Results 81 to 90 of about 9,919 (261)
Automating AI Discovery for Biomedicine Through Knowledge Graphs and Large Language Models Agents
Advanced Intelligent Discovery, EarlyView.This work proposes a novel framework that automates biomedical discovery by integrating knowledge graphs with multiagent large language models. A biologically aligned graph exploration strategy identifies hidden pathways between biomedical entities, and specialized agents use this pathway to iteratively design AI predictors and wet‐lab validation ...
Naafey Aamer +3 more
wiley +1 more source
Compiling Specialised Comparable Corpora. Should we always trust (Semi-)automatic Compilation Tools?
Linguamática, 2016 Decisions at the outset of compiling a comparable corpus are of crucial importance for how the corpus is to be built and analysed later on. Several variables and external criteria are usually followed when building a corpus but little is been said ...
Hernani Costa +3 more
doaj
ILCEAThe research focuses on the study of nouns in a bilingual specialised press corpus (around 260,000 words), made up of original texts dealing with economic and financial topics in Italian and in French.
Marie-Pierre Escoubas Benveniste +1 more
doaj +1 more source
LLM‐Based Scientific Assistants for Knowledge Extraction: Which Design Choices Matter?
Advanced Intelligent Discovery, EarlyView.A comprehensive framework for optimizing Large Language Models in domain‐specific applications is introduced. The LLM Playground integrates Prompt Engineering, knowledge augmentation, and advanced reasoning strategies to enable systematic comparison of architectures and base models.
David Exler +7 more
wiley +1 more source
When Biology Meets Medicine: A Perspective on Foundation Models
Advanced Intelligent Discovery, EarlyView.Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu +3 more
wiley +1 more source
A Corpus-Based Study of Dual Pronoun Translation
Darnioji daugiakalbystėThis article aims to answer the following questions: what is the distribution of dual pronouns in original and translated Lithuanian fiction texts; what English language patterns are rendered by Lithuanian dual pronouns; and how Lithuanian dual pronouns ...
Vaičenonienė Jurgita
doaj +1 more source
AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective
Advanced Intelligent Discovery, EarlyView.The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley +1 more source
Large Language Model‐Based Chatbots in Higher Education
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.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
THE ROLE OF CORPUS LINGUISTICS IN CONTEMPORARY LINGUISTICS RESEARCH AND TRANSLATION STUDIES
Вестник Волгоградского государственного университета: Серия 2. ЯзыкознаниеThe article presents a systematic review of research papers on corpus linguistics as an innovative direction in empirical linguistics. It reveals the theoretical and methodological foundations of the field, defines the specifics of corpus linguistics in
Pei Haitong
doaj +1 more source
Calibration‐Free Electromyography Motor Intent Decoding Using Large‐Scale Supervised Pretraining
Advanced Intelligent Systems, EarlyView.Calibration‐free electromyography motor intent decoding is enabled through large‐scale supervised pretraining across heterogeneous datasets. A Spatially Aware Feature‐learning Transformer processes variable channel counts and electrode geometries, allowing transfer across users and recording setups. On a held‐out benchmark, fine‐tuned cross‐user models
Alexander E. Olsson +3 more
wiley +1 more source