Fetching the paper…
Reading the bibliography…
Clarification questions are an essential dialogue tool to signal misunderstanding, ambiguities, and under-specification in language use.
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.
Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter
Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf. 2019 · 1910
Earlier work this paper cites.
Verification of forecasts expressed in terms of probability
Glenn W Brier. 1950 · 1950
Earlier work this paper cites.
The construction of reality in the child (vol. xiii)
J Piaget. 1954 · 1954
Earlier work this paper cites.
The preference for self-correction in the organization of repair in conversation
Emanuel A Schegloff, Gail Jefferson, and Harvey Sacks. 1977 · 1977
Earlier work this paper cites.
Feedback to first language learners: The role of repetitions and clarification questions
Marty J Demetras, Kathryn Nolan Post, and Catherine E Snow. 1986 · 1986
Earlier work this paper cites.
Collaborating on contributions to conversations
Herbert H Clark and Edward F Schaefer. 1987 · 1987
Earlier work this paper cites.
Some sources of misunderstanding in talk-in-interaction
Emanuel A. Schegloff. 1987 · 1987
Earlier work this paper cites.
Grounding in communication
Herbert H Clark and Susan E Brennan. 1991 · 1991
Earlier work this paper cites.
Using language
Herbert H Clark. 1996 · 1996
Earlier work this paper cites.
Conversation as action under uncertainty
Tim Paek and Eric Horvitz. 2000 · 2000
Earlier work this paper cites.
On the means for clarification in dialogue
Matthew Purver, Jonathan Ginzburg, and Patrick Healey. 2001 · 2001
Earlier work this paper cites.
Clarification in spoken dialogue systems
Malte Gabsdil. 2003 · 2003
Earlier work this paper cites.
The theory and use of clarification requests in dialogue
Matthew Richard John Purver. 2004 · 2004
Earlier work this paper cites.
Form, intonation and function of clarification requests in german task-oriented spoken dialogues
Kepa Joseba Rodríguez and David Schlangen. 2004 · 2004
Earlier work this paper cites.
Causes and strategies for requesting clarification in dialogue
David Schlangen. 2004 · 2004
Earlier work this paper cites.
Implications for generating clarification requests in task-oriented dialogues
Verena Rieser and Johanna D Moore. 2005 · 2005
Earlier work this paper cites.
Using machine learning to explore human multimodal clarification strategies
Verena Rieser and Oliver Lemon. 2006 · 2006
Earlier work this paper cites.
Children’s questions: A mechanism for cognitive development
Michelle M Chouinard, Paul L Harris, and Michael P Maratsos. 2007 · 2007
Earlier work this paper cites.
Galatea: A discourse modeller supporting concept-level error handling in spoken dialogue systems
Gabriel Skantze. 2008 · 2008
Earlier work this paper cites.
Clarification potential of instructions
Luciana Benotti. 2009 · 2009
Earlier work this paper cites.
A comparison of LSTM and BERT for small corpus
Aysu Ezen-Can. 2020 · 2009
Earlier work this paper cites.
The cultural origins of human cognition
Michael Tomasello. 2009 · 2009
Earlier work this paper cites.
Father input and child vocabulary development: The importance of wh questions and clarification requests
Kathryn A Leech, Virginia C Salo, Meredith L Rowe, and Natasha J Cabrera. 2013 · 2013
Earlier work this paper cites.
Bringing semantics into focus using visual abstraction
C Lawrence Zitnick and Devi Parikh. 2013 · 2013
Cited alongside, same era.
Clarification requests on the level of uptake
Julian J Schlöder and Raquel Fernández. 2014 · 2014
Cited alongside, same era.
Towards natural clarification questions in dialogue systems
Svetlana Stoyanchev, Alex Liu, and Julia Hirschberg. 2014 · 2014
Cited alongside, same era.
Obtaining well calibrated probabilities using bayesian binning
Mahdi Pakdaman Naeini, Gregory Cooper, and Milos Hauskrecht. 2015 · 2015
Cited alongside, same era.
Sources of developmental change in the efficiency of information search
Azzurra Ruggeri, Tania Lombrozo, Thomas L Griffiths, and Fei Xu. 2016 · 2016
Cited alongside, same era.
Modeling the clarification potential of instructions: Predicting clarification requests and other reactions
Luciana Benotti and Patrick Blackburn. 2017 · 2017
Grounding ‘grounding’ in NLP
Khyathi Raghavi Chandu, Yonatan Bisk, and Alan W Black. 2021 · 2021
Later among the works it cites.
How should agents ask questions for situated learning? an annotated dialogue corpus
Felix Gervits, Antonio Roque, Gordon Briggs, Matthias Scheutz, and Matthew Marge. 2021 · 2021
Later among the works it cites.
Aleatoric and epistemic uncertainty in machine learning: An introduction to concepts and methods
Eyke Hüllermeier and Willem Waegeman. 2021 · 2021
Later among the works it cites.
Hierarchical conditional relation networks for multimodal video question answering
Thao Minh Le, Vuong Le, Svetha Venkatesh, and Truyen Tran. 2021 · 2021
Later among the works it cites.
Towards facet-driven generation of clarifying questions for conversational search
Ivan Sekulić, Mohammad Aliannejadi, and Fabio Crestani. 2021 · 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…
Cited alongside, same era.
On calibration of modern neural networks
Chuan Guo, Geoff Pleiss, Yu Sun, and Kilian Q Weinberger. 2017 · 2017
Cited alongside, same era.
What uncertainties do we need in bayesian deep learning for computer vision?
Alex Kendall and Yarin Gal. 2017 · 2017
Cited alongside, same era.
Simple and scalable predictive uncertainty estimation using deep ensembles
Balaji Lakshminarayanan, Alexander Pritzel, and Charles Blundell. 2017 · 2017
Cited alongside, same era.
“why is toma late to school again?” preschoolers identify the most informative questions
Azzurra Ruggeri, Zi Lin Sim, and Fei Xu. 2017 · 2017
Cited alongside, same era.
Decomposition of uncertainty in bayesian deep learning for efficient and risk-sensitive learning
Stefan Depeweg, Jose-Miguel Hernandez-Lobato, Finale Doshi-Velez, and Steffen Udluft. 2018 · 2018
Cited alongside, same era.
Do people ask good questions?
Anselm Rothe, Brenden M Lake, and Todd M Gureckis. 2018 · 2018
Cited alongside, same era.
Alberto Testoni and Raffaella Bernardi. 2021 · 2021
Later among the works it cites.
Diverse and specific clarification question generation with keywords
Zhiling Zhang and Kenny Zhu. 2021 · 2021
Later among the works it cites.
Self-motivated communication agent for real-world vision-dialog navigation
Yi Zhu, Yue Weng, Fengda Zhu, Xiaodan Liang, Qixiang Ye, Yutong Lu, and Jianbin Jiao. 2021 · 2021
Later among the works it cites.
Dialfred: Dialogue-enabled agents for embodied instruction following
Xiaofeng Gao, Qiaozi Gao, Ran Gong, Kaixiang Lin, Govind Thattai, and Gaurav S Sukhatme. 2022 · 2022
Later among the works it cites.
Dialog acts for task driven embodied agents
Spandana Gella, Aishwarya Padmakumar, Patrick Lange, and Dilek Hakkani-Tur. 2022 · 2022
Later among the works it cites.
A small but informed and diverse model: The case of the multimodal GuessWhat!? guessing game
Claudio Greco, Alberto Testoni, Raffaella Bernardi, and Stella Frank. 2022 · 2022
Later among the works it cites.
Julia Kiseleva, Alexey Skrynnik, Artem Zholus, Shrestha Mohanty, Negar Arabzadeh, Marc-Alexandre Côté, Mohammad Aliannejadi, Milagro Teruel, Ziming Li, Mikhail Burtsev, et al. 2022 · 2022
Later among the works it cites.
Collecting interactive multi-modal datasets for grounded language understanding
Shrestha Mohanty, Negar Arabzadeh, Milagro Teruel, Yuxuan Sun, Artem Zholus, Alexey Skrynnik, Mikhail Burtsev, Kavya Srinet, Aleksandr Panov, Arthur Szlam, et al. 2022 · 2022
Later among the works it cites.
Visual descriptor extraction from patent figure captions: A case study of data efficiency between bilstm and transformer
Xin Wei, Jian Wu, Kehinde Ajayi, and Diane Oyen. 2022 · 2022
Later among the works it cites.
Uncertainty in natural language generation: From theory to applications
Joris Baan, Nico Daheim, Evgenia Ilia, Dennis Ulmer, Haau-Sing Li, Raquel Fernández, Barbara Plank, Rico Sennrich, Chrysoula Zerva, and Wilker Aziz. 2023 · 2023
Later among the works it cites.
’What are you referring to?’ Evaluating the ability of multi-modal dialogue models to process clarificational exchanges
Javier Chiyah-Garcia, Alessandro Suglia, Arash Eshghi, and Helen Hastie. 2023 · 2023
Later among the works it cites.
Yang Deng, Wenqiang Lei, Lizi Liao, and Tat-Seng Chua. 2023 · 2023
Later among the works it cites.
Aligning predictive uncertainty with clarification questions in grounded dialog
Kata Naszadi, Putra Manggala, and Christof Monz. 2023 · 2023
Later among the works it cites.
Dealing with semantic underspecification in multimodal NLP
Sandro Pezzelle. 2023 · 2023
Later among the works it cites.
Semantic adaptation to the interpretation of gradable adjectives via active linguistic interaction
Sandro Pezzelle and Raquel Fernández. 2023 · 2023
Later among the works it cites.
Learning by asking for embodied visual navigation and task completion
Ying Shen and Ismini Lourentzou. 2023 · 2023
Later among the works it cites.
Teach: Task-driven embodied agents that chat
Aishwarya Padmakumar, Jesse Thomason, Ayush Shrivastava, Patrick Lange, Anjali Narayan-Chen, Spandana Gella, Robinson Piramuthu, Gokhan Tur, and Dilek Hakkani-Tur. 2022 · 2025
Closest in time.
Learning to execute actions or ask clarification questions
Zhengxiang Shi, Yue Feng, and Aldo Lipani. 2022 · 2070
Closest in time.