Results 101 to 110 of about 106,494 (293)

ChatGPT Relies More Heavily on Consonants Than on Vowels to Recognize Words

Journal of Cognition
Humans develop biases during language learning. For example, we rely more heavily on consonants than on vowels to identify words. Advances on artificial intelligence have allowed the development of proficient large language models that sometimes mimic ...
Juan Manuel Toro
doaj   +1 more source

An Integrated NLP‐ML Framework for Property Prediction and Design of Steels

Advanced Science, EarlyView.
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju, Adithya Umanath Rai, Jose Thomson, Marzie Ghorbani, Shujing Zhao, Nick Birbilis   +5 more
wiley   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

Promoting problem-solving skills in computer programming with an LLM-empowered multi-agent system: A cognitive apprenticeship perspective

Educational Technology & Society
To address the limitations of large language models in fostering problem-solving skills in programming, this paper proposes an LLM-empowered multi-agent system grounded in a theoretical framework that integrates cognitive apprenticeship with the Use ...
Xiaochun Wang, Jingze Li, Qirui Gu and Deming Liang
doaj   +1 more source

Automated Extraction of Multicomponent Alloy Data Using Large Language Models for Sustainable Design

Advanced Science, EarlyView.
A large language model (LLM) based pipeline is developed to automatically extract a comprehensive and accurate multicomponent alloy database from literature corpus. The extracted dataset is integrated with sustainability indicators to identify potential alloys that outperform existing industrial benchmark materials in terms of both performance and ...
Aravindan Kamatchi Sundaram, Mohit Chakraborty, Sai Mani Kumar Devathi, B. Pabitramohan Prusty, Rohit Batra   +4 more
wiley   +1 more source

On the Use of Large Language Models for Improving Student and Staff Experience in Higher Education

Open Education Studies
Large language models (LLMs) hold great promise for enhancing teaching and learning in higher education, yet educators and administrators still lack practical examples to guide their adoption.
O’Neill Sam, Mulgrew David, Bagdasar Ovidiu   +2 more
doaj   +1 more source

Automating Chemical Reasoning in High‐Throughput Phase Identification With a Probabilistic, LLM‐Guided Framework

Advanced Science, EarlyView.
Autonomous laboratories can now synthesize materials faster than experts can interpret the resulting diffraction data. A probabilistic framework combines refinement‐fit metrics with large language model‐derived chemical reasoning to rank competing phase interpretations and flag those unsuitable for autonomous use.
Olympia Dartsi, Lauren N. Walters, Amalie E. Trewartha, Steven B. Torrisi, Amanda Volk, Liam Joyce, Gerbrand Ceder, Anubhav Jain   +7 more
wiley   +1 more source

Research and outlook on techniques for improving the quality of substation monitoring data

Zhejiang dianli
With the advancement of digitalization and intelligence in substation protection and monitoring systems， the volume of multi-source heterogeneous data generated by secondary systems has increased sharply， with continuously rising dimensionality. This has
ZHENG Xiang, CHEN Shaoyu, WU Jiayi, ZHANG Yikang, ZHANG Min, YU Yiting, XUE Ancheng   +6 more
doaj   +1 more source

A Generative Neuro‐Symbolic AI for Protein Sequence Design

Advanced Science, EarlyView.
We introduce EffieDes, a neuro‐symbolic framework coupling deep learning‐based fitness landscape parameterization with exact automated reasoning. Unlike greedy sampling, EffieDes identifies sequences that globally optimize fitness while satisfying intricate design constraints.
Marianne Defresne, Delphine Dessaux, Samuel Buchet, Lucie Barthe, Liza Ammar‐Khodja, Bessam Azizi, Valentin Durante, Gianluca Cioci, Simon de Givry, Alain Roussel, Luis F. Garcia‐Alles, Thomas Schiex, Sophie Barbe   +12 more
wiley   +1 more source

When Do LLMs Need Retrieval Augmentation? Mitigating LLMs' Overconfidence Helps Retrieval Augmentation [PDF]

Large Language Models (LLMs) have been found to have difficulty knowing they do not possess certain knowledge and tend to provide specious answers in such cases.
Ni, Shiyu, Guo, Jiafeng, Bi, Keping, Cheng, Xueqi   +3 more
core   +1 more source