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Neural network models of language have long been used as a tool for developing hypotheses about conceptual representation in the mind and brain.
Language models are few-shot learners
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Language models are few-shot learners
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Semantic cognition: A parallel distributed processing approach
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Semantic feature production norms for a large set of living and nonliving things
Ken McRae, George S Cree, Mark S Seidenberg, and Chris McNorgan. 2005 · 2005
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Exemplar by feature applicability matrices and other dutch normative data for semantic concepts
Simon De Deyne, Steven Verheyen, Eef Ameel, Wolf Vanpaemel, Matthew J Dry, Wouter Voorspoels, and Gert Storms. 2008 · 2008
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Adaptively learning the crowd kernel
Omer Tamuz, Ce Liu, Serge Belongie, Ohad Shamir, and Adam Tauman Kalai. 2011 · 2011
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The centre for speech, language and the brain (cslb) concept property norms
Barry J Devereux, Lorraine K Tyler, Jeroen Geertzen, and Billi Randall. 2014 · 2014
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Next: A system for real-world development, evaluation, and application of active learning
Kevin G Jamieson, Lalit Jain, Chris Fernandez, Nicholas J Glattard, and Robert D Nowak. 2015 · 2015
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Enriching word vectors with subword information
Piotr Bojanowski, Edouard Grave, Armand Joulin, and Tomas Mikolov. 2017 · 2017
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Things-data: A multimodal collection of large-scale datasets for investigating object representations in brain and behavior
Martin N Hebart, Oliver Contier, Lina Teichmann, Adam Rockter, Charles Y Zheng, Alexis Kidder, Anna Corriveau, Maryam Vaziri-Pashkam, and Chris I Baker. 2022 · 2022
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Training compute-optimal large language models
Jordan Hoffmann, Sebastian Borgeaud, Arthur Mensch, Elena Buchatskaya, Trevor Cai, Eliza Rutherford, Diego de Las Casas, Lisa Anne Hendricks, Johannes Welbl, Aidan Clark, et al. 2022 · 2022
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Training language models to follow instructions with human feedback
Long Ouyang, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll L Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al. 2022 · 2022
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Self-consistency improves chain of thought reasoning in language models
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc Le, Ed Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou. 2022 · 2022
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How decisions and the desire for coherency shape subjective preferences over time
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Cultural influences on word meanings revealed through large-scale semantic alignment
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Reverse-engineering the cortical architecture for controlled semantic cognition
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Finetuned language models are zero-shot learners
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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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Using large language models in psychology
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