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Related papers: LLMs in Qualitative Research: Opportunities, Limit…

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The use of large language models (LLMs) for qualitative analysis is gaining attention in various fields, including software engineering, where qualitative methods are essential for understanding human and social factors. This study aimed to…

Software Engineering · Computer Science 2025-03-11 Matheus de Morais Leça , Lucas Valença , Reydne Santos , Ronnie de Souza Santos

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…

Qualitative researchers use tools to collect, sort, and analyze their data. Should qualitative researchers use large language models (LLMs) as part of their practice? LLMs could augment qualitative research, but it is unclear if their use…

Human-Computer Interaction · Computer Science 2025-03-03 Hope Schroeder , Marianne Aubin Le Quéré , Casey Randazzo , David Mimno , Sarita Schoenebeck

We review discourses about the philosophy of science in qualitative research and evidence from cognitive linguistics in order to ground a framework for discussing the use of Large Language Models (LLMs) to support the qualitative analysis…

Human-Computer Interaction · Computer Science 2024-07-17 James Eschrich , Sarah Sterman

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

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…

This paper provides a primer on Large Language Models (LLMs) and identifies their strengths, limitations, applications and research directions. It is intended to be useful to those in academia and industry who are interested in gaining an…

Computation and Language · Computer Science 2024-12-09 Sandra Johnson , David Hyland-Wood

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 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) are powerful artificial intelligence (AI) tools transforming how research is conducted. However, their use in research has been met with skepticism, due to concerns about hallucinations, biases and potential…

Artificial Intelligence · Computer Science 2025-07-08 Ruian Ke , Ruy M. Ribeiro

This paper addresses the conceptual, methodological and technical challenges in studying large language models (LLMs) and the texts they produce from a quantitative linguistics perspective. It builds on a theoretical framework that…

Computation and Language · Computer Science 2024-08-30 Jiří Milička

Large Language Models (LLMs) have recently gained significant attention due to their remarkable capabilities in performing diverse tasks across various domains. However, a thorough evaluation of these models is crucial before deploying them…

While many researchers use Large Language Models (LLMs) through chat-based access, their real potential lies in leveraging LLMs via application programming interfaces (APIs). This paper conceptualizes LLMs as universal text processing…

Computation and Language · Computer Science 2026-03-23 Ivan Zupic

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

[Context] Large Language Models (LLMs) are increasingly used to assist qualitative research in Software Engineering (SE), yet the methodological implications of this usage remain underexplored. Their integration into interpretive processes…

Software Engineering · Computer Science 2025-11-19 Tatiane Ornelas , Allysson Allex Araújo , Júlia Araújo , Marina Araújo , Bianca Trinkenreich , Marcos Kalinowski

Large language models (LLMs) show promise for improving the efficiency of qualitative analysis in large, multi-site health-services research. Yet methodological guidance for LLM integration into qualitative analysis and evidence of their…

Computation and Language · Computer Science 2026-01-22 Sasha Ronaghi , Emma-Louise Aveling , Maria Levis , Rachel Lauren Ross , Emily Alsentzer , Sara Singer

Large language models (LLMs) are increasingly utilized by researchers across a wide range of domains, and qualitative social science is no exception; however, this adoption faces persistent challenges, including interpretive bias, low…

Computation and Language · Computer Science 2025-10-30 Ali Sanaei , Ali Rajabzadeh

Large language models (LLM) have revolutionized the processing of natural language. Although first benchmarks of the process modeling abilities of LLM are promising, it is currently under debate to what extent an LLM can generate good…

Computation and Language · Computer Science 2025-03-19 Peter Fettke , Constantin Houy

The rise of large language models (LLMs) has led many researchers to consider their usage for scientific work. Some have found benefits using LLMs to augment or automate aspects of their research pipeline, while others have urged caution…

Computation and Language · Computer Science 2024-11-11 Zhehui Liao , Maria Antoniak , Inyoung Cheong , Evie Yu-Yen Cheng , Ai-Heng Lee , Kyle Lo , Joseph Chee Chang , Amy X. Zhang

Building effective machine learning (ML) workflows to address complex tasks is a primary focus of the Automatic ML (AutoML) community and a critical step toward achieving artificial general intelligence (AGI). Recently, the integration of…

Machine Learning · Computer Science 2024-12-30 Yang Gu , Hengyu You , Jian Cao , Muran Yu , Haoran Fan , Shiyou Qian
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