Results 101 to 110 of about 429,933 (317)
Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Advanced Intelligent Discovery, EarlyView.Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang +4 more
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
Symbolon, 2020 Theatre and drama methods are moving outside the walls of theatre both in different forms of participatory theatre and in the case of cultural and social performances.
Anja Keränen
doaj
Increasing Assessment Literacy Among LCTL Instructors Through Blended Learning [PDF]
Journal of the National Council of Less Commonly Taught Languages, 2009 This article describes the need for assessment literacy among less commonly taught language (LCTL) educators as well as one approach toward providing professional development to such educators.
Victoria C. Nier +2 more
doaj
Learning, Keeping, and Using Language: Selected Papers from the 8th World Congress of Applied Linguistics [PDF]
, 1992 Marianne Celce‐Murcia
openalex +1 more source
Визначення україномовними та російськомовними науковцями поняття «корпусна лінгвістика» (на матеріалі web-корпусу) [PDF]
, 2015 У статті робиться спроба проаналізувати визначення термінів «корпусна лінгвістика» та «корпусная лингвистика» у веб-корпусі. Здійснено аналіз джерел та дефініцій зазначеного поняття.
Коцюк, Л. (L. Kotsiuk)
core
Advanced Intelligent Systems, EarlyView.This article offers a comprehensive review of topic modeling techniques, tracing their evolution from inception to recent developments. It explores methods such as latent Dirichlet allocation, latent semantic analysis, non‐negative matrix factorization, probabilistic latent semantic analysis, Top2Vec, and BERTopic, highlighting their strengths ...
Pratima Kumari +6 more
wiley +1 more source
The accordian and the deep bowl of spaghetti: Eight researchers' experiences of using IPA as a methodology [PDF]
, 2014 Since 1996 Interpretative Phenomenological Analysis (IPA) has grown rapidly and been applied in areas outside its initial “home” of health psychology. However, explorations of its application from a researcher's perspective are scarce.
Holland, Fiona G. +7 more
core +1 more source
Topically Driven Neural Language Model
, 2017 Language models are typically applied at the sentence level, without access to the broader document context. We present a neural language model that incorporates document context in the form of a topic model-like architecture, thus providing a succinct ...
Baldwin, Timothy +2 more
core +1 more source
Advanced Intelligent Systems, EarlyView.Image classification plays a pivotal role in biomedical image analysis. Herein, it is shown that large multimodal models, such as GPT‐4, achieve superior performance in one‐shot learning, generalization, interpretability, and text‐driven image classification. Applications span tissue, cell type, cellular state, and disease classification, outperforming
Wenpin Hou +4 more
wiley +1 more source