Results 81 to 90 of about 19,032 (297)
ABSTRACT Mental well‐being is central to adult learner success, yet many adult education institutions lack capacity to provide timely and accessible support. This article examines how artificial intelligence (AI) can strengthen mental health–adjacent supports in adult and continuing higher education, with attention to professional practice and ...
Adam L. McClain, Thomas Wade
wiley +1 more source
Transformer models are the state-of-the-art in Natural Language Processing (NLP) and the core of the Large Language Models (LLMs). We propose a transformer-based model for transition-based dependency parsing of free word order languages.
Fatima Tuz Zuhra +2 more
doaj +1 more source
ABSTRACT Background Cognitive impairment is a common non‐motor symptom in Multiple Sclerosis (MS), negatively affecting autonomy and Quality of Life (QoL). Innovative rehabilitation strategies, such as semi‐immersive virtual reality (VR) and computerized cognitive training (CCT), may offer advantages over traditional cognitive rehabilitation (TCR ...
Maria Grazia Maggio +8 more
wiley +1 more source
Lexicon-Enhanced LSTM With Attention for General Sentiment Analysis
Long short-term memory networks (LSTMs) have gained good performance in sentiment analysis tasks. The general method is to use LSTMs to combine word embeddings for text representation.
Xianghua Fu +4 more
doaj +1 more source
Objective To support high‐quality, patient‐centered care for systemic lupus erythematosus (SLE), the American College of Rheumatology (ACR) developed evidence‐based measures incorporating clinical and patient‐reported outcome measures (PROMs). Using the Consolidated Framework for Implementation Research (CFIR), we conducted semistructured interviews ...
Catherine Nasrallah +13 more
wiley +1 more source
A Joint Model for Word Embedding and Word Morphology [PDF]
This paper presents a joint model for performing unsupervised morphological analysis on words, and learning a character-level composition function from morphemes to word embeddings. Our model splits individual words into segments, and weights each segment according to its ability to predict context words.
Rei, Marek, Cao, Kris
openaire +3 more sources
Def2Vec : a model to extract word embeddings from dictionary definitions
LAUREA MAGISTRALEIl sistema più diffuso per rappresentare le parole di un testo al fine di elaborare dei contenuti in linguaggio naturale è l'uso dei word embeddings.
Morazzoni, Irene
core
Evaluating word association-derived word embeddings on semantic analogies [PDF]
Word embeddings trained on large scale text corpora are central to modern natural language processing and are also important as cognitive models and tools in psycholinguistic research.
Cabana, Álvaro +3 more
core
What Do Large Language Models Know About Materials?
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer +2 more
wiley +1 more source
Learning Bilingual Word Embedding Mappings with Similar Words in Related Languages Using GAN
Cross-lingual word embeddings display words from different languages in the same vector space. They provide reasoning about semantics, compare the meaning of words across languages and word meaning in multilingual contexts, necessary to bilingual lexicon
Ghafour Alipour +2 more
doaj +1 more source

