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We propose TuringAdvice, a new challenge task and dataset for language understanding models.
Learning and evaluating general linguistic intelligence
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The information bottleneck method
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Towards a human-like open-domain chatbot
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Adversarial filters of dataset biases
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Fill in the blanc: Human-free quality estimation of document summaries
Oleg Vasilyev, Vedant Dharnidharka, and John Bohannon. 2020 · 2002
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Language models are few-shot learners
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Advice taking and decision-making: An integrative literature review, and implications for the organizational sciences
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The pascal recognising textual entailment challenge
Ido Dagan, Oren Glickman, and Bernardo Magnini. 2006 · 2006
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A game-theoretic approach to generating spatial descriptions
Dave Golland, Percy Liang, and Dan Klein. 2010 · 2010
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Unbiased look at dataset bias
Antonio Torralba and Alexei A Efros. 2011 · 2011
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Effects of user similarity in social media
Ashton Anderson, Daniel P. Huttenlocher, Jon M. Kleinberg, and Jure Leskovec. 2012 · 2012
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Predicting pragmatic reasoning in language games
Michael C Frank and Noah D Goodman. 2012 · 2012
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Conll-2012 shared task: Modeling multilingual unrestricted coreference in ontonotes
Sameer Pradhan, Alessandro Moschitti, Nianwen Xue, Olga Uryupina, and Yuchen Zhang. 2012 · 2012
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Semantic parsing with combinatory categorial grammars
Yoav Artzi, Nicholas FitzGerald, and Luke S Zettlemoyer. 2013 · 2013
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What’s in a name? understanding the interplay between titles, content, and communities in social media
Himabindu Lakkaraju, Julian J. McAuley, and Jure Leskovec. 2013 · 2013
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Social influence bias: a randomized experiment
Lev Muchnik, Sinan Aral, and Sean J. Taylor. 2013 · 2013
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A large annotated corpus for learning natural language inference
Samuel R. Bowman, Gabor Angeli, Christopher Potts, and Christopher D. Manning. 2015 · 2015
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Talking to the crowd: What do people react to in online discussions?
Aaron Jaech, Victoria Zayats, Hao Fang, Mari Ostendorf, and Hannaneh Hajishirzi. 2015 · 2015
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The social impact of natural language processing
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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Question answering as an automatic evaluation metric for news article summarization
Matan Eyal, Tal Baumel, and Michael Elhadad. 2019 · 2019
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On making reading comprehension more comprehensive
Matt Gardner, Jonathan Berant, Hannaneh Hajishirzi, Alon Talmor, and Sewon Min. 2019 · 2019
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“good” isn’t good enough
Ben Green. 2019 · 2019
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Unifying human and statistical evaluation for natural language generation
Tatsunori Hashimoto, Hugh Zhang, and Percy Liang. 2019 · 2019
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Neural text summarization: A critical evaluation
Wojciech Kryscinski, Nitish Shirish Keskar, Bryan McCann, Caiming Xiong, and Richard Socher. 2019 · 2019
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Dirk Hovy and Shannon L Spruit. 2016 · 2016
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Squad: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
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Learning language games through interaction
Sida I Wang, Percy Liang, and Christopher D Manning. 2016 · 2016
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Natural language does not emerge ‘naturally’ in multi-agent dialog
Satwik Kottur, José Moura, Stefan Lee, and Dhruv Batra. 2017 · 2017
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Multi-agent cooperation and the emergence of (natural) language
Angeliki Lazaridou, Alexander Peysakhovich, and Marco Baroni. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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A semantic qa-based approach for text summarization evaluation
Ping Chen, Fei Wu, Tong Wang, and Wei Ding. 2018 · 2018
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Natural questions: a benchmark for question answering research
Tom Kwiatkowski, Jennimaria Palomaki, Olivia Redfield, Michael Collins, Ankur Parikh, Chris Alberti, Danielle Epstein, Illia Polosukhin, Matthew Kelcey, Jacob Devlin, Kenton Lee, Kristina N. Toutanova, Llion Jones, Ming-Wei Chang, Andrew Dai, Jakob Uszkoreit, Quoc Le, and Slav Petrov. 2019 · 2019
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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 · 2019
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Social iqa: Commonsense reasoning about social interactions
Maarten Sap, Hannah Rashkin, Derek Chen, Ronan Le Bras, and Yejin Choi. 2019 · 2019
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Answers unite! unsupervised metrics for reinforced summarization models
Thomas Scialom, Sylvain Lamprier, Benjamin Piwowarski, and Jacopo Staiano. 2019 · 2019
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The woman worked as a babysitter: On biases in language generation
Emily Sheng, Kai-Wei Chang, Premkumar Natarajan, and Nanyun Peng. 2019 · 2019
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Bert has a mouth, and it must speak: Bert as a markov random field language model
Alex Wang and Kyunghyun Cho. 2019 · 2019
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Hype: A benchmark for human eye perceptual evaluation of generative models
Sharon Zhou, Mitchell Gordon, Ranjay Krishna, Austin Narcomey, Li Fei-Fei, and Michael Bernstein. 2019 · 2019
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Piqa: Reasoning about physical commonsense in natural language
Yonatan Bisk, Rowan Zellers, Ronan Le Bras, Jianfeng Gao, and Yejin Choi. 2020 · 2020
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Realtoxicityprompts: Evaluating neural toxic degeneration in language models
Samuel Gehman, Suchin Gururangan, Maarten Sap, Yejin Choi, and Noah A Smith. 2020 · 2020
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Help! need advice on identifying advice
Venkata Subrahmanyan Govindarajan, Benjamin Chen, Rebecca Warholic, Katrin Erk, and Junyi Jessy Li. 2020 · 2020
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Algorithmic realism: Expanding the boundaries of algorithmic thought
Ben Green and Salomé Viljoen. 2020 · 2020
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The curious case of neural text degeneration
Ari Holtzman, Jan Buys, Li Du, Maxwell Forbes, and Yejin Choi. 2020 · 2020
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On the dangers of stochastic parrots: Can language models be too big?
Emily M Bender, Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell. 2021 · 2021
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