Results 51 to 60 of about 106,494 (293)

Semantic Modeling in Materials Science and Engineering With Platform MaterialDigital Core Ontology 3.0

Advanced Engineering Materials, EarlyView.
The community‐driven Platform MaterialDigital Core Ontology (PMDco) 3.0 is introduced as a Basic Formal Ontology‐aligned semantic backbone for the processing–structure–properties paradigm in Materials Science and Engineering. Modular engineering, automated releases, and validation workflows are highlighted and key semantic patterns for materials ...
Markus Schilling, Philipp von Hartrott, Jörg Waitelonis, Thomas Hanke, Henk Birkholz, Hossein Beygi Nasrabadi, Khashayar Razghandi, Kamilla Zaripova, Felix Thonagel, Fabian Neuhaus, Martin Glauer, Lars Vogt, Harald Sack, Lutz Mädler, Bernd Bayerlein, Chris Eberl   +15 more
wiley   +1 more source

CS1-LLM: Integrating LLMs into CS1 Instruction

Proceedings of the 2024 on Innovation and Technology in Computer Science Education V. 1
The recent, widespread availability of Large Language Models (LLMs) like ChatGPT and GitHub Copilot may impact introductory programming courses (CS1) both in terms of what should be taught and how to teach it. Indeed, recent research has shown that LLMs are capable of solving the majority of the assignments and exams we previously used in CS1.
Annapurna Vadaparty, Daniel Zingaro, David H. Smith IV, Mounika Padala, Christine Alvarado, Jamie Gorson Benario, Leo Porter 0001   +6 more
openaire   +4 more sources

Physics‐Grounded Materials Artificial Intelligence for Reliable Materials Discovery

Advanced Functional Materials, EarlyView.
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, Qian Wang, Seong‐Hoon Jang, Hao Li   +3 more
wiley   +1 more source

Towards Vision Enhancing LLMs: Empowering Multimodal Knowledge Storage and Sharing in LLMs [PDF]

, 2023
Recent advancements in multimodal large language models (MLLMs) have achieved significant multimodal generation capabilities, akin to GPT-4. These models predominantly map visual information into language representation space, leveraging the vast ...
Li, Yunxin, Wang, Wei, Cao, Xiaochun, Hu, Baotian, Zhang, Min   +4 more
core   +1 more source

A Philosophical and Ontological Perspective on Artificial General Intelligence and The Metaverse

Journal of Metaverse
This paper leverages various philosophical and ontological frameworks to explore the concept of embodied artificial general intelligence (AGI), its relationship to human consciousness, and the key role of the metaverse in facilitating this relationship ...
Martin Schmalzried
doaj   +1 more source

Agentic AutoSurvey: Let LLMs Survey LLMs

CoRR
29 pages, 7 ...
Yixin Liu 0002, Yonghui Wu 0001, Denghui Zhang, Lichao Sun 0001   +3 more
openaire   +3 more sources

An Epigenetic Fate Converter Based on Nuclei‐Targeting Lipid Nanoparticles Drives Neuronal Programming of Stem Cells for Spinal Cord Repair

Advanced Functional Materials, EarlyView.
Schematic illustration of LNP‐MPG nuclei‐targeting delivery of HMW‐FGF2 promoting histone acetylation to regulate the fate of DPSCs and treat spinal cord injury. LNPs components include pHMW‐FGF2 plasmid, DSPC, Dlin‐MC3‐DMA, cholesterol, and PEG2000, and are modified with MPG to form HMW‐FGF2@LNP‐MPG (HLM). HLM nuclei‐targets DPSCs to deliver HMW‐FGF2,
Heng Zhou, Qiang Qin, Xiqin Li, Hanyu Ding, Chun Xu, Yan He, Qingsong Ye   +6 more
wiley   +1 more source

Generative Artificial Intelligence in Ubiquitous Learning: Evaluating a Chatbot-based Recommendation Engine for Personalized and Context-aware Education

Acta Informatica Pragensia
Background: Ubiquitous learning environments aim to provide personalized and context-aware educational resources; however, traditional recommendation systems often fall short in meeting these dynamic learner needs.Objective: This study develops and ...
Manel Guettala, Samir Bourekkache, Okba Kazar, Saad Harous   +3 more
doaj   +1 more source

LEAD: Literature Enhanced Ab Initio Discovery of Nitride Dusting Layers for Enhanced Tunnel Magnetoresistance and Lower Resistance Magnetic Tunnel Junctions

Advanced Materials, EarlyView.
Magnetic tunnel junctions (MTJs) using MgO tunnel barriers face challenges of high resistance‐area product and low tunnel magnetoresistance (TMR). To discover alternative materials, Literature Enhanced Ab initio Discovery (LEAD) is developed. The LEAD‐predicted materials are theoretically evaluated, showing that MTJs with dusting of ScN or TiN on ...
Sabiq Islam, William S. Rogers, Chen‐Yu Hu, Ming‐Yuan Song, Xinyu Bao, Shehrin Sayed, Jean Anne C. Incorvia   +6 more
wiley   +1 more source

Reductive, Exclusionary, Normalising: The Limits of Generative AI Music

Transactions of the International Society for Music Information Retrieval
Up until recently, most approaches to music generation were based on deductive logic: generative rules were devised on the basis of musicians’ preferences, subjective appreciation and dominant music theories.
Fabio Morreale, Marco A. Martinez-Ramirez, Raul Masu, WeiHsiang Liao, Yuki Mitsufuji   +4 more
doaj   +1 more source