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Related papers: Large language models in materials science and the…

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Large Language Models (LLMs) have garnered considerable interest due to their impressive natural language capabilities, which in conjunction with various emergent properties make them versatile tools in workflows ranging from complex code…

Materials Science · Physics 2024-10-22 Ge Lei , Ronan Docherty , Samuel J. Cooper

Large language models (LLMs) have emerged as powerful tools in chemistry, significantly impacting molecule design, property prediction, and synthesis optimization. This review highlights LLM capabilities in these domains and their potential…

Machine Learning · Computer Science 2024-11-18 Mayk Caldas Ramos , Christopher J. Collison , Andrew D. White

Large language models (LLMs) have rapidly advanced natural language processing, driving significant breakthroughs in tasks such as text generation, machine translation, and domain-specific reasoning. The field now faces a critical dilemma…

Computation and Language · Computer Science 2025-10-15 Jiya Manchanda , Laura Boettcher , Matheus Westphalen , Jasser Jasser

Large language models (LLMs) have ushered in a new era for processing complex information in various fields, including science. The increasing amount of scientific literature allows these models to acquire and understand scientific…

Computation and Language · Computer Science 2024-08-21 Huy Quoc To , Ming Liu , Guangyan Huang

The exponential growth of text-based data in domains such as healthcare, education, and social sciences has outpaced the capacity of traditional qualitative analysis methods, which are time-intensive and prone to subjectivity. Large…

Large Language Models (LLMs) are increasingly applied in the fields of mechanical engineering and materials science. As models that establish connections through the interface of language, LLMs can be applied for step-wise reasoning through…

Applied Physics · Physics 2025-07-22 Adrian Ehrenhofer , Thomas Wallmersperger , Gianaurelio Cuniberti

The vast majority of materials science knowledge exists in unstructured natural language, yet structured data is crucial for innovative and systematic materials design. Traditionally, the field has relied on manual curation and partial…

Large Language Models (LLMs) have recently emerged as a focal point of research and application, driven by their unprecedented ability to understand and generate text with human-like quality. Even more recently, LLMs have been extended into…

Computation and Language · Computer Science 2024-04-03 Kilian Carolan , Laura Fennelly , Alan F. Smeaton

Large language models (LLMs) have exhibited exceptional capabilities in natural language understanding and generation, image recognition, and multimodal tasks, charting a course towards AGI and emerging as a central issue in the global…

Computation and Language · Computer Science 2025-11-20 Guoqiang Liang , Jingqian Gong , Mengxuan Li , Gege Lin , Shuo Zhang

The integration of artificial intelligence into various domains is rapidly increasing, with Large Language Models (LLMs) becoming more prevalent in numerous applications. This work is included in an overall project which aims to train an…

Computational Physics · Physics 2025-01-09 Christophe Bajan , Guillaume Lambard

Large Language Models (LLMs) create exciting possibilities for powerful language processing tools to accelerate research in materials science. While LLMs have great potential to accelerate materials understanding and discovery, they…

Materials Science · Physics 2024-09-26 Santiago Miret , N M Anoop Krishnan

Large language models (LLMs) and transformer-based architectures are increasingly utilized for source code analysis. As software systems grow in complexity, integrating LLMs into code analysis workflows becomes essential for enhancing…

Software Engineering · Computer Science 2025-03-25 Hamed Jelodar , Mohammad Meymani , Roozbeh Razavi-Far

In many scientific fields, large language models (LLMs) have revolutionized the way text and other modalities of data (e.g., molecules and proteins) are handled, achieving superior performance in various applications and augmenting the…

Computation and Language · Computer Science 2024-10-01 Yu Zhang , Xiusi Chen , Bowen Jin , Sheng Wang , Shuiwang Ji , Wei Wang , Jiawei Han

Large language models (LLMs) have shown significant potential to change how we write, communicate, and create, leading to rapid adoption across society. This dissertation examines how individuals and institutions are adapting to and…

Computation and Language · Computer Science 2025-06-24 Weixin Liang

Large Language Models (LLMs) are catalyzing a paradigm shift in scientific discovery, evolving from task-specific automation tools into increasingly autonomous agents and fundamentally redefining research processes and human-AI…

Computation and Language · Computer Science 2025-09-18 Tianshi Zheng , Zheye Deng , Hong Ting Tsang , Weiqi Wang , Jiaxin Bai , Zihao Wang , Yangqiu Song

Large Language Models (LLMs) have emerged as a transformative power in enhancing natural language comprehension, representing a significant stride toward artificial general intelligence. The application of LLMs extends beyond conventional…

Due to an exponential increase in published research articles, it is impossible for individual scientists to read all publications, even within their own research field. In this work, we investigate the use of large language models (LLMs)…

Large language models (LLMs) are beginning to reshape how chemists plan and run reactions in organic synthesis. Trained on millions of reported transformations, these text-based models can propose synthetic routes, forecast reaction…

Artificial Intelligence · Computer Science 2025-08-08 Kartar Kumar Lohana Tharwani , Rajesh Kumar , Sumita , Numan Ahmed , Yong Tang

Large Language Models (LLMs) are distinguished by their architecture, which dictates their parameter size and performance capabilities. Social scientists have increasingly adopted LLMs for text classification tasks, which are difficult to…

Computation and Language · Computer Science 2024-11-05 Marcello Carammia , Stefano Maria Iacus , Giuseppe Porro
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