Results 101 to 110 of about 131,744 (288)
Journal of Organizational Behavior, EarlyView.ABSTRACT With rising use of artificial intelligence (AI) in organizations, alongside increasing mental health issues, we seek to understand how AI use affects human stress. Drawing on the automation–augmentation perspective, we propose that AI control over decision‐making thwarts human autonomy and thus contributes to stress.
Florian Klonek, Sharon Parker
wiley +1 more source
Language acquisition and machine learning [PDF]
, 1986 In this paper, we review recent progress in the field of machine learning and examine its implications for computational models of language acquisition. As a framework for understanding this research, we propose four component tasks involved in learning ...
Carbonell, Jaime G., Langley, Pat
core +1 more source
AI‐powered nursing handoffs: Introducing and evaluating the patient report template
Learning Health Systems, EarlyView.Abstract Purpose To understand (1) if nurses view the individual components of the Patient Report Template as useful in their day‐to‐day workflow, and (2) understand the perceptions of nurses related to artificial intelligence use in their day‐to‐day work.
Gabriel Vald +3 more
wiley +1 more source
How to Conduct a Multi‐Domain Systematic (Literature) Review? Guidelines Using The Lotus Protocol
Psychology &Marketing, EarlyView.ABSTRACT Complex challenges increasingly demand multidisciplinary research across intersecting knowledge domains. However, existing systematic (literature) review protocols offer limited guidance and tend to confine scholars to single‐domain or single‐intersection reviews.
Bart J. A. van Bueren +6 more
wiley +1 more source
Frontiers in Psychology, 2019 This paper presents an experimental study investigating artificial grammar learning in monolingual and bilingual children, with and without dyslexia, using an original methodology.
Maria Vender +4 more
doaj +1 more source
Few-Shot Bayesian Imitation Learning with Logical Program Policies
, 2019 Humans can learn many novel tasks from a very small number (1--5) of demonstrations, in stark contrast to the data requirements of nearly tabula rasa deep learning methods.
Allen, Kelsey R. +4 more
core +1 more source
Macromolecular Rapid Communications, EarlyView.This work presents a structure‐aware graph convolutional network that models polymers as statistical ensembles to predict macroscopic properties. By combining topologically realistic graphs generated via kinetic Monte Carlo simulations with explicit molar mass distributions, the framework achieves high accuracy in classifying architectures and ...
Julian Kimmig +7 more
wiley +1 more source
Frontiers in Psychology, 2019 Both adjacent and non-adjacent dependencies (AD and NAD) are present in natural language and other domains, yet the learning of non-adjacent sequential dependencies generally only occurs under favorable circumstances.
Joanne A. Deocampo +4 more
doaj +1 more source
Uncovering Semantic Patterns in Sustainability Research: A Systematic NLP Review
Sustainable Development, EarlyView.ABSTRACT This study maps how Natural Language Processing (NLP) contributes to sustainability. Using a PRISMA‐guided review of 131 English‐language articles from Web of Science (2018–2025), we combine bibliometric co‐word mapping with BERTopic to derive complementary structural and semantic views. Four themes emerge: Topic 0—Climate Change Discourse and
Ehsan Tashakori +3 more
wiley +1 more source
Inductive learning of locality relations in segmental phonology
Laboratory Phonology, 2019 This paper reports on a series of artificial grammar learning experiments focused on locality relations in patterns of long-distance consonant agreement (harmony) and disagreement (dissimilation).
Gunnar Hansson, Kevin James McMullin
doaj +2 more sources