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The ability to handle miscommunication is crucial to robust and faithful conversational AI.
The preference for self-correction in the organization of repair in conversation
E.A. Schegloff, Gail Jefferson, and Harvey Sacks. 1977 · 1977
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Conversational organization: Interaction between speakers and hearers
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Repair after next turn: The last structurally provided defense of intersubjectivity in conversation
E.A. Schegloff. 1992 · 1992
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Designing confirmation mechanisms and error recover techniques in a railway information system for Spanish
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CLARIE: the Clarification Engine
Matthew Purver. 2004 · 2004
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Clarifying noun phrase semantics
Matthew Purver and Jonathan Ginzburg. 2004 · 2004
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Form, intonation and function of clarification requests in German task-oriented spoken dialogues
Kepa Rodríguez and David Schlangen. 2004 · 2004
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Implications for generating clarification requests in task-oriented dialogues
Verena Rieser and Johanna Moore. 2005 · 2005
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Using machine learning to explore human multimodal clarification strategies
Verena Rieser and Oliver Lemon. 2006 · 2006
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Semantic co-ordination in dialogue: the role of direct interaction
Gregory J. Mills. 2007 · 2007
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Towards incremental speech generation in dialogue systems
Gabriel Skantze and Anna Hjalmarsson. 2010 · 2010
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Dium : An incremental dialogue manager that can produce self-corrections
Okko Buß and David Schlangen. 2011 · 2011
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Processing self-repairs in an incremental type-theoretic dialogue system
Julian Hough and Matthew Purver. 2012 · 2012
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Universal principles in the repair of communication problems
Mark Dingemanse, Seán G. Roberts, Julija Baranova, Joe Blythe, Paul Drew, Simeon Floyd, Rosa S. Gisladottir, Kobin H. Kendrick, Stephen C. Levinson, Elizabeth Manrique, Giovanni Rossi, and N. J. Enfield. 2015 · 2015
Transforming question answering datasets into natural language inference datasets
Dorottya Demszky, Kelvin Guu, and Percy Liang. 2018 · 2018
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Running Repairs: Coordinating Meaning in Dialogue
Patrick G. T. Healey, Gregory J. Mills, Arash Eshghi, and Christine Howes. 2018 · 2018
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Computational models of miscommunication phenomena
Matthew Purver, Julian Hough, and Christine Howes. 2018 · 2018
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Benchmarking zero-shot text classification: Datasets, evaluation and entailment approach
Wenpeng Yin, Jamaal Hay, and Dan Roth. 2019 · 2019
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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, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher 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 · 2020
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Modelling Incremental Self-Repair Processing in Dialogue
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Recurrent neural networks for incremental disfluency detection
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Challenging neural dialogue models with natural data: Memory networks fail on incremental phenomena
Igor Shalyminov, Arash Eshghi, and Oliver Lemon. 2017 · 2017
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Alana v2: Entertaining and informative open-domain social dialogue using ontologies and entity linking
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AmbigQA: Answering ambiguous open-domain questions
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Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Remi 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 Rush. 2020 · 2020
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Bertscore: Evaluating text generation with BERT
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q. Weinberger, and Yoav Artzi. 2020 · 2020
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Open-domain question answering goes conversational via question rewriting
Raviteja Anantha, Svitlana Vakulenko, Zhucheng Tu, Shayne Longpre, Stephen Pulman, and Srinivas Chappidi. 2021 · 2021
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Exploring the limits of transfer learning with a unified text-to-text transformer
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