Results 61 to 70 of about 63,129 (302)

Enhancing Knowledge Tracing with Large Language Models (LLMs)

In intelligent tutoring systems (ITS), knowledge tracing (KT) is a fundamental requirement for effective education and data mining. The main objective of KT is to model and predict the evolving understanding level of a student on different educational tasks.
Baig, Duaa, Nurbakova, Diana, Calabretto, Sylvie, Mbaye, Baba   +3 more
openaire   +2 more sources

Genetic Diagnosis and Discovery Enabled by Large Language Models

Advanced Science, EarlyView.
We demonstrate that large language models (LLMs) can facilitate genetic diagnosis and discovery. LLMs were used to solve four types of genetic problems of sequentially increased complexity. An LLM‐based pipeline could analyze genetic variants in the genomic sequences of human hearing loss or rare genetic disease patients and assist in identifying ...
Tao Tu, Khaled Saab, Weida Liu, Zhouqing Fang, Zhuanfen Cheng, Svetolik Spasic, Maja Djurisic, Hiroaki Mohri, Wenlong Ren, Anil Palepu, Juraj Gottweis, Alan Karthikesalingam, Kavita Kulkarni, Annalisa Pawlosky, Devon Bonner, Elijah Kravets, Shruti Marwaha, Hector R. Mendez, Matthew T. Wheeler, Jonathan A. Bernstein, Undiagnosed Diseases Network, Cheng‐Yu Tsai, Chen‐Chi Wu, Konstantina M. Stankovic, Vivek Natarajan, Gary Peltz   +25 more
wiley   +1 more source

Data Management Opportunities in Unifying Large Language Models + Knowledge Graphs [PDF]

Large Language Models (LLMs), e.g., ChatGPT, PaLM, and LLaMA are transforming natural language processing (NLP) and artificial intelligence (AI). Recent LLMs browse Web knowledge and learn from external knowledge bases, unifying LLMs and knowledge graphs
Chen, Xi, Khan, Arijit, Wu, Tianxing
core   +3 more sources

Using large language models to extract information from pediatric clinical reports.

PLOS Digital Health
Most medical documentation, including clinical reports, exists in unstructured formats, which hinder efficient data analysis and integration into decision-making systems for patient care and research.
Katharina Danhauser, Yingding Wang, Christoph Klein, Uta Tacke, Larissa Mantoan, Laura Aurica Ritter, Florian Heinen, Chiara Nobile, Moritz Tacke   +8 more
doaj   +1 more source

From Illusion to Insight: A Taxonomic Survey of Hallucination Mitigation Techniques in LLMs

AI
Large Language Models (LLMs) exhibit remarkable generative capabilities but remain vulnerable to hallucinations—outputs that are fluent yet inaccurate, ungrounded, or inconsistent with source material.
Ioannis Kazlaris, Efstathios Antoniou, Konstantinos Diamantaras, Charalampos Bratsas   +3 more
doaj   +1 more source

Unit Test Generation Using Large Language Models: A Systematic Literature Review [PDF]

Unit testing is a fundamental aspect of software development, ensuring the correctness and robustness of code implementations. Traditionally, unit tests are manually crafted by developers based on their understanding of the code and its requirements ...
Slotkienė, Asta, Zapkus, Dovydas Marius
core   +2 more sources

MicrobeDiscover: A Knowledge Graph–Enabled AI Framework for Identifying Microbes for Inorganic Nanomaterial Biosynthesis

Advanced Science, EarlyView.
Microbial synthesis of nanomaterials (NMs) is eco‐friendly, but the screening of microorganisms is limited by inefficient traditional methods (currently only involving∽400 microorganisms/90 NMs). We propose AI framework MicrobeDiscover, integrating a knowledge graph of microbe‐NM interactions.
Ludi Wang, Hexing Han, Yufeng Liu, Zhiyuan Ning, Yujie Ma, Haidan Wang, Jinling Xu, Qiansheng Huang, Wenjuan Cui, Yuanchun Zhou, Yang Gao, Bin Wang, Yi Du   +12 more
wiley   +1 more source

Overeducation and spatial flexibility in Italian local labour markets [PDF]

According to a recent strand of literature this paper highlights the relevance of spatial mobility as an explanatory factor of the individual risk of being overeducated.
Croce, Giuseppe, Ghignoni, Emanuela
core   +1 more source

Advancing Precision Nutrition Through Multimodal Data and Artificial Intelligence

Advanced Science, EarlyView.
Individual responses to food vary dramatically, challenging traditional dietary advice. This review explores how the unique genetic makeup, gut microbiome, and brain activity shape host metabolic health. We examine how artificial intelligence integrates these multimodal data to predict individualized dietary needs, moving beyond one‐size‐fits‐all ...
Yuanqing Fu, Ke Zhang, Zelei Miao, Gaoyi Yang, Yujing Huang, Ju‐Sheng Zheng   +5 more
wiley   +1 more source

Large Language Models are Effective Table-to-Text Generators, Evaluators, and Feedback Providers

, 2023
Large language models (LLMs) have shown remarkable ability on controllable text generation. However, the potential of LLMs in generating text from structured tables remains largely under-explored.
Cohan, Arman, Nan, Linyong, Si, Shengyun, Tang, Xiangru, Zhang, Haowei, Zhao, Yilun   +5 more
core