Results 111 to 120 of about 236,117 (266)
Large Language Model‐Based Chatbots in Higher Education
The use of large language models (LLMs) in higher education can facilitate personalized learning experiences, advance asynchronized learning, and support instructors, students, and researchers across diverse fields. The development of regulations and guidelines that address ethical and legal issues is essential to ensure safe and responsible adaptation
Defne Yigci +4 more
wiley +1 more source
Herein, a patient‐mounted neuro optical coherence tomography system that integrates a 5 degrees‐of‐freedom skull‐mounted robot (Skullbot) with a 0.6 mm neuroendoscope for targeted, minimally invasive deep brain imaging, is developed. The system offers high‐resolution imaging with precise deployment, demonstrated through successful tumor imaging in a ...
Chao Xu +7 more
wiley +1 more source
FTGRN introduces an LLM‐enhanced framework for gene regulatory network inference through a two‐stage workflow. It combines a Transformer‐based model, pretrained on GPT‐4 derived gene embeddings and regulatory knowledge, with a fine‐tuning stage utilizing single‐cell RNA‐seq data.
Guangzheng Weng +7 more
wiley +1 more source
Illustration of text data mining of rare earth mineral thermodynamic parameters with the large language model‐powered LMExt. A dataset is built with mined thermodynamic properties. Subsequently, a machine learning model is trained to predict formation enthalpy from the dataset.
Juejing Liu +6 more
wiley +1 more source
Robust Dysarthric Speech Recognition with GAN Enhancement and LLM Correction
This study tackles dysarthric speech recognition by combining generative adversarial network (GAN)‐generated synthetic data with large language model (LLM)‐based error correction. The approach integrates three key elements: an improved CycleGAN to generate synthetic dysarthric speech for data augmentation, a multimodal automatic speech recognition core
Yibo He +3 more
wiley +1 more source
Feature from recent image foundation models (DINOv2) are useful for vision tasks (segmentation, object localization) with little or no human input. Once upsampled, they can be used for weakly supervised micrograph segmentation, achieving strong results when compared to classical features (blurs, edge detection) across a range of material systems.
Ronan Docherty +2 more
wiley +1 more source
Constructing the Corpus of Children's Video Media (CCVM): A new resource and guidelines for constructing comparable and reusable corpora. [PDF]
Gowenlock A +3 more
europepmc +1 more source
SciLitMiner: An Intelligent System for Scientific Literature Mining and Knowledge Discovery
SciLitMiner is an intelligent system that federately ingests scientific literature, filters it using advanced information retrieval methods, and applies retrieval‐augmented generation tailored to scientific domains. Demonstrated on creep deformation in γ‐TiAl alloys, SciLitMiner provides a controlled workflow for systematic knowledge discovery and ...
Vipul Gupta +3 more
wiley +1 more source
Development of a robust corpus for automated evaluation of online health information in Chinese using the DISCERN scale. [PDF]
E T +7 more
europepmc +1 more source
Language‐Guided Robot Grasping Based on Basic Geometric Shape Fitting
This article presents a language‐guided, model‐free grasping framework that integrates multimodal perception with primitive‐based geometric fitting. By explicitly modeling object geometry from RGB‐D data, the method enables semantically controllable grasp pose generation and achieves robust performance in both structured and cluttered real‐world ...
Qun Niu +5 more
wiley +1 more source

