Results 21 to 30 of about 63,129 (302)
Large Language Models (LLMs) and Causality Extraction from Text
This tutorial explores the application of Large Language Models (LLMs), such as BERT, LLAMA, and GPT-3.5/4, to the extraction of causality from text documents, including identifying causes, effects, and actions in diverse texts, such as business ...
Wlodek Zadrozny
doaj +1 more source
Automated Assessment of Students' Code Comprehension using LLMs
Assessing student's answers and in particular natural language answers is a crucial challenge in the field of education. Advances in machine learning, including transformer-based models such as Large Language Models(LLMs), have led to significant ...
Banjade, Rabin +3 more
core
Objective A patient‐centered approach for chronic disease management, including systemic lupus erythematosus (SLE), aligns treatment with patients’ values and preferences, leading to improved outcomes. This paper summarizes how patient experiences, perspectives, and priorities informed the American College of Rheumatology (ACR) 2024 Lupus Nephritis (LN)
Shivani Garg +20 more
wiley +1 more source
Benchmarking Large Language Models in Retrieval-Augmented Generation
Retrieval-Augmented Generation (RAG) is a promising approach for mitigating the hallucination of large language models (LLMs). However, existing research lacks rigorous evaluation of the impact of retrieval-augmented generation on different large ...
Chen, Jiawei +3 more
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What Do Large Language Models Know About Materials?
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer +2 more
wiley +1 more source
Industrial applications of large language models
Large language models (LLMs) are artificial intelligence (AI) based computational models designed to understand and generate human like text. With billions of training parameters, LLMs excel in identifying intricate language patterns, enabling remarkable
Mubashar Raza +4 more
doaj +1 more source
From Large Language Models to Large Multimodal Models: A Literature Review
With the deepening of research on Large Language Models (LLMs), significant progress has been made in recent years on the development of Large Multimodal Models (LMMs), which are gradually moving toward Artificial General Intelligence. This paper aims to
Dawei Huang +3 more
doaj +1 more source
Visual Literacy and New Technologies [PDF]
This body of research addresses the connection between arts, identity and new technology, and investigates the impact of images on adolescent identities, the relationship between online modes of communication and cyber-bullying, the increasing ...
Bamford, Anne
core
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source
The great Transformer: Examining the role of large language models in the political economy of AI
In recent years, AI research has become more and more computationally demanding. In natural language processing (NLP), this tendency is reflected in the emergence of large language models (LLMs) like GPT-3.
Dieuwertje Luitse, Wiebke Denkena
doaj +1 more source

