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Cognitive Network Science Reveals Bias in GPT-3, GPT-3.5 Turbo, and GPT-4 Mirroring Math Anxiety in High-School Students.

, , , , and . Big Data Cogn. Comput., 7 (3): 124 (2023)

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Cognitive Network Science Reveals Bias in GPT-3, GPT-3.5 Turbo, and GPT-4 Mirroring Math Anxiety in High-School Students., , , , and . Big Data Cogn. Comput., 7 (3): 124 (2023)A Probabilistic Tree Model to Analyze Fuzzy Rating Data., and . IPMU (2), volume 1602 of Communications in Computer and Information Science, page 457-468. Springer, (2022)Multi-fidelity error estimation accelerates greedy model reduction of complex dynamical systems., , , and . CoRR, (2023)Cognitive network science reveals bias in GPT-3, ChatGPT, and GPT-4 mirroring math anxiety in high-school students., , , , and . CoRR, (2023)Dynamic Fuzzy Rating Tracker (DYFRAT): a novel methodology for modeling real-time dynamic cognitive processes in rating scales., and . Appl. Soft Comput., (2014)sgr: A Package for Simulating Conditional Fake Ordinal Data., and . R J., 6 (1): 164 (2014)Cognitive Network Science Unveils Affective Bias in GPT Models Mirroring Math Anxiety in High-School Students., , , , and . HHAI, volume 386 of Frontiers in Artificial Intelligence and Applications, page 451-453. IOS Press, (2024)Conjunctive prediction of an ordinal criterion variable on the basis of binary predictors., and . Discret. Appl. Math., 147 (1): 91-100 (2005)Model Order Reduction for Delayed PEEC Models With Guaranteed Accuracy and Observed Stability., , , , and . IEEE Trans. Circuits Syst. I Regul. Pap., 69 (10): 4177-4190 (2022)Non-convex fuzzy data and fuzzy statistics: a first descriptive approach to data analysis., , and . Soft Comput., 18 (8): 1575-1588 (2014)