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Random Number Generation Tasks (RNGTs) are used in psychology for examining how humans generate sequences devoid of predictable patterns.
Language models are few-shot learners
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Response preferences: A review of some relevant literature
GS Tune. 1964 · 1964
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Monitoring attention deployment by random number generation: An index to measure subjective randomness
Frederick J Evans. 1978 · 1978
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Testing random number generators
Pierre L’Ecuyer. 1992 · 1992
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Random generation: Analysis of the responses
Norman Ginsburg and P Karpiuk. 1994 · 1994
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Working memory and supervisory control after severe closed-head injury. A study of dual task performance and random generation
Philippe Azouvi, Corinne Jokic, Martial Van Der Linden, Nicole Marlier, and Bernard Bussel. 1996 · 1996
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Exploring the central executive
Alan Baddeley. 1996 · 1996
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Random number generation in dementia of the Alzheimer type: A test of frontal executive functions
Peter Brugger, Andreas U Monsch, David P Salmon, and Nelson Butters. 1996 · 1996
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Random generation and the executive control of working memory
Alan Baddeley. 1998 · 1998
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The left dorsolateral prefrontal cortex and random generation of responses: studies with transcranial magnetic stimulation
Marjan Jahanshahi and Georg Dirnberger. 1998 · 1998
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The effects of transcranial magnetic stimulation over the dorsolateral prefrontal cortex on suppression of habitual counting during random number generation
Marjan Jahanshahi, Paolo Profice, Richard G Brown, Mike C Ridding, Georg Dirnberger, and John C Rothwell. 1998 · 1998
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Analyzing human random generation behavior: A review of methods used and a computer program for describing performance
John N Towse and Derek Neil. 1998 · 1998
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Age-related differences in random generation
Martial Van der Linden, Annick Beerten, and Mauro Pesenti. 1998 · 1998
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Good parameters and implementations for combined multiple recursive random number generators
Pierre L’ecuyer. 1999 · 1999
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The role of the dorsolateral prefrontal cortex in random number generation: a study with positron emission tomography
Marjan Jahanshahi, Georg Dirnberger, Rebecca Fuller, and Chris D Frith. 2000 · 2000
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The unity and diversity of executive functions and their contributions to complex “frontal lobe” tasks: A latent variable analysis
Akira Miyake, Naomi P Friedman, Michael J Emerson, Alexander H Witzki, Amy Howerter, and Tor D Wager. 2000 · 2000
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Humans can consciously generate random number sequences: A possible test for artificial intelligence
Navindra Persaud. 2005 · 2005
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Random number generation as an index of controlled processing
Marjan Jahanshahi, T Saleem, Aileen K Ho, Georg Dirnberger, and R Fuller. 2006 · 2006
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Recommendation for random number generation using deterministic random bit generators (revised)
Elaine B Barker, John Michael Kelsey, et al · 2007
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The random number generation task: Psychometric properties and normative data of an executive function task in a mixed sample
Maarten Peters, Timo Giesbrecht, Marko Jelicic, and Harald Merckelbach. 2007 · 2007
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Random number generation and creativity
William Bains. 2008 · 2008
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AI and the transformation of social science research
Igor Grossmann, Matthew Feinberg, Dawn C Parker, Nicholas A Christakis, Philip E Tetlock, and William A Cunningham. 2023 · 2023
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Human-like intuitive behavior and reasoning biases emerged in large language models but disappeared in ChatGPT
Thilo Hagendorff, Sarah Fabi, and Michal Kosinski. 2023 · 2023
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Albert Q Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, et al · 2023
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Yuan Li, Yixuan Zhang, and Lichao Sun. 2023 · 2023
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Summary of chatgpt-related research and perspective towards the future of large language models
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Małgorzata Figurska, Maciej Stańczyk, and Kamil Kulesza. 2008 · 2008
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Random number generation: Types and techniques
David F DiCarlo. 2012 · 2012
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Intrinsic randomness as a measure of quantum coherence
Xiao Yuan, Hongyi Zhou, Zhu Cao, and Xiongfeng Ma. 2015 · 2015
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Building machines that learn and think like people
Brenden M Lake, Tomer D Ullman, Joshua B Tenenbaum, and Samuel J Gershman. 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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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
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Yiheng Liu, Tianle Han, Siyuan Ma, Jiayue Zhang, Yuanyuan Yang, Jiaming Tian, Hao He, Antong Li, Mengshen He, Zhengliang Liu, et al · 2023
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Large language models predict human sensory judgments across six modalities
Raja Marjieh, Ilia Sucholutsky, Pol van Rijn, Nori Jacoby, and Thomas L Griffiths. 2023 · 2023
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Human-like problem-solving abilities in large language models using ChatGPT
Graziella Orrù, Andrea Piarulli, Ciro Conversano, and Angelo Gemignani. 2023 · 2023
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Language models and psychological sciences
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Gemini: a family of highly capable multimodal models
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Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al · 2023
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A majority of Americans have heard of ChatGPT, but few have tried it themselves
Emily A Vogels. 2023 · 2023
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Emergent analogical reasoning in large language models
Taylor Webb, Keith J Holyoak, and Hongjing Lu. 2023 · 2023
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A brief overview of ChatGPT: The history, status quo and potential future development
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Exploring the Frontiers of LLMs in Psychological Applications: A Comprehensive Review
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Randomness
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