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The deployment of large language models (LLMs) in diverse applications requires a thorough understanding of their decision-making strategies and behavioral patterns.
Computing machinery and intelligence
Alan M. Turing. 1950 · 1950
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Constant elasticity of substitution production functions
Daniel McFadden. 1963 · 1963
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Sparks of artificial general intelligence: Early experiments with gpt-4
Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, Johannes Gehrke, Eric Horvitz, Ece Kamar, Peter Lee, Yin Tat Lee, Yuanzhi Li, Scott Lundberg, et al · 2023
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The emergence of economic rationality of GPT
Yiting Chen, Tracy Xiao Liu, You Shan, and Songfa Zhong. 2023 · 2023
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Gpts are gpts: An early look at the labor market impact potential of large language models
Tyna Eloundou, Sam Manning, Pamela Mishkin, and Daniel Rock. 2023 · 2023
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Ideas are dimes a dozen: Large language models for idea generation in innovation
Karan Girotra, Lennart Meincke, Christian Terwiesch, and Karl T Ulrich. 2023 · 2023
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Benefits, limits, and risks of GPT-4 as an AI chatbot for medicine
Peter Lee, Sebastien Bubeck, and Joseph Petro. 2023 · 2023
Cited alongside, same era.
How We Learned to Stop Worrying and Love AI: Analyzing the Rapid Evolution of Generative Pre-Trained Transformer (GPT) and its Impacts on Law, Business, and Society
Scott Shackelford, Lawrence J Trautman, and W Gregory Voss. 2023 · 2023
Later among the works it cites.
A Turing test of whether AI chatbots are behaviorally similar to humans
Qiaozhu Mei, Yutong Xie, Walter Yuan, and Matthew O Jackson. 2024 · 2024
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Can Large Language Model Agents Simulate Human Trust Behaviors?
Chengxing Xie, Canyu Chen, Feiran Jia, Ziyu Ye, Kai Shu, Adel Bibi, Ziniu Hu, Philip Torr, Bernard Ghanem, and Guohao Li. 2024 · 2024
Closest in time.
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