Fetching the paper…
Reading the bibliography…
Multi-turn dialogue modeling as a challenging branch of natural language understanding (NLU), aims to build representations for machines to understand human dialogues, which provides a solid foundation for multiple downstream tasks.
Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
Earlier work this paper cites.
Adaptive mixtures of local experts
Robert A. Jacobs, Michael I. Jordan, Steven J. Nowlan, and Geoffrey E. Hinton. 1991 · 1991
Earlier work this paper cites.
Task-specific objectives of pre-trained language models for dialogue adaptation
Junlong Li, Zhuosheng Zhang, Hai Zhao, Xi Zhou, and Xiang Zhou. 2020b · 2009
Earlier work this paper cites.
The Ubuntu dialogue corpus: A large dataset for research in unstructured multi-turn dialogue systems
Ryan Lowe, Nissan Pow, Iulian Serban, and Joelle Pineau. 2015 · 2015
Earlier work this paper cites.
SQuAD: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Earlier work this paper cites.
Sequential matching network: A new architecture for multi-turn response selection in retrieval-based chatbots
Yu Wu, Wei Wu, Chen Xing, Ming Zhou, and Zhoujun Li. 2017 · 2017
Earlier work this paper cites.
Modeling multi-turn conversation with deep utterance aggregation
Zhuosheng Zhang, Jiangtong Li, Pengfei Zhu, Hai Zhao, and Gongshen Liu. 2018 · 2018
Earlier work this paper cites.
Multi-turn response selection for chatbots with deep attention matching network
Xiangyang Zhou, Lu Li, Daxiang Dong, Yi Liu, Ying Chen, Wayne Xin Zhao, Dianhai Yu, and Hua Wu. 2018 · 2018
Earlier work this paper cites.
BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Earlier work this paper cites.
SAMSum corpus: A human-annotated dialogue dataset for abstractive summarization
Bogdan Gliwa, Iwona Mochol, Maciej Biesek, and Aleksander Wawer. 2019 · 2019
Earlier work this paper cites.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al. 2019 · 2019
Earlier work this paper cites.
CoQA: A conversational question answering challenge
Siva Reddy, Danqi Chen, and Christopher D. Manning. 2019 · 2019
Earlier work this paper cites.
Do neural dialog systems use the conversation history effectively? an empirical study
Chinnadhurai Sankar, Sandeep Subramanian, Chris Pal, Sarath Chandar, and Yoshua Bengio. 2019 · 2019
Cited alongside, same era.
Improving machine reading comprehension with general reading strategies
Kai Sun, Dian Yu, Dong Yu, and Claire Cardie. 2019b · 2019
Cited alongside, same era.
FriendsQA: Open-domain question answering on TV show transcripts
Zhengzhe Yang and Jinho D. Choi. 2019 · 2019
Cited alongside, same era.
Multi-view sequence-to-sequence models with conversational structure for abstractive dialogue summarization
Jiaao Chen and Diyi Yang. 2020 · 2020
Cited alongside, same era.
Neural dialogue state tracking with temporally expressive networks
Junfan Chen, Richong Zhang, Yongyi Mao, and Jie Xu. 2020 · 2020
Cited alongside, same era.
ELECTRA: pre-training text encoders as discriminators rather than generators
Language model as an annotator: Exploring DialoGPT for dialogue summarization
Xiachong Feng, Xiaocheng Feng, Libo Qin, Bing Qin, and Ting Liu. 2021 · 2021
Later among the works it cites.
Dialogbert: Discourse-aware response generation via learning to recover and rank utterances
Xiaodong Gu, Kang Min Yoo, and Jung-Woo Ha. 2021 · 2021
Later among the works it cites.
Dadgraph: A discourse-aware dialogue graph neural network for multiparty dialogue machine reading comprehension
Jiaqi Li, Ming Liu, Zihao Zheng, Heng Zhang, Bing Qin, Min-Yen Kan, and Ting Liu. 2021a · 2021
Later among the works it cites.
Filling the gap of utterance-aware and speaker-aware representation for multi-turn dialogue
Longxiang Liu, Zhuosheng Zhang, Hai Zhao, Xi Zhou, and Xiang Zhou. 2021a · 2021
Later among the works it cites.
A graph reasoning network for multi-turn response selection via customized pre-training
Yongkang Liu, Shi Feng, Daling Wang, Kaisong Song, Feiliang Ren, and Yifei Zhang. 2021b · 2021
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Kevin Clark, Minh-Thang Luong, Quoc V. Le, and Christopher D. Manning. 2020 · 2020
Cited alongside, same era.
MuTual: A dataset for multi-turn dialogue reasoning
Leyang Cui, Yu Wu, Shujie Liu, Yue Zhang, and Ming Zhou. 2020 · 2020
Cited alongside, same era.
ALBERT: A lite BERT for self-supervised learning of language representations
Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, and Radu Soricut. 2020 · 2020
Cited alongside, same era.
BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer. 2020 · 2020
Cited alongside, same era.
Transformers to learn hierarchical contexts in multiparty dialogue for span-based question answering
Changmao Li and Jinho D. Choi. 2020 · 2020
Cited alongside, same era.
Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020 · 2020
Cited alongside, same era.
DialogSum: A real-life scenario dialogue summarization dataset
Yulong Chen, Yang Liu, Liang Chen, and Yue Zhang. 2021 · 2021
Cited alongside, same era.
Co-gat: A co-interactive graph attention network for joint dialog act recognition and sentiment classification
Libo Qin, Zhouyang Li, Wanxiang Che, Minheng Ni, and Ting Liu. 2021b · 2021
Later among the works it cites.
Multi-turn dialogue reading comprehension with pivot turns and knowledge
Zhuosheng Zhang, Junlong Li, and Hai Zhao. 2021 · 2021
Later among the works it cites.
Post-training dialogue summarization using pseudo-paraphrasing
Qi Jia, Yizhu Liu, Haifeng Tang, and Kenny Q. Zhu. 2022 · 2022
Closest in time.
Semantic-preserving adversarial code comprehension
Yiyang Li, Hongqiu Wu, and Hai Zhao. 2022 · 2022
Closest in time.
Forging multiple training objectives for pre-trained language models via meta-learning
Hongqiu Wu, Ruixue Ding, Hai Zhao, Boli Chen, Pengjun Xie, Fei Huang, and Min Zhang. 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.
Self- and pseudo-self-supervised prediction of speaker and key-utterance for multi-party dialogue reading comprehension
Yiyang Li and Hai Zhao. 2021 · 2063
Closest in time.