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Dialogue State Tracking (DST), a key component of task-oriented conversation systems, represents user intentions by determining the values of pre-defined slots in an ongoing dialogue.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al. 2020 · 1901
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Mihail Eric, Rahul Goel, Shachi Paul, Adarsh Kumar, Abhishek Sethi, Peter Ku, Anuj Kumar Goyal, Sanchit Agarwal, Shuyang Gao, and Dilek Hakkani-Tur. 2019 · 1907
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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
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The dialog state tracking challenge series
Jason D Williams, Matthew Henderson, Antoine Raux, Blaise Thomson, Alan Black, and Deepak Ramachandran. 2014 · 2014
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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
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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
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter. 2018 · 2018
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Billion-scale similarity search with GPUs
Jeff Johnson, Matthijs Douze, and Hervé Jégou. 2019 · 2019
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Sentence-bert: Sentence embeddings using siamese bert-networks
Nils Reimers and Iryna Gurevych. 2019 · 2019
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Robust zero-shot cross-domain slot filling with example values
Darsh Shah, Raghav Gupta, Amir Fayazi, and Dilek Hakkani-Tur. 2019 · 2019
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Transferable multi-domain state generator for task-oriented dialogue systems
Chien-sheng Wu, Andrea Madotto, Ehsan Hosseini-asl, Ciaming Xiong, Richard Socher, and Pascale Ngan Fung. 2019 · 2019
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From machine reading comprehension to dialogue state tracking: Bridging the gap
Shuyang Gao, Sanchit Agarwal, Di Jin, Tagyoung Chung, and Dilek Hakkani-Tur. 2020 · 2020
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In search of lost domain generalization
Ishaan Gulrajani and David Lopez-Paz. 2020 · 2020
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Don’t stop pretraining: Adapt language models to domains and tasks
Suchin Gururangan, Ana Marasović, Swabha Swayamdipta, Kyle Lo, Iz Beltagy, Doug Downey, and Noah A Smith. 2020 · 2020
Cited alongside, same era.
Ma-dst: Multi-attention-based scalable dialog state tracking
Adarsh Kumar, Peter Ku, Anuj Goyal, Angeliki Metallinou, and Dilek Hakkani-Tur. 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, Peter J Liu, et al. 2020 · 2020
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Towards scalable multi-domain conversational agents: The schema-guided dialogue dataset
Abhinav Rastogi, Xiaoxue Zang, Srinivas Sunkara, Raghav Gupta, and Pranav Khaitan. 2020 · 2020
Cited alongside, same era.
Improving limited labeled dialogue state tracking with self-supervision
Chien-Sheng Wu, Steven CH Hoi, and Caiming Xiong. 2020 · 2020
Cited alongside, same era.
Few-shot bot: Prompt-based learning for dialogue systems
Andrea Madotto, Zhaojiang Lin, Genta Indra Winata, and Pascale Fung. 2021 · 2021
Later among the works it cites.
Calibrate before use: Improving few-shot performance of language models
Zihao Zhao, Eric Wallace, Shi Feng, Dan Klein, and Sameer Singh. 2021 · 2021
Later among the works it cites.
Meta-learning via language model in-context tuning
Yanda Chen, Ruiqi Zhong, Sheng Zha, George Karypis, and He He. 2022 · 2022
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Show, don’t tell: Demonstrations outperform descriptions for schema-guided task-oriented dialogue
Raghav Gupta, Harrison Lee, Jeffrey Zhao, Abhinav Rastogi, Yuan Cao, and Yonghui Wu. 2022 · 2022
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A comparative study on schema-guided dialogue state tracking
Jie Cao and Yi Zhang. 2021 · 2021
Cited alongside, same era.
Discovering dialogue slots with weak supervision
Vojtěch Hudeček, Ondřej Dušek, and Zhou Yu. 2021 · 2021
Cited alongside, same era.
Dialogue state tracking with a language model using schema-driven prompting
Chia-Hsuan Lee, Hao Cheng, and Mari Ostendorf. 2021 · 2021
Cited alongside, same era.
Zero-shot generalization in dialog state tracking through generative question answering
Shuyang Li, Jin Cao, Mukund Sridhar, Henghui Zhu, Shang-Wen Li, Wael Hamza, and Julian McAuley. 2021 · 2021
Cited alongside, same era.
Zero-shot dialogue state tracking via cross-task transfer
Zhaojiang Lin, Bing Liu, Andrea Madotto, Seungwhan Moon, Zhenpeng Zhou, Paul A Crook, Zhiguang Wang, Zhou Yu, Eunjoon Cho, Rajen Subba, et al. 2021a · 2021
Cited alongside, same era.
Leveraging slot descriptions for zero-shot cross-domain dialogue statetracking
Zhaojiang Lin, Bing Liu, Seungwhan Moon, Paul A Crook, Zhenpeng Zhou, Zhiguang Wang, Zhou Yu, Andrea Madotto, Eunjoon Cho, and Rajen Subba. 2021b · 2021
Cited alongside, same era.
What makes good in-context examples for gpt- 3 3 ?
Jiachang Liu, Dinghan Shen, Yizhe Zhang, Bill Dolan, Lawrence Carin, and Weizhu Chen. 2021 · 2021
Cited alongside, same era.
Yushi Hu, Chia-Hsuan Lee, Tianbao Xie, Tao Yu, Noah A Smith, and Mari Ostendorf. 2022 · 2022
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“do you follow me?”: A survey of recent approaches in dialogue state tracking
Léo Jacqmin, Lina M Rojas Barahona, and Benoit Favre. 2022 · 2022
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Few-shot parameter-efficient fine-tuning is better and cheaper than in-context learning
Haokun Liu, Derek Tam, Mohammed Muqeeth, Jay Mohta, Tenghao Huang, Mohit Bansal, and Colin Raffel. 2022 · 2022
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Cins: Comprehensive instruction for few-shot learning in task-oriented dialog systems
Fei Mi, Yasheng Wang, and Yitong Li. 2022 · 2022
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Rethinking the role of demonstrations: What makes in-context learning work?
Sewon Min, Xinxi Lyu, Ari Holtzman, Mikel Artetxe, Mike Lewis, Hannaneh Hajishirzi, and Luke Zettlemoyer. 2022 · 2022
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Dialogue summaries as dialogue states (ds2), template-guided summarization for few-shot dialogue state tracking
Jamin Shin, Hangyeol Yu, Hyeongdon Moon, Andrea Madotto, and Juneyoung Park. 2022 · 2022
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Tianbao Xie, Chen Henry Wu, Peng Shi, Ruiqi Zhong, Torsten Scholak, Michihiro Yasunaga, Chien-Sheng Wu, Ming Zhong, Pengcheng Yin, Sida I Wang, et al. 2022 · 2022
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Fedgen: Generalizable federated learning for sequential data
Praveen Venkateswaran, Vatche Isahagian, Vinod Muthusamy, and Nalini Venkatasubramanian. 2023 · 2023
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