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Dialogue systems are usually categorized into two types, open-domain and task-oriented.
Towards a human-like open-domain chatbot
Daniel Adiwardana, Minh-Thang Luong, David R So, Jamie Hall, Noah Fiedel, Romal Thoppilan, Zi Yang, Apoorv Kulshreshtha, Gaurav Nemade, Yifeng Lu, et al. 2020b · 2001
Earlier work this paper cites.
Reinforcement learning of cooperative persuasive dialogue policies using framing
Takuya Hiraoka, Graham Neubig, Sakriani Sakti, Tomoki Toda, and Satoshi Nakamura. 2014 · 2014
Earlier work this paper cites.
DailyDialog: A manually labelled multi-turn dialogue dataset
Yanran Li, Hui Su, Xiaoyu Shen, Wenjie Li, Ziqiang Cao, and Shuzi Niu. 2017 · 2017
Earlier work this paper cites.
Parlai: A dialog research software platform
A. H. Miller, W. Feng, A. Fisch, J. Lu, D. Batra, A. Bordes, D. Parikh, and J. Weston. 2017 · 2017
Earlier work this paper cites.
Bilateral multi-perspective matching for natural language sentences
Zhiguo Wang, Wael Hamza, and Radu Florian. 2017 · 2017
Earlier work this paper cites.
Learning conversational systems that interleave task and non-task content
Zhou Yu, Alan W Black, and Alexander I. Rudnicky. 2017 · 2017
Earlier work this paper cites.
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 Gašić. 2018 · 2018
Earlier work this paper cites.
Hierarchical neural story generation
Angela Fan, Mike Lewis, and Yann Dauphin. 2018 · 2018
Earlier work this paper cites.
Know what you don’t know: Unanswerable questions for SQuAD
Pranav Rajpurkar, Robin Jia, and Percy Liang. 2018 · 2018
Earlier work this paper cites.
Adafactor: Adaptive learning rates with sublinear memory cost
Noam Shazeer and Mitchell Stern. 2018 · 2018
Earlier work this paper cites.
Dialogue scenario collection of persuasive dialogue with emotional expressions via crowdsourcing
Koichiro Yoshino, Yoko Ishikawa, Masahiro Mizukami, Yu Suzuki, Sakriani Sakti, and Satoshi Nakamura. 2018 · 2018
Earlier work this paper cites.
SWAG: A large-scale adversarial dataset for grounded commonsense inference
Rowan Zellers, Yonatan Bisk, Roy Schwartz, and Yejin Choi. 2018 · 2018
Cited alongside, same era.
Personalizing dialogue agents: I have a dog, do you have pets too?
Saizheng Zhang, Emily Dinan, Jack Urbanek, Arthur Szlam, Douwe Kiela, and Jason Weston. 2018 · 2018
Cited alongside, same era.
Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter. 2019 · 2019
Cited alongside, same era.
Commonsenseqa: A question answering challenge targeting commonsense knowledge
Alon Talmor, Jonathan Herzig, Nicholas Lourie, and Jonathan Berant. 2019 · 2019
Cited alongside, same era.
Target-guided open-domain conversation
Jianheng Tang, Tiancheng Zhao, Chenyan Xiong, Xiaodan Liang, Eric Xing, and Zhiting Hu. 2019 · 2019
Cited alongside, same era.
Towards scalable multi-domain conversational agents: The schema-guided dialogue dataset
Abhinav Rastogi, Xiaoxue Zang, Srinivas Sunkara, Raghav Gupta, and Pranav Khaitan. 2020 · 2020
Later among the works it cites.
Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter
Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf. 2020 · 2020
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 William B Dolan. 2020 · 2020
Later among the works it cites.
Towards a universal nlg for dialogue systems and simulators with future bridging
Philipp Ennen, Yen-Ting Lin, Ali Girayhan Ozbay, Ferdinando Insalata, Maolin Li, Ye Tian, Sepehr Jalali, and Da shan Shiu. 2021 · 2021
Later among the works it cites.
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Xuewei Wang, Weiyan Shi, Richard Kim, Yoojung Oh, Sijia Yang, Jingwen Zhang, and Zhou Yu. 2019 · 2019
Cited alongside, same era.
The curious case of neural text degeneration
Ari Holtzman, Jan Buys, Li Du, Maxwell Forbes, and Yejin Choi. 2020 · 2020
Cited alongside, same era.
A simple language model for task-oriented dialogue
Ehsan Hosseini-Asl, Bryan McCann, Chien-Sheng Wu, Semih Yavuz, and Richard Socher. 2020 · 2020
Cited alongside, same era.
Towards conversational recommendation over multi-type dialogs
Zeming Liu, Haifeng Wang, Zheng-Yu Niu, Hua Wu, Wanxiang Che, and Ting Liu. 2020 · 2020
Cited alongside, same era.
Language model is all you need: Natural language understanding as question answering
Mahdi Namazifar, Alexandros Papangelis, Gokhan Tur, and Dilek Hakkani-Tür. 2020 · 2020
Cited alongside, same era.
Towards a human-like open-domain chatbot
Daniel Adiwardana, Minh-Thang Luong, David R. So, Jamie Hall, Noah Fiedel, Romal Thoppilan, Zi Yang, Apoorv Kulshreshtha, Gaurav Nemade, Yifeng Lu, and Quoc V. Le. 2020a
Cited in the paper.
Zhaojiang Lin, Bing Liu, Andrea Madotto, Seungwhan Moon, Zhenpeng Zhou, Paul Crook, Zhiguang Wang, Zhou Yu, Eunjoon Cho, Rajen Subba, and Pascale Fung. 2021 · 2021
Later among the works it cites.
Recipes for building an open-domain chatbot
Stephen Roller, Emily Dinan, Naman Goyal, Da Ju, Mary Williamson, Yinhan Liu, Jing Xu, Myle Ott, Eric Michael Smith, Y-Lan Boureau, et al. 2021 · 2021
Later among the works it cites.
OTTers: One-turn topic transitions for open-domain dialogue
Karin Sevegnani, David M. Howcroft, Ioannis Konstas, and Verena Rieser. 2021 · 2021
Later among the works it cites.
Adding chit-chat to enhance task-oriented dialogues
Kai Sun, Seungwhan Moon, Paul Crook, Stephen Roller, Becka Silvert, Bing Liu, Zhiguang Wang, Honglei Liu, Eunjoon Cho, and Claire Cardie. 2021 · 2021
Later among the works it cites.
Fusing task-oriented and open-domain dialogues in conversational agents
Tom Young, Frank Xing, Vlad Pandelea, Jinjie Ni, and Erik Cambria. 2022 · 2022
Closest in time.
Can you put it all together: Evaluating conversational agents’ ability to blend skills
Eric Michael Smith, Mary Williamson, Kurt Shuster, Jason Weston, and Y-Lan Boureau. 2020 · 2030
Closest in time.