Results 61 to 70 of about 1,092,002 (281)

In Situ Graph Reasoning and Knowledge Expansion Using Graph‐PRefLexOR

open access: yesAdvanced Intelligent Discovery, EarlyView.
Graph‐PRefLexOR is a novel framework that enhances language models with in situ graph reasoning, symbolic abstraction, and recursive refinement. By integrating graph‐based representations into generative tasks, the approach enables interpretable, multistep reasoning.
Markus J. Buehler
wiley   +1 more source

A Cross-Linguistic Preference For Torso Stability In The Lexicon: Evidence From 24 Sign Languages [PDF]

open access: yes, 2016
When the arms move in certain ways, they can cause the torso to twist or rock. Such extraneous torso movement is undesirable, especially during sign language communication, when torso position may carry linguistic significance, so we expend effort to ...
Napoli, Donna Jo, Sanders, N.
core   +1 more source

Named Entity Recognition Models for Machine Learning Interatomic Potentials: A User‐Centric Approach to Knowledge Extraction from Scientific Literature

open access: yesAdvanced Intelligent Discovery, EarlyView.
Named entity recognition pipeline for knowledge extraction from scientific literature. Machine learning interatomic potential (MLIP) is an emerging technique that has helped achieve molecular dynamics simulations with unprecedented balance between efficiency and accuracy. Recently, the body of MLIP literature has been growing rapidly, which propels the
Bowen Zheng, Grace X. Gu
wiley   +1 more source

Artificial Intelligence for Bone: Theory, Methods, and Applications

open access: yesAdvanced Intelligent Discovery, EarlyView.
Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan   +3 more
wiley   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

open access: yesAdvanced 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

Does Scale-Free Syntactic Network Emerge in Second Language Learning?

open access: yesFrontiers in Psychology, 2019
Language is a complex system during whose operation many properties may emerge spontaneously. Using complex network approach, existing studies have found that, in first language (L1) acquisition, syntactic complex network featuring the scale-free and the
Jingyang Jiang   +4 more
doaj   +1 more source

Review: Encyclopedia of linguistics [PDF]

open access: yes, 2005
The two volumes of this new encyclopedia contain over five hundred self-contained essays, each between 1000 and 3000 words, covering a very wide range of topics.
Barnard, Roger
core   +1 more source

Large Language Model‐Based Chatbots in Higher Education

open access: yesAdvanced 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

The linguistics of gender [PDF]

open access: yes, 1996
This chapter explores grammatical gender as a linguistic phenomenon. First, I define gender in terms of agreement, and look at the parts of speech that can take gender agreement.
Van Berkum, J.
core  

Recent Advancements in Topic Modeling Techniques for Healthcare, Bioinformatics, and Other Potential Applications

open access: yesAdvanced 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

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