Results 91 to 100 of about 8,049,290 (285)
Uncertainty-Aware Natural Language Inference with Stochastic Weight Averaging
This paper introduces Bayesian uncertainty modeling using Stochastic Weight Averaging-Gaussian (SWAG) in Natural Language Understanding (NLU) tasks.
Virpioja, Sami +4 more
core
The physical realization of artificial neurons is a critical challenge for energy‐efficient neuromorphic computing. This review presents a comprehensive analysis of the evolution of artificial neuron implementations from conventional CMOS to emerging post‐CMOS technologies.
Kannan Udaya Mohanan +4 more
wiley +1 more source
Large Language Models meet moral values: A comprehensive assessment of moral abilities
Automatic moral classification in textual data is crucial for various fields including Natural Language Processing (NLP), social sciences, and ethical AI development.
Luana Bulla +3 more
doaj +1 more source
Towards robust and generalisable natural language predicate inference [PDF]
Natural language predicate inference is an important task of natural language processing, which bears particular significance in identifying supporting material for answering questions in the open domain.
Li, Tianyi
core +1 more source
Physics‐Grounded Materials Artificial Intelligence for Reliable Materials Discovery
Physics‐Grounded Materials AI (PhysMat AI) integrates physical priors, descriptors, constraints, verification, and data infrastructure into a unified full‐stack framework, enabling reliable, interpretable, and autonomous AI‐driven materials discovery.
Yuhang Wang +3 more
wiley +1 more source
Using Neural Networks to Generate Inferential Roles for Natural Language
Neural networks have long been used to study linguistic phenomena spanning the domains of phonology, morphology, syntax, and semantics. Of these domains, semantics is somewhat unique in that there is little clarity concerning what a model needs to be ...
Peter Blouw, Chris Eliasmith
doaj +1 more source
Natural Language Inference (NLI) via LLMs.
Natural Language Inference (NLI) is a fundamental task in Natural Language Processing that aims to determine whether a hypothesis can be inferred from a given premise.
Pérez Terán, Nicolás
core +1 more source
Advanced ink systems for solution‐processed textile triboelectric nanogenerators are systematically summarized, spanning conductive, tribo‐negative, and tribo‐positive layers. By connecting ink chemistry, deposition methods, and device function, the present review reveals the key governing principles of solution development and highlights practical ...
Xinlong Sun, Stephen Beeby
wiley +1 more source
Natural language directed inference from ontologies [PDF]
This paper presents an investigation into the problem of content determination in natural language generation (NLG), using as an example the problem of determining what to say when asked “What is an A?”, where A is a concept defined in an OWL ontology ...
Jeff Z. Pan +3 more
core +1 more source
This work reveals the UV‐curing‐induced monomer‐rich domain, oligomer‐rich domain, and entangled oligomer domain. The cured submicron films in stressed state induce interlayer nano‐wrinkle structures during the deposition of the second layer. Stress‐free cured films in relaxed state form non‐diffusive, diffusive and semi‐diffusive interlayer ...
Shouzheng Chen +13 more
wiley +1 more source

