Results 1 to 10 of about 34,912 (272)
Using cognitive psychology to understand GPT-3. [PDF]
Proc Natl Acad Sci U S A, 2023 We study GPT-3, a recent large language model, using tools from cognitive psychology. More specifically, we assess GPT-3's decision-making, information search, deliberation, and causal reasoning abilities on a battery of canonical experiments from the literature.
Binz M, Schulz E.
europepmc +8 more sources
AI model GPT-3 (dis)informs us better than humans. [PDF]
Sci Adv, 2023 Artificial intelligence (AI) is changing the way we create and evaluate information, and this is happening during an infodemic, which has been having marked effects on global health. Here, we evaluate whether recruited individuals can distinguish disinformation from accurate information, structured in the form of tweets, and determine whether a tweet ...
Spitale G, Biller-Andorno N, Germani F.
europepmc +6 more sources
Overlap in meaning is a stronger predictor of semantic activation in GPT-3 than in humans [PDF]
Scientific Reports, 2023 Modern large language models generate texts that are virtually indistinguishable from those written by humans and achieve near-human performance in comprehension and reasoning tests.
Jan Digutsch, Michal Kosinski
doaj +2 more sources
Feature-based detection of automated language models: tackling GPT-2, GPT-3 and Grover [PDF]
PeerJ Computer Science, 2021 The recent improvements of language models have drawn much attention to potential cases of use and abuse of automatically generated text. Great effort is put into the development of methods to detect machine generations among human-written text in order ...
Leon Fröhling, Arkaitz Zubiaga
doaj +3 more sources
Comparative performance of GPT-4, GPT-o3, GPT-5, Gemini-3-Flash, and DeepSeek-R1 in ophthalmology question answering [PDF]
Frontiers in Cell and Developmental BiologyBackgroundThe application of large language models (LLMs) in medicine is rapidly advancing, showing particular promise in specialized fields like ophthalmology.
Ping Zhang +6 more
doaj +2 more sources
Will Machines Replace Us? Machine-Authored Texts and the Future of Scholarship
Law, Technology and Humans, 2021 We present here the first machine-generated law review article. Our self-interest motivates us to believe that knowledge workers who write complex articles drawing upon years of research and effort are safe from AI developments.
Benjamin Alarie +2 more
doaj +1 more source
Law, Technology and Humans, 2021 This brief editorial focuses on the contribution in this volume titled ‘Machines Will Never Replace Humans!’ compiled by GPT-3. The brief text is provocative.
Kieran Tranter
doaj +1 more source
Design of text generator application with OpenAI GPT-3
Journal of Electrical Engineering and Computer, 2023 The increasing need for text content creation today challenges the development of systems that can alleviate the need for text creation. Currently, text generation is done manually and has various shortcomings, especially in terms of time constraints ...
Kaira Milani Fitria
doaj +1 more source
Law, Technology and Humans, 2023 In 2021, an artificial intelligence system wrote a law article. The results were far from perfect but begged the question of whether a human author will still be able to compete against artificial intelligence.
Jerome De Cooman
doaj +1 more source
Effectiveness of Zero-shot Models in Automatic Arabic Poem Generation
Jordanian Journal of Computers and Information Technology, 2023 Text generation is one of the most challenging applications in artificial intelligence and natural language processing. In recent years, text generation has gotten much attention thanks to the advances in deep learning and language modeling approaches ...
Mohamed El Ghaly Beheitt +1 more
doaj +1 more source