Fetching the paper…
Reading the bibliography…
The Winograd Schema (WS) has been proposed as a test for measuring commonsense capabilities of models.
Assessing bert’s syntactic abilities
Yoav Goldberg. 2019 · 1901
Earlier work this paper cites.
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.
A knowledge hunting framework for common sense reasoning
Ali Emami, Noelia De La Cruz, Adam Trischler, Kaheer Suleman, and Jackie Chi Kit Cheung. 2018 · 1958
Earlier work this paper cites.
Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
Earlier work this paper cites.
A review of winograd schema challenge datasets and approaches
Vid Kocijan, Thomas Lukasiewicz, Ernest Davis, Gary Marcus, and Leora Morgenstern. 2020 · 2004
Earlier work this paper cites.
Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
Earlier work this paper cites.
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, et al. 2020 · 2005
Earlier work this paper cites.
The pascal recognising textual entailment challenge
Ido Dagan, Oren Glickman, and Bernardo Magnini. 2005 · 2005
Earlier work this paper cites.
The winograd schema challenge
Hector Levesque, Ernest Davis, and Leora Morgenstern. 2012 · 2012
Earlier work this paper cites.
Resolving complex cases of definite pronouns: the winograd schema challenge
Altaf Rahman and Vincent Ng. 2012 · 2012
Earlier work this paper cites.
Recognizing Textual Entailment: Models and Applications
Ido Dagan, Dan Roth, Mark Sammons, and Fabio Massimo Zanzoto. 2013 · 2013
Earlier work this paper cites.
Acquiring comparative commonsense knowledge from the web
Niket Tandon, Gerard De Melo, and Gerhard Weikum. 2014 · 2014
Earlier work this paper cites.
The winograd schema challenge and reasoning about correlation
Daniel Bailey, Amelia J Harrison, Yuliya Lierler, Vladimir Lifschitz, and Julian Michael. 2015 · 2015
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba. 2015 · 2015
Earlier work this paper cites.
The theory of correlation formulas and their application to discourse coherence
Julian Michael. 2015 · 2015
Earlier work this paper cites.
Never-ending learning
T. Mitchell, W. Cohen, E. Hruschka, P. Talukdar, J. Betteridge, A. Carlson, B. Dalvi, M. Gardner, B. Kisiel, J. Krishnamurthy, N. Lao, K. Mazaitis, T. Mohamed, N. Nakashole, E. Platanios, A. Ritter, M. Samadi, B. Settles, R. Wang, D. Wijaya, A. Gupta, X. Chen, A. Saparov, M. Greaves, and J. Welling. 2015 · 2015
Earlier work this paper cites.
Solving hard coreference problems
Haoruo Peng, Daniel Khashabi, and Dan Roth. 2015 · 2015
Earlier work this paper cites.
Towards addressing the winograd schema challenge-building and using a semantic parser and a knowledge hunting module
Arpit Sharma, Nguyen Ha Vo, Somak Aditya, and Chitta Baral. 2015 · 2015
Earlier work this paper cites.
Yukun Zhu, Ryan Kiros, Rich Zemel, Ruslan Salakhutdinov, Raquel Urtasun, Antonio Torralba, and Sanja Fidler. 2015 · 2015
Earlier work this paper cites.
Are elephants bigger than butterflies? reasoning about sizes of objects
Hessam Bagherinezhad, Hannaneh Hajishirzi, Yejin Choi, and Ali Farhadi. 2016 · 2016
Earlier work this paper cites.
Tackling the winograd schema challenge through machine logical inferences
Nicos Isaak and Loizos Michael. 2016 · 2016
Earlier work this paper cites.
Verb physics: Relative physical knowledge of actions and objects
Maxwell Forbes and Yejin Choi. 2017 · 2017
Earlier work this paper cites.
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
Cited alongside, same era.
A marker passing approach to winograd schemas
Johannes Fähndrich, Sabine Weber, and Hannes Kanthak. 2018 · 2018
Cited alongside, same era.
Breaking NLI systems with sentences that require simple lexical inferences
Max Glockner, Vered Shwartz, and Yoav Goldberg. 2018 · 2018
Cited alongside, same era.
Annotation artifacts in natural language inference data
Suchin Gururangan, Swabha Swayamdipta, Omer Levy, Roy Schwartz, Samuel Bowman, and Noah A Smith. 2018 · 2018
Cited alongside, same era.
How much reading does reading comprehension require? a critical investigation of popular benchmarks
Divyansh Kaushik and Zachary C Lipton. 2018 · 2018
Cited alongside, same era.
Addressing the winograd schema challenge as a sequence ranking task
Cycle-consistency for robust visual question answering
Meet Shah, Xinlei Chen, Marcus Rohrbach, and Devi Parikh. 2019 · 2019
Later among the works it cites.
Using answer set programming for commonsense reasoning in the winograd schema challenge
Arpit Sharma. 2019 · 2019
Later among the works it cites.
How reasonable are common-sense reasoning tasks: A case-study on the winograd schema challenge and swag
Paul Trichelair, Ali Emami, Adam Trischler, Kaheer Suleman, and Jackie Chi Kit Cheung. 2019 · 2019
Later among the works it cites.
Sp-10k: A large-scale evaluation set for selectional preference acquisition
Hongming Zhang, Hantian Ding, and Yangqiu Song. 2019 · 2019
Later among the works it cites.
“going on a vacation” takes longer than “going for a walk”: A study of temporal commonsense understanding
Ben Zhou, Daniel Khashabi, Qiang Ning, and Dan Roth. 2019 · 2019
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Juri Opitz and Anette Frank. 2018 · 2018
Cited alongside, same era.
Hypothesis only baselines in natural language inference
Adam Poliak, Jason Naradowsky, Aparajita Haldar, Rachel Rudinger, and Benjamin Van Durme. 2018 · 2018
Cited alongside, same era.
Event2mind: Commonsense inference on events, intents, and reactions
Hannah Rashkin, Maarten Sap, Emily Allaway, Noah A Smith, and Yejin Choi. 2018 · 2018
Cited alongside, same era.
A simple method for commonsense reasoning
Trieu H Trinh and Quoc V Le. 2018 · 2018
Cited alongside, same era.
Performance impact caused by hidden bias of training data for recognizing textual entailment
Masatoshi Tsuchiya. 2018 · 2018
Cited alongside, same era.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
How large are lions? inducing distributions over quantitative attributes
Yanai Elazar, Abhijit Mahabal, Deepak Ramachandran, Tania Bedrax-Weiss, and Dan Roth. 2019 · 2019
Cited alongside, same era.
The sensitivity of language models and humans to Winograd schema perturbations
Mostafa Abdou, Vinit Ravishankar, Maria Barrett, Yonatan Belinkov, Desmond Elliott, and Anders Søgaard. 2020 · 2020
Later among the works it cites.
Piqa: Reasoning about physical commonsense in natural language
Yonatan Bisk, Rowan Zellers, Ronan LeBras, Jianfeng Gao, and Yejin Choi. 2020 · 2020
Later among the works it cites.
An analysis of dataset overlap on winograd-style tasks
Ali Emami, Kaheer Suleman, Adam Trischler, and Jackie Chi Kit Cheung. 2020 · 2020
Later among the works it cites.
What bert is not: Lessons from a new suite of psycholinguistic diagnostics for language models
Allyson Ettinger. 2020 · 2020
Later among the works it cites.
Evaluating models’ local decision boundaries via contrast sets
Matt Gardner, Yoav Artzi, Victoria Basmov, Jonathan Berant, Ben Bogin, Sihao Chen, Pradeep Dasigi, Dheeru Dua, Yanai Elazar, Ananth Gottumukkala, Nitish Gupta, Hannaneh Hajishirzi, Gabriel Ilharco, Daniel Khashabi, Kevin Lin, Jiangming Liu, Nelson F. Liu, Phoebe Mulcaire, Qiang Ning, Sameer Singh, Noah A. Smith, Sanjay Subramanian, Reut Tsarfaty, Eric Wallace, Ally Zhang, and Ben Zhou. 2020 · 2020
Later among the works it cites.
Contrastive self-supervised learning for commonsense reasoning
Tassilo Klein and Moin Nabi. 2020 · 2020
Later among the works it cites.
Precise task formalization matters in winograd schema evaluations
Haokun Liu, William Huang, Dhara Mungra, and Samuel Bowman. 2020 · 2020
Later among the works it cites.
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. 2020 · 2020
Later among the works it cites.
Winogrande: An adversarial winograd schema challenge at scale
Keisuke Sakaguchi, Ronan Le Bras, Chandra Bhagavatula, and Yejin Choi. 2020 · 2020
Later among the works it cites.
olmpics-on what language model pre-training captures
Alon Talmor, Yanai Elazar, Yoav Goldberg, and Jonathan Berant. 2020 · 2020
Later among the works it cites.
An empirical study on robustness to spurious correlations using pre-trained language models
Lifu Tu, Garima Lalwani, Spandana Gella, and He He. 2020 · 2020
Later among the works it cites.
Blimp: The benchmark of linguistic minimal pairs for english
Alex Warstadt, Alicia Parrish, Haokun Liu, Anhad Mohananey, Wei Peng, Sheng-Fu Wang, and Samuel R Bowman. 2020 · 2020
Later among the works it cites.
Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi 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 M. Rush. 2020 · 2020
Later among the works it cites.
ASER: A large-scale eventuality knowledge graph
Hongming Zhang, Xin Liu, Haojie Pan, Yangqiu Song, and Cane Wing-Ki Leung. 2020a · 2020
Later among the works it cites.
Evaluating commonsense in pre-trained language models
Xuhui Zhou, Yue Zhang, Leyang Cui, and Dandan Huang. 2020 · 2020
Later among the works it cites.
Measuring and Improving Consistency in Pretrained Language Models
Yanai Elazar, Nora Kassner, Shauli Ravfogel, Abhilasha Ravichander, Eduard Hovy, Hinrich Schütze, and Yoav Goldberg. 2021 · 2021
Closest in time.