dc.contributor.author | Dhingra, S | |
dc.contributor.author | Singh, M | |
dc.contributor.author | Vaisakh, SB | |
dc.contributor.author | Malviya, N | |
dc.contributor.author | Gill, SS | |
dc.date.accessioned | 2023-09-07T14:50:19Z | |
dc.date.available | 2023-08-28 | |
dc.date.available | 2023-09-07T14:50:19Z | |
dc.date.issued | 2023-09-06 | |
dc.identifier.issn | 2772-4859 | |
dc.identifier.other | 100139 | |
dc.identifier.uri | https://qmro.qmul.ac.uk/xmlui/handle/123456789/90567 | |
dc.description.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. | en_US |
dc.format.extent | 100139 - 100139 | |
dc.publisher | Elsevier | en_US |
dc.relation.ispartof | BenchCouncil Transactions on Benchmarks Standards and Evaluations | |
dc.rights | Attribution 3.0 United States | * |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/us/ | * |
dc.title | Mind meets machine: Unravelling GPT-4’s cognitive psychology | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1016/j.tbench.2023.100139 | |
pubs.author-url | https://arxiv.org/abs/2303.11436 | en_US |
pubs.issue | 3 | en_US |
pubs.notes | Not known | en_US |
pubs.publication-status | Published | en_US |
pubs.publisher-url | https://www.sciencedirect.com/science/article/pii/S277248592300056X | en_US |
pubs.volume | 3 | en_US |
dcterms.dateAccepted | 2023-08-28 | |