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Dialogue state tracking (DST) aims to record user queries and goals during a conversational interaction achieved by maintaining a predefined set of slots and their corresponding values.
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, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 1901
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Efficient context and schema fusion networks for multi-domain dialogue state tracking
Su Zhu, Jieyu Li, Lu Chen, and Kai Yu. 2020 · 2004
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Word-based dialog state tracking with recurrent neural networks
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Neural belief tracker: Data-driven dialogue state tracking
Nikola Mrkšić, Diarmuid Ó Séaghdha, Tsung-Hsien Wen, Blaise Thomson, and Steve Young. 2017 · 2017
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A network-based end-to-end trainable task-oriented dialogue system
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MultiWOZ - a large-scale multi-domain Wizard-of-Oz dataset for task-oriented dialogue modelling
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Global-locally self-attentive encoder for dialogue state tracking
Victor Zhong, Caiming Xiong, and Richard Socher. 2018 · 2018
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SAMSum corpus: A human-annotated dialogue dataset for abstractive summarization
Bogdan Gliwa, Iwona Mochol, Maciej Biesek, and Aleksander Wawer. 2019 · 2019
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Transferable multi-domain state generator for task-oriented dialogue systems
Chien-Sheng Wu, Andrea Madotto, Ehsan Hosseini-Asl, Caiming Xiong, Richard Socher, and Pascale Fung. 2019 · 2019
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Schema-guided multi-domain dialogue state tracking with graph attention neural networks
Lu Chen, Boer Lv, Chi Wang, Su Zhu, Bowen Tan, and Kai Yu. 2020 · 2020
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A simple language model for task-oriented dialogue
Ehsan Hosseini-Asl, Bryan McCann, Chien-Sheng Wu, Semih Yavuz, and Richard Socher. 2020 · 2020
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Efficient dialogue state tracking by selectively overwriting memory
Sungdong Kim, Sohee Yang, Gyuwan Kim, and Sang-Woo Lee. 2020 · 2020
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A sequence-to-sequence approach to dialogue state tracking
Yue Feng, Yang Wang, and Hang Li. 2021 · 2021
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Dialogue state tracking with a language model using schema-driven prompting
Chia-Hsuan Lee, Hao Cheng, and Mari Ostendorf. 2021a · 2021
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Dialogue state tracking with a language model using schema-driven prompting
Chia-Hsuan Lee, Hao Cheng, and Mari Ostendorf. 2021b · 2021
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The power of scale for parameter-efficient prompt tuning
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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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Amendable generation for dialogue state tracking
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Effective sequence-to-sequence dialogue state tracking
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Description-driven task-oriented dialog modeling
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Beyond the granularity: Multi-perspective dialogue collaborative selection for dialogue state tracking
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Unified dialog model pre-training for task-oriented dialog understanding and generation
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Least-to-most prompting enables complex reasoning in large language models
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Codegen: An open large language model for code with multi-turn program synthesis
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Self-consistency improves chain of thought reasoning in language models
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