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Large Language Models are Not Models of Natural Language: They are Corpus Models

IEEE Access, 2022
Natural Language Processing (NLP) has become one of the leading application areas in the current Artificial Intelligence boom. Transfer learning has enabled large deep learning neural networks trained on the language modeling task to vastly improve ...
Csaba Veres
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Knowledge Engineering Using Large Language Models [PDF]

Transactions on Graph Data and Knowledge, 2023
Knowledge engineering is a discipline that focuses on the creation and maintenance of processes that generate and apply knowledge. Traditionally, knowledge engineering approaches have focused on knowledge expressed in formal languages.
Allen, Bradley P., Stork, Lise, Groth, Paul   +2 more
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Can large language models write reflectively

Computers and Education: Artificial Intelligence, 2023
Generative Large Language Models (LLMs) demonstrate impressive results in different writing tasks and have already attracted much attention from researchers and practitioners. However, there is limited research to investigate the capability of generative
Yuheng Li, Lele Sha, Lixiang Yan, Jionghao Lin, Mladen Raković, Kirsten Galbraith, Kayley Lyons, Dragan Gašević, Guanliang Chen   +8 more
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Large Language Models and Logical Reasoning

Encyclopedia, 2023
In deep learning, large language models are typically trained on data from a corpus as representative of current knowledge. However, natural language is not an ideal form for the reliable communication of concepts.
Robert Friedman
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Emotional intelligence of Large Language Models

Journal of Pacific Rim Psychology, 2023
Large Language Models (LLMs) have demonstrated remarkable abilities across numerous disciplines, primarily assessed through tasks in language generation, knowledge utilization, and complex reasoning.
Xuena Wang, Xueting Li, Zi Yin, Yue Wu, Jia Liu   +4 more
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Large language models and political science

Frontiers in Political Science, 2023
Large Language Models (LLMs) are a type of artificial intelligence that uses information from very large datasets to model the use of language and generate content.
Mitchell Linegar, Rafal Kocielnik, R. Michael Alvarez, R. Michael Alvarez   +3 more
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Enhancing Agriculture QA Models Using Large Language Models [PDF]

BIO Web of Conferences
Agriculture is a complex process that requires a great deal of knowledge and experience. Yet, the complexity and often chaotic nature of web data presents a considerable challenge in obtaining suitable results.
He Xiaoyan
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Large-scale evaluation of multimodal large language models for pneumothorax detection

Diagnostic and Interventional Radiology
PURPOSE: Pneumothorax requires rapid recognition and accurate interpretation of chest X-rays (CXRs), particularly in acute settings where delays can have serious consequences.
Hamza Eren Güzel, Cemre Özenbaş, Ali Murat Koç   +2 more
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Consistent Responses to Paraphrased Questions as Evidence Against Hallucination: A Study on Hallucinations in LLMs [PDF]

International Journal of Web Research
The increasing adoption of large language models (LLMs) has intensified concerns about hallucinations—outputs that are syntactically fluent but factually incorrect.
Tara Zare, Mehrnoush Shamsfard
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State of the Art Survey of Automatic Question Generation Based on Large Language Models [PDF]

International Journal of Telecommunications
Automatic Question Generation (AQG) has emerged as one of the core research problems in educational technology owing to its potential to automate assessments and facilitate the development of adaptive learning platforms.
OLa Abdullah, Mohammed Nasef, Ahmed Emam
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