Results 101 to 110 of about 239,466 (252)

Machine Learning‐Assisted Second‐Order Perturbation Theory for Chemical Potential Correction Toward Hubbard U Determination

Advanced Intelligent Discovery, EarlyView.
In this work, the Doubao large language model (LLM) is involved in the formula derivation processes for Hubbard U determination regarding the second‐order perturbations of the chemical potential. The core ML tool is optimized for physical domain knowledge, which is not limited to parameter prediction but rather serves as an interactive physical theory ...
Mingzi Sun, Tong Wu, Baian Chen, Zikang Li, Qiuyang Lu, Lu Lu, Hon Ho Wong, Cheuk Hei Chan, Bolong Huang   +8 more
wiley   +1 more source

On Cost-Effectiveness of Language Models for Time Series Anomaly Detection

Information
Detecting anomalies in time series data is crucial across several domains, including healthcare, finance, and automotive. Large Language Models (LLMs) have recently shown promising results by leveraging robust model pretraining. However, fine-tuning LLMs
Ali Yassine, Luca Cagliero, Luca Vassio
doaj   +1 more source

Evolution of Physical Intelligence Across Scales

Advanced Intelligent Discovery, EarlyView.
By following the evolution of physical intelligence across scales, this article shows how intelligence arises from materials, structures, physical interactions, and collectives. It establishes physical intelligence as the evolutionary foundation upon which embodied intelligence is built.
Ke Liu, Tianyun Huang, Aming Li, Pengyu Lv, Tingting Qin, Wenhui Chen, Hui Wei, Huiling Duan   +7 more
wiley   +1 more source

Survey of Different Large Language Model Architectures: Trends, Benchmarks, and Challenges

IEEE Access
Large Language Models (LLMs) represent a class of deep learning models adept at understanding natural language and generating coherent responses to various prompts or queries.
Minghao Shao, Abdul Basit, Ramesh Karri, Muhammad Shafique   +3 more
doaj   +1 more source

Lower Energy Large Language Models (LLMs)

Computer, 2023
Hsiao-Ying Lin, Jeffrey M. Voas
semanticscholar   +1 more source

Automating AI Discovery for Biomedicine Through Knowledge Graphs and Large Language Models Agents

Advanced Intelligent Discovery, EarlyView.
This work proposes a novel framework that automates biomedical discovery by integrating knowledge graphs with multiagent large language models. A biologically aligned graph exploration strategy identifies hidden pathways between biomedical entities, and specialized agents use this pathway to iteratively design AI predictors and wet‐lab validation ...
Naafey Aamer, Muhammad Nabeel Asim, Shan Munir, Andreas Dengel   +3 more
wiley   +1 more source

LLM‐Based Scientific Assistants for Knowledge Extraction: Which Design Choices Matter?

Advanced Intelligent Discovery, EarlyView.
A comprehensive framework for optimizing Large Language Models in domain‐specific applications is introduced. The LLM Playground integrates Prompt Engineering, knowledge augmentation, and advanced reasoning strategies to enable systematic comparison of architectures and base models.
David Exler, Manuel Raimann, Marc Münker, Maxim Rosin, Joaquin E. Urrutia Gómez, Christof M. Niemeyer, Markus Reischl, Luca Rettenberger   +7 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

JorGPT: Instructor-Aided Grading of Programming Assignments with Large Language Models (LLMs)

Future Internet
This paper explores the application of large language models (LLMs) to automate the evaluation of programming assignments in an undergraduate “Introduction to Programming” course.
Jorge Cisneros-González, Natalia Gordo-Herrera, Iván Barcia-Santos, Javier Sánchez-Soriano   +3 more
doaj   +1 more source

AI Powered Biobanks From Static Archives to Dynamic Discovery Engines

Advanced Intelligent Discovery, EarlyView.
Large language models (LLMs) provide a potential framework for transforming biobanks from static data repositories into intelligent discovery engines. By enabling unified representation and analysis of multimodal biomedical data, LLM‐based systems facilitate dynamic risk prediction, biomarker identification, and mechanistic interpretation, thereby ...
Wenzhen Yin, Yutian Feng, Wenrui Ma, Yuxin Su, Li Min, Juan Liu   +5 more
wiley   +1 more source