based natural language generation for spoken dialogue systems. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing (EMNLP ’15) . 1711–1721
Tsung-Hsien Wen, Milica Gasic, Nikola Mrksic, Pei-Hao Su, David Vandyke, and Steve Young. 2015 · 2015
Earlier work this paper cites.
Task completion platform: A self-serve multi-domain goal oriented dialogue platform. In Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL ’16) . 47–51
Paul Crook, Alex Marin, Vipul Agarwal, Khushboo Aggarwal, Tasos Anastasakos, Ravi Bikkula, Daniel Boies, Asli Celikyilmaz, Senthilkumar Chandramohan, Zhaleh Feizollahi, et al · 2016
Cited alongside, same era.
A context-aware natural language generator for dialogue systems. In Proceedings of the 17th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL ’16) . 185–190
Ondrej Dušek and Filip Jurcıcek. 2016 · 2016
Cited alongside, same era.
A persona-based neural conversation model. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL ’16) . 994–1003
Jiwei Li, Michel Galley, Chris Brockett, Georgios P Spithourakis, Jianfeng Gao, and Bill Dolan. 2016 · 2016
Cited alongside, same era.
Building end-to-end dialogue systems using generative hierarchical neural network models. In Thirtieth AAAI Conference on Artificial Intelligence (AAAI ’16) . 3776–3784
Iulian Vlad Serban, Alessandro Sordoni, Yoshua Bengio, Aaron C Courville, and Joelle Pineau. 2016 · 2016
Hybrid code networks: practical and efficient end-to-end dialog control with supervised and reinforcement learning. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (ACL ’17) . 665–677
Jason D Williams, Kavosh Asadi, and Geoffrey Zweig. 2017 · 2017
Later among the works it cites.
Building task-oriented dialogue systems for online shopping. In Thirty-First AAAI Conference on Artificial Intelligence (AAAI ’2017) . 4618–4626
Zhao Yan, Nan Duan, Peng Chen, Ming Zhou, Jianshe Zhou, and Zhoujun Li. 2017 · 2017
Later among the works it cites.
MultiWOZ-A large-scale multi-domain wizard-of-oz dataset for task-oriented dialogue modelling. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP ’18) . 5016–5026
Paweł Budzianowski, Tsung-Hsien Wen, Bo-Hsiang Tseng, Iñigo Casanueva, Stefan Ultes, Osman Ramadan, and Milica Gasic. 2018b · 2018
Later among the works it cites.
Understanding back-translation at scale. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP ’18) . 489–500
Sergey Edunov, Myle Ott, Michael Auli, and David Grangier. 2018 · 2018
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Sequential dialogue context modeling for spoken language understanding. In Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue (SIGDIAL ’17) . 103–114
Ankur Bapna, Gokhan Tur, Dilek Hakkani-Tur, and Larry Heck. 2017 · 2017
Cited alongside, same era.
Learning end-to-end goal-oriented dialog. In International Conference on Learning Representations (ICLR ’17) . –
Antoine Bordes and Jason Weston. 2017 · 2017
Cited alongside, same era.
A survey on dialogue systems: Recent advances and new frontiers
Hongshen Chen, Xiaorui Liu, Dawei Yin, and Jiliang Tang. 2017b · 2017
Cited alongside, same era.
Dynamic time-aware attention to speaker roles and contexts for spoken language understanding. In Proceedings of 2017 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU ’17) . 554–560
Po-Chun Chen, Ta-Chung Chi, Shang-Yu Su, and Yun-Nung Chen. 2017a · 2017
Cited alongside, same era.
Key-value retrieval networks for task-oriented dialogue. In Proceedings of the 18th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL ’17) . 37–49
Mihail Eric, Lakshmi Krishnan, Francois Charette, and Christopher D Manning. 2017 · 2017
Cited alongside, same era.
Outrageously large neural networks: The sparsely-gated mixture-of-experts layer. In International Conference on Learning Representations (ICLR ’17) . –
Noam Shazeer, Azalia Mirhoseini, Krzysztof Maziarz, Andy Davis, Quoc Le, Geoffrey Hinton, and Jeff Dean. 2017 · 2017
Cited alongside, same era.
Towards end-to-end multi-domain dialogue modelling
Pawel Budzianowski, Iñigo Casanueva, Bo-Hsiang Tseng, and Milica Gasic. 2018a
Cited in the paper.
A network-based end-to-end trainable task-oriented dialogue system. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics (EACL ’17) . 438–449
Tsung-Hsien Wen, David Vandyke, Nikola Mrkšić, Milica Gasic, Lina M Rojas Barahona, Pei-Hao Su, Stefan Ultes, and Steve Young. 2017a
Cited in the paper.
Later among the works it cites.
Multi-source domain adaptation with mixture of experts. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP ’18) . 4694–4703
Jiang Guo, Darsh J Shah, and Regina Barzilay. 2018 · 2018
Later among the works it cites.
Sequicity: Simplifying task-oriented dialogue systems with single sequence-to-sequence architectures. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (ACL ’18) . 1437–1447
Wenqiang Lei, Xisen Jin, Min-Yen Kan, Zhaochun Ren, Xiangnan He, and Dawei Yin. 2018 · 2018
Later among the works it cites.
Multi-task learning for joint language understanding and dialogue state tracking. In Proceedings of the 19th Annual SIGdial Meeting on Discourse and Dialogue (SIGDIAL ’19) . 376–384
Abhinav Rastogi, Raghav Gupta, and Dilek Hakkani-Tur. 2018 · 2018
Later among the works it cites.
Global-locally self-attentive encoder for dialogue state tracking. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (ACL ’18) . 1458–1467
Victor Zhong, Caiming Xiong, and Richard Socher. 2018 · 2018
Later among the works it cites.
Granger-causal attentive mixtures of experts: Learning important features with neural networks. In AAAI Conference on Artificial Intelligence (AAAI ’19) . –
Patrick Schwab, Djordje Miladinovic, and Walter Karlen. 2019 · 2019
Closest in time.
Sanghyun Yi, Rahul Goel, Chandra Khatri, Tagyoung Chung, Behnam Hedayatnia, Anu Venkatesh, Raefer Gabriel, and Dilek Hakkani-Tur. 2019 · 2019
Closest in time.