Results 51 to 60 of about 2,298 (183)
Communications of the ACM, 1992 Because meaningful sentences are composed of meaningful words, any system that hopes to process natural languages as people do must have information about words and their meanings. This information is traditionally provided through dictionaries, and machine-readable dictionaries are now widely available.
openaire +6 more sources
Human tests for machine models: What lies “Beyond the Imitation Game”?
Journal of Linguistic Anthropology, Volume 36, Issue 1, May 2026.Abstract Benchmarking large language models (LLMs) is a key practice for evaluating their capabilities and risks. This paper considers the development of “BIG Bench,” a crowdsourced benchmark designed to test LLMs “Beyond the Imitation Game.” Drawing on linguistic anthropological and ethnographic analysis of the project's GitHub repository, we examine ...
Noya Kohavi, Anna Weichselbraun
wiley +1 more source
The semantic classification of adjectives in the Bulgarian Wordnet: Towards a multiclass approach
Cognitive Studies | Études cognitives, 2018 The semantic classification of adjectives in the Bulgarian Wordnet: Towards a multiclass approach The paper presents an attempt at semantic classification of adjectives in the Bulgarian wordnet.
Tsvetana Dimitrova, Valentina Stefanova
doaj +1 more source
Benchmarking speech biomarkers of Alzheimer's against cognitive and neural measures
Alzheimer's &Dementia, Volume 22, Issue 4, April 2026.Abstract INTRODUCTION Digital speech biomarkers (DSBs) support the detection and monitoring of Alzheimer's disease (AD) in Latinos. However, they have not been benchmarked against standard cognitive and neuroimaging measures, missing a critical validation milestone. METHODS Thirty‐three AD patients and 33 healthy controls completed verbal fluency tasks,
Ivan Caro +15 more
wiley +1 more source
Size Matters: The Impact of Training Size in Taxonomically-Enriched Word Embeddings
Open Computer Science, 2019 Word embeddings trained on natural corpora (e.g., newspaper collections, Wikipedia or the Web) excel in capturing thematic similarity (“topical relatedness”) on word pairs such as ‘coffee’ and ‘cup’ or ’bus’ and ‘road’.
Maldonado Alfredo +2 more
doaj +1 more source
Conditional Text Generation for AI‐Powered Interviews: A T5‐Based System With GPT‐2 Comparison
Engineering Reports, Volume 8, Issue 4, April 2026.This work introduces an AI‐based interview system that uses T5 to generate context‐specific interview questions and responses. By comparing it with GPT‐2, the study shows T5's ability to produce more coherent and relevant dialogue, supporting advances in automated interview and conversational AI applications.
Kritika Acharya, Rashna K.C., Sudip Rana
wiley +1 more source
LanguagesSpecialized languages can activate different sets of semantic features when compared to general language or express concepts through different words according to the domain.
Chiara Barbero, Raquel Amaro
doaj +1 more source
SciLitMiner: An Intelligent System for Scientific Literature Mining and Knowledge Discovery
Advanced Intelligent Systems, Volume 8, Issue 3, March 2026.SciLitMiner is an intelligent system that federately ingests scientific literature, filters it using advanced information retrieval methods, and applies retrieval‐augmented generation tailored to scientific domains. Demonstrated on creep deformation in γ‐TiAl alloys, SciLitMiner provides a controlled workflow for systematic knowledge discovery and ...
Vipul Gupta +3 more
wiley +1 more source
Building an Arabic Sentiment Lexicon Using Semi-supervised Learning
Journal of King Saud University: Computer and Information Sciences, 2014 Sentiment analysis is the process of determining a predefined sentiment from text written in a natural language with respect to the entity to which it is referring. A number of lexical resources are available to facilitate this task in English.
Fawaz H.H. Mahyoub +2 more
doaj +1 more source
CPT: Pharmacometrics &Systems Pharmacology, Volume 15, Issue 3, March 2026.ABSTRACT The purpose was to evaluate retrieval‐augmented generative (RAG) artificial intelligence (AI) methods for assessing the regulatory compliance of drug information and adherence to best practices in clinical trial protocols. Integrated systems containing RAG and large language model (LLM) components were employed to evaluate drug information and
Shreyas Waikar +2 more
wiley +1 more source