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Targeted syntactic evaluations of language models ask whether models show stable preferences for syntactically acceptable content over minimal-pair unacceptable inputs.
This construction needs learned
Michael P. Kaschak and Arthur M. Glenberg. 2004 · 2004
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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, et al. 2020 · 2005
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Probing for semantic evidence of composition by means of simple classification tasks
Allyson Ettinger, Ahmed Elgohary, and Philip Resnik. 2016 · 2016
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Assessing the ability of lstms to learn syntax-sensitive dependencies
Tal Linzen, Emmanuel Dupoux, and Yoav Goldberg. 2016 · 2016
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Pointer sentinel mixture models
Stephen Merity, Caiming Xiong, James Bradbury, and Richard Socher. 2016 · 2016
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Priming and language change , pages 173–90
Martin J Pickering and Simon Garrod. 2017 · 2017
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Targeted syntactic evaluation of language models
Rebecca Marvin and Tal Linzen. 2018 · 2018
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Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever. 2018 · 2018
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A neural model of adaptation in reading
Marten van Schijndel and Tal Linzen. 2018 · 2018
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Analyzing and interpreting neural networks for nlp: A report on the first blackboxnlp workshop
Afra Alishahi, Grzegorz Chrupała, and Tal Linzen. 2019 · 2019
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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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Verb argument structure alternations in word and sentence embeddings
Katharina Kann, Alex Warstadt, Adina Williams, and Samuel R. Bowman. 2019 · 2019
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Using priming to uncover the organization of syntactic representations in neural language models
Grusha Prasad, Marten van Schijndel, and Tal Linzen. 2019 · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeff Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
Cited alongside, same era.
Neural network acceptability judgments
Alex Warstadt, Amanpreet Singh, and Samuel R. Bowman. 2019 · 2019
Cited alongside, same era.
Syntactic priming depends on procedural, reward-based computations: evidence from experimental data and a computational model
Yuxue Cher Yang and Andrea Stocco. 2019 · 2019
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A systematic assessment of syntactic generalization in neural language models
Jennifer Hu, Jon Gauthier, Peng Qian, Ethan Wilcox, and Roger Levy. 2020 · 2020
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Compositionality decomposed: How do neural networks generalise?
Dieuwke Hupkes, Verna Dankers, Mathijs Mul, and Elia Bruni. 2020 · 2020
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Are natural language inference models IMPPRESsive? Learning IMPlicature and PRESupposition
Making pre-trained language models better few-shot learners
Tianyu Gao, Adam Fisch, and Danqi Chen. 2021 · 2021
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It’s not just size that matters: Small language models are also few-shot learners
Timo Schick and Hinrich Schütze. 2021b · 2021
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Sequence length is a domain: Length-based overfitting in transformer models
Dusan Varis and Ondřej Bojar. 2021 · 2021
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Can language models learn from explanations in context?
Andrew K Lampinen, Ishita Dasgupta, Stephanie CY Chan, Kory Matthewson, Michael Henry Tessler, Antonia Creswell, James L McClelland, Jane X Wang, and Felix Hill. 2022 · 2022
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Andrew Kyle Lampinen. 2022 · 2022
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Negated and misprimed probes for pretrained language models: Birds can talk, but cannot fly
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Exploring BERT’s sensitivity to lexical cues using tests from semantic priming
Kanishka Misra, Allyson Ettinger, and Julia Rayz. 2020 · 2020
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Cross-linguistic syntactic evaluation of word prediction models
Aaron Mueller, Garrett Nicolai, Panayiota Petrou-Zeniou, Natalia Talmina, and Tal Linzen. 2020 · 2020
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The EOS decision and length extrapolation
Benjamin Newman, John Hewitt, Percy Liang, and Christopher D. Manning. 2020 · 2020
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BLiMP: A benchmark of linguistic minimal pairs for English
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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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Fantastically ordered prompts and where to find them: Overcoming few-shot prompt order sensitivity
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minicons: Enabling flexible behavioral and representational analyses of transformer language models
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Structural persistence in language models: Priming as a window into abstract language representations
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The curious case of absolute position embeddings
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Do prompt-based models really understand the meaning of their prompts?
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Chain of thought prompting elicits reasoning in large language models
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Opt: Open pre-trained transformer language models
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