Results 101 to 110 of about 63,129 (302)

CrossMatAgent: AI‐Assisted Design of Manufacturable Metamaterial Patterns via Multi‐Agent Generative Framework

Advanced Intelligent Discovery, EarlyView.
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian, Martin Taylor Sobczak, Dhanush Patil, Jixin Hou, Lin Pang, Arunachalam Ramanathan, Libin Yang, Xianyan Chen, Yuval Golan, Xiaoming Zhai, Hongyue Sun, Kenan Song, Xianqiao Wang   +12 more
wiley   +1 more source

Large language models: an overview of foundational architectures, recent trends, and a new taxonomy

Discover Applied Sciences
Since the introduction of foundational models such as Bidirectional Encoder Representations from Transformers (BERT) and Generative Pre-trained Transformers (GPT), there has been rapid evolution in both the scale and application of large language models (
Ibomoiye Domor Mienye, Nobert Jere, George Obaido, Oyindamola Omolara Ogunruku, Ebenezer Esenogho, Cameron Modisane   +5 more
doaj   +1 more source

Artificial Intelligence for Bone: Theory, Methods, and Applications

Advanced 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, Haicang Zhang, Liping Tong, Di Chen   +3 more
wiley   +1 more source

Potential Benefits of Employing Large Language Models in Research in Moral Education and Development

, 2023
Recently, computer scientists have developed large language models (LLMs) by training prediction models with large-scale language corpora and human reinforcements.
Han, Hyemin
core  

LLM-SAP: Large Language Models Situational Awareness-Based Planning

2024 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)
This article has been accepted by ICME2024 Workshop MML4SG.
Wang, Liman, Zhong, Hanyang
openaire   +2 more sources

Deep Learning‐Assisted Design of Mechanical Metamaterials

Advanced Intelligent Discovery, EarlyView.
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong, Pu Wen, Zhiping Chai, Dunxuan Wu, Han Ding, Zhigang Wu   +5 more
wiley   +1 more source

A chatbot for a thought: the flower of evil has bloomed (60 Years Later) [PDF]

This article examines the implications of recent advancements in Large Language Models (LLMs) through the lens of Marshall McLuhan's seminal work Understanding Media.
Granata, Paolo
core   +3 more sources

Large Language Model (LLM)-Enabled Graphs in Dynamic Networking

IEEE Network
Recent advances in generative artificial intelligence (AI), and particularly the integration of large language models (LLMs), have had considerable impact on multiple domains. Meanwhile, enhancing dynamic network performance is a crucial element in promoting technological advancement and meeting the growing demands of users in many applications areas ...
Geng Sun, Yixian Wang, Dusit Niyato, Jiacheng Wang, Xinying Wang, H. Vincent Poor, Khaled B. Letaief   +6 more
openaire   +2 more sources

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

Advanced 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, Xinyi Chen, Xu Ye, Yulin Yang, Bin Ai   +4 more
wiley   +1 more source

A Survey of Robot Intelligence with Large Language Models

Applied Sciences
Since the emergence of ChatGPT, research on large language models (LLMs) has actively progressed across various fields. LLMs, pre-trained on vast text datasets, have exhibited exceptional abilities in understanding natural language and planning tasks ...
Hyeongyo Jeong, Haechan Lee, Changwon Kim, Sungtae Shin   +3 more
doaj   +1 more source