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Related papers: Materials science in the era of large language mod…

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Large language models (LLMs) are rapidly transforming materials science. This review examines recent LLM applications across the materials discovery pipeline, focusing on three key areas: mining scientific literature , predictive modelling,…

Computation and Language · Computer Science 2025-11-17 Fengxu Yang , Weitong Chen , Jack D. Evans

Large Language Models (LLMs) have recently demonstrated remarkable capabilities in natural language processing tasks and beyond. This success of LLMs has led to a large influx of research contributions in this direction. These works…

Computation and Language · Computer Science 2024-10-18 Humza Naveed , Asad Ullah Khan , Shi Qiu , Muhammad Saqib , Saeed Anwar , Muhammad Usman , Naveed Akhtar , Nick Barnes , Ajmal Mian

In this paper, we describe the capabilities and constraints of Large Language Models (LLMs) within disparate academic disciplines, aiming to delineate their strengths and limitations with precision. We examine how LLMs augment scientific…

The rapid development of Large Language Models (LLMs) demonstrates remarkable multilingual capabilities in natural language processing, attracting global attention in both academia and industry. To mitigate potential discrimination and…

Computation and Language · Computer Science 2025-01-08 Kaiyu Huang , Fengran Mo , Xinyu Zhang , Hongliang Li , You Li , Yuanchi Zhang , Weijian Yi , Yulong Mao , Jinchen Liu , Yuzhuang Xu , Jinan Xu , Jian-Yun Nie , Yang Liu

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 emerged as powerful tools in various research domains. This article examines their potential through a literature review and firsthand experimentation. While LLMs offer benefits like cost-effectiveness and…

Human-Computer Interaction · Computer Science 2024-04-10 M. Namvarpour , A. Razi

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

Large Language Models (LLMs) have demonstrated their transformative potential across numerous disciplinary studies, reshaping the existing research methodologies and fostering interdisciplinary collaboration. However, a systematic…

Computation and Language · Computer Science 2025-07-14 Lu Xiang , Yang Zhao , Yaping Zhang , Chengqing Zong

Large language models (LLMs) have been touted to enable increased productivity in many areas of today's work life. Scientific research as an area of work is no exception: the potential of LLM-based tools to assist in the daily work of…

Software Engineering · Computer Science 2024-04-24 Mohamed Nejjar , Luca Zacharias , Fabian Stiehle , Ingo Weber

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) 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

Large language models (LLMs) have become the secret ingredient driving numerous industrial applications, showcasing their remarkable versatility across a diverse spectrum of tasks. From natural language processing and sentiment analysis to…

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

Large Language Models (LLMs) have seen significant use in domains such as natural language processing and computer vision. Going beyond text, image and graphics, LLMs present a significant potential for analysis of time series data,…

Machine Learning · Computer Science 2024-05-08 Xiyuan Zhang , Ranak Roy Chowdhury , Rajesh K. Gupta , Jingbo Shang

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) 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…

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

With the advent of large language models (LLMs), there is a growing interest in applying LLMs to scientific tasks. In this work, we conduct an experimental study to explore applicability of LLMs for configuring, annotating, translating,…

Human-Computer Interaction · Computer Science 2025-10-13 Orcun Yildiz , Tom Peterka

This paper examines the opportunities, limitations, and practical considerations associated with the use of large language models (LLMs) in qualitative research. Drawing on a multidisciplinary perspective that combines expertise in…

Human-Computer Interaction · Computer Science 2026-05-19 Henry Salgado , Meagan R. Kendall , Martine Ceberio , Alexandra Coso Strong
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