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To diversify and enrich generated dialogue responses, knowledge-grounded dialogue has been investigated in recent years.
Distilling task-specific knowledge from BERT into simple neural networks
Raphael Tang, Yao Lu, Linqing Liu, Lili Mou, Olga Vechtomova, and Jimmy Lin. 2019 · 1903
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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. 2019 · 1910
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Distilbert, a distilled version of BERT: smaller, faster, cheaper and lighter
Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf. 2019 · 1910
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K-adapter: Infusing knowledge into pre-trained models with adapters
Ruize Wang, Duyu Tang, Nan Duan, Zhongyu Wei, Xuanjing Huang, Cuihong Cao, Daxin Jiang, Ming Zhou, et al. 2020 · 2002
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Recipes for building an open-domain chatbot
Stephen Roller, Emily Dinan, Naman Goyal, Da Ju, Mary Williamson, Yinhan Liu, Jing Xu, Myle Ott, Kurt Shuster, Eric M Smith, et al. 2020 · 2004
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Unsupervised commonsense question answering with self-talk
Vered Shwartz, Peter West, Ronan Le Bras, Chandra Bhagavatula, and Yejin Choi. 2020 · 2004
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Language models are few-shot learners
Tom B Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al. 2020 · 2005
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Anne Lauscher, Olga Majewska, Leonardo FR Ribeiro, Iryna Gurevych, Nikolai Rozanov, and Goran Glavaš. 2020 · 2005
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Autoprompt: Eliciting knowledge from language models with automatically generated prompts
Taylor Shin, Yasaman Razeghi, Robert L Logan IV, Eric Wallace, and Sameer Singh. 2020 · 2010
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba. 2015 · 2015
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Lei Jimmy Ba, Jamie Ryan Kiros, and Geoffrey E. Hinton. 2016 · 2016
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A diversity-promoting objective function for neural conversation models
Jiwei Li, Michel Galley, Chris Brockett, Jianfeng Gao, and William B Dolan. 2016 · 2016
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SemEval-2017 task 1: Semantic textual similarity multilingual and crosslingual focused evaluation
Daniel Cer, Mona Diab, Eneko Agirre, Iñigo Lopez-Gazpio, and Lucia Specia. 2017 · 2017
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Supervised learning of universal sentence representations from natural language inference data
Alexis Conneau, Douwe Kiela, Holger Schwenk, Loïc Barrault, and Antoine Bordes. 2017 · 2017
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Autoencoding variational inference for topic models
Akash Srivastava and Charles Sutton. 2017 · 2017
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A dataset for document grounded conversations
Kangyan Zhou, Shrimai Prabhumoye, and Alan W Black. 2018 · 2018
Cited alongside, same era.
Simple, scalable adaptation for neural machine translation
Ankur Bapna and Orhan Firat. 2019 · 2019
Cited alongside, same era.
Wizard of wikipedia: Knowledge-powered conversational agents
Emily Dinan, Stephen Roller, Kurt Shuster, Angela Fan, Michael Auli, and Jason Weston. 2019 · 2019
Cited alongside, same era.
Sequential latent knowledge selection for knowledge-grounded dialogue
Byeongchang Kim, Jaewoo Ahn, and Gunhee Kim. 2019 · 2019
Cited alongside, same era.
Learning to select knowledge for response generation in dialog systems
Rongzhong Lian, Min Xie, Fan Wang, Jinhua Peng, and Hua Wu. 2019 · 2019
Cited alongside, same era.
Language models as knowledge bases?
Fabio Petroni, Tim Rocktäschel, Sebastian Riedel, Patrick Lewis, Anton Bakhtin, Yuxiang Wu, and Alexander Miller. 2019 · 2019
Learning knowledge bases with parameters for task-oriented dialogue systems
Andrea Madotto, Samuel Cahyawijaya, Genta Indra Winata, Yan Xu, Zihan Liu, Zhaojiang Lin, and Pascale Fung. 2020 · 2020
Later among the works it cites.
tBERT: Topic models and BERT joining forces for semantic similarity detection
Nicole Peinelt, Dong Nguyen, and Maria Liakata. 2020 · 2020
Later among the works it cites.
How much knowledge can you pack into the parameters of a language model?
Adam Roberts, Colin Raffel, and Noam Shazeer. 2020 · 2020
Later among the works it cites.
MobileBERT: a compact task-agnostic BERT for resource-limited devices
Zhiqing Sun, Hongkun Yu, Xiaodan Song, Renjie Liu, Yiming Yang, and Denny Zhou. 2020 · 2020
Later among the works it cites.
Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander M. Rush. 2020 · 2020
Later among the works it cites.
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Cited alongside, same era.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
Cited alongside, same era.
Sentence-BERT: Sentence embeddings using Siamese BERT-networks
Nils Reimers and Iryna Gurevych. 2019 · 2019
Cited alongside, same era.
Fast structured decoding for sequence models
Zhiqing Sun, Zhuohan Li, Haoqing Wang, Di He, Zi Lin, and Zhihong Deng. 2019 · 2019
Cited alongside, same era.
Low-resource knowledge-grounded dialogue generation
Xueliang Zhao, Wei Wu, Chongyang Tao, Can Xu, Dongyan Zhao, and Rui Yan. 2019 · 2019
Cited alongside, same era.
DeFormer: Decomposing pre-trained transformers for faster question answering
Qingqing Cao, Harsh Trivedi, Aruna Balasubramanian, and Niranjan Balasubramanian. 2020 · 2020
Cited alongside, same era.
Bridging the gap between prior and posterior knowledge selection for knowledge-grounded dialogue generation
Xiuyi Chen, Fandong Meng, Peng Li, Feilong Chen, Shuang Xu, Bo Xu, and Jie Zhou. 2020 · 2020
Cited alongside, same era.
Knowledge-grounded dialogue generation with pre-trained language models
Xueliang Zhao, Wei Wu, Can Xu, Chongyang Tao, Dongyan Zhao, and Rui Yan. 2020 · 2020
Later among the works it cites.
Pre-training is a hot topic: Contextualized document embeddings improve topic coherence
Federico Bianchi, Silvia Terragni, and Dirk Hovy. 2021 · 2021
Closest in time.
Autoregressive entity retrieval
Nicola De Cao, Gautier Izacard, Sebastian Riedel, and Fabio Petroni. 2021 · 2021
Closest in time.
Knowledge enhanced fine-tuning for better handling unseen entities in dialogue generation
Leyang Cui, Yu Wu, Shujie Liu, and Yue Zhang. 2021 · 2021
Closest in time.
Frontal language areas do not emerge in the absence of temporal language areas: A case study of an individual born without a left temporal lobe
Greta Tuckute, Alexander Paunov, Hope Kean, Hannah Small, Zachary Mineroff, Idan Blank, and Evelina Fedorenko. 2021 · 2021
Closest in time.
Can generative pre-trained language models serve as knowledge bases for closed-book qa?
Cunxiang Wang, Pai Liu, and Yue Zhang. 2021 · 2021
Closest in time.
Dialogue-oriented pre-training
Yi Xu and Hai Zhao. 2021 · 2021
Closest in time.
Think before you speak: Learning to generate implicit knowledge for response generation by self-talk
Pei Zhou, Behnam Hedayatnia, Karthik Gopalakrishnan, Seokhwan Kim, Jay Pujara, Xiang Ren, Yang Liu, and Dilek Hakkani-Tur. 2021 · 2021
Closest in time.
Multi-stage prompting for knowledgeable dialogue generation
Zihan Liu, Mostofa Patwary, Ryan Prenger, Shrimai Prabhumoye, Wei Ping, Mohammad Shoeybi, and Bryan Catanzaro. 2022 · 2022
Closest in time.