AIMC Topic: Language

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A simulated dataset for proactive robot task inference from streaming natural language dialogues.

Scientific data
This paper introduces a dataset designed to support research on proactive robots that infer human needs from natural language conversations. Unlike traditional human-robot interaction datasets focused on explicit commands, this dataset captures impli...

Current Landscape and Future Directions Regarding Generative Large Language Models in Stroke Care: Scoping Review.

JMIR medical informatics
BACKGROUND: Stroke has a major impact on global health, causing long-term disability and straining health care resources. Generative large language models (gLLMs) have emerged as promising tools to help address these challenges, but their application...

Classifying Patient Complaints Using Artificial Intelligence-Powered Large Language Models: Cross-Sectional Study.

Journal of medical Internet research
BACKGROUND: Patient complaints provide valuable insights into the performance of health care systems, highlighting potential risks not apparent to staff. Patient complaints can drive systemic changes that enhance patient safety. However, manual categ...

Transfer learning driven fake news detection and classification using large language models.

Scientific reports
Today, the problem of using social media to spread false information is not only widespread but also quite serious. The extensive dissemination of fake news, regardless of whether it is produced by human beings or computer programs, has a negative im...

Zero-shot performance analysis of large language models in sumrate maximization.

PloS one
Large language models have revolutionized the field of natural language processing and are now becoming a one-stop solution to various tasks. In the field of Networking, LLMs can also play a major role when it comes to resource optimization and shari...

Using a large language model (ChatGPT) to assess risk of bias in randomized controlled trials of medical interventions: protocol for a pilot study of interrater agreement with human reviewers.

BMC medical research methodology
BACKGROUND: Risk of bias (RoB) assessment is an essential part of systematic reviews that requires reading and understanding each eligible trial and RoB tools. RoB assessment is subject to human error and is time-consuming. Machine learning-based too...

A qualitative study on ethical issues related to the use of AI-driven technologies in foreign language learning.

Scientific reports
The current situation in the use of AI-driven technologies in education has seen an unprecedented rise, however, the impact of these technologies from the perspective of ethical issues is largely unknown. The aim of the research is to provide a clear...

Impact of large language models and vision deep learning models in predicting neoadjuvant rectal score for rectal cancer treated with neoadjuvant chemoradiation.

BMC medical imaging
This study aims to explore Deep Learning methods, namely Large Language Models (LLMs) and Computer Vision models to accurately predict neoadjuvant rectal (NAR) score for locally advanced rectal cancer (LARC) treated with neoadjuvant chemoradiation (N...

A dataset for recognition of Arabic accents from spoken L2 English speech (ArL2Eng).

Scientific data
This paper introduces the ArL2Eng dataset, a speech corpus of L2 English produced by native speakers of Arabic, and highlights its potential in supporting research into automated language assessment. ArL2Eng comprises audio sequences from speakers of...

Large Language Model Symptom Identification From Clinical Text: Multicenter Study.

Journal of medical Internet research
BACKGROUND: Recognizing patient symptoms is fundamental to medicine, research, and public health. However, symptoms are often underreported in coded formats even though they are routinely documented in physician notes. Large language models (LLMs), n...