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- Title
Mind meets machine: Unravelling GPT-4's cognitive psychology.
- Authors
Dhingra, Sifatkaur; Singh, Manmeet; Vaisakh S. B.; Malviya, Neetiraj; Gill, Sukhpal Singh
- Abstract
Cognitive psychology delves on understanding perception, attention, memory, language, problem-solving, decision-making, and reasoning. Large Language Models (LLMs) are emerging as potent tools increasingly capable of performing human-level tasks. The recent development in the form of Generative Pre-trained Transformer 4 (GPT-4) and its demonstrated success in tasks complex to humans exam and complex problems has led to an increased confidence in the LLMs to become perfect instruments of intelligence. Although GPT-4 report has shown performance on some cognitive psychology tasks, a comprehensive assessment of GPT-4, via the existing well-established datasets is required. In this study, we focus on the evaluation of GPT-4's performance on a set of cognitive psychology datasets such as CommonsenseQA, SuperGLUE, MATH and HANS. In doing so, we understand how GPT-4 processes and integrates cognitive psychology with contextual information, providing insight into the underlying cognitive processes that enable its ability to generate the responses. We show that GPT-4 exhibits a high level of accuracy in cognitive psychology tasks relative to the prior state-of-the-art models. Our results strengthen the already available assessments and confidence on GPT-4's cognitive psychology abilities. It has significant potential to revolutionise the field of Artificial Intelligence (AI), by enabling machines to bridge the gap between human and machine reasoning.
- Subjects
MACHINE learning; COGNITIVE psychology; DECISION making; ACCURACY; ARTIFICIAL intelligence
- Publication
BenchCouncil Transactions on Benchmarks, Standards & Evaluations, 2023, Vol 3, Issue 3, p1
- ISSN
2772-4859
- Publication type
Article
- DOI
10.1016/j.tbench.2023.100139