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A paradigm shift is underway in Software Engineering, with AI systems such as LLMs playing an increasingly important role in boosting software development productivity. This trend is anticipated to persist. In the next years, we expect a…

软件工程 · 计算机科学 2026-03-27 Valerio Terragni , Annie Vella , Partha Roop , Kelly Blincoe

Survey research has a long-standing history of being a human-powered field, but one that embraces various technologies for the collection, processing, and analysis of various behavioral, political, and social outcomes of interest, among…

数字图书馆 · 计算机科学 2025-09-04 Trent D. Buskirk , Florian Keusch , Leah von der Heyde , Adam Eck

The advent of AI driven large language models (LLMs) have stirred discussions about their role in qualitative research. Some view these as tools to enrich human understanding, while others perceive them as threats to the core values of the…

软件工程 · 计算机科学 2023-06-26 Muneera Bano , Didar Zowghi , Jon Whittle

The rapid growth of Large Language Models (LLMs) has been a driving force in transforming various domains, reshaping the artificial general intelligence landscape. However, the increasing computational and memory demands of these models…

Large Language Models (LLMs) are changing the way we operate our society and will undoubtedly impact power systems as well - but how exactly? By integrating various data streams - including real-time grid data, market dynamics, and consumer…

计算机与社会 · 计算机科学 2025-04-15 Seyyedreza Madani , Ahmadreza Tavasoli , Zahra Khoshtarash Astaneh , Pierre-Olivier Pineau

Large Language Models (LLMs) have revolutionized the process of customer engagement, campaign optimization, and content generation, in marketing management. In this paper, we explore the transformative potential of LLMs along with the…

计算与语言 · 计算机科学 2025-01-22 Raha Aghaei , Ali A. Kiaei , Mahnaz Boush , Javad Vahidi , Mohammad Zavvar , Zeynab Barzegar , Mahan Rofoosheh

Large Language Models (LLMs) are the cornerstone in automating Requirements Engineering (RE) tasks, underpinning recent advancements in the field. Their pre-trained comprehension of natural language is pivotal for effectively tailoring them…

软件工程 · 计算机科学 2024-05-16 Andreas Vogelsang , Jannik Fischbach

Large language models (LLMs) have rapidly evolved from text generators into powerful problem solvers. Yet, many open tasks demand critical thinking, multi-source, and verifiable outputs, which are beyond single-shot prompting or standard…

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,…

人机交互 · 计算机科学 2025-10-13 Orcun Yildiz , Tom Peterka

Given the increasing demands in computer programming education and the rapid advancement of large language models (LLMs), LLMs play a critical role in programming education. This study provides a systematic review of selected empirical…

计算机与社会 · 计算机科学 2025-06-30 Meina Zhu , Lanyu Xu , Barbara Ericson

The rapid evolution of large language models (LLMs) and their capacity to simulate human cognition and behavior has given rise to LLM-based frameworks and tools that are evaluated and applied based on their ability to perform tasks…

计算与语言 · 计算机科学 2024-12-03 Jing Yi Wang , Nicholas Sukiennik , Tong Li , Weikang Su , Qianyue Hao , Jingbo Xu , Zihan Huang , Fengli Xu , Yong Li

Large Language Models (LLMs) have emerged as a transformative AI paradigm, profoundly influencing daily life through their exceptional language understanding and contextual generation capabilities. Despite their remarkable performance, LLMs…

This paper presents a detailed case study examining the application of Large Language Models (LLMs) in the construction of test cases within the context of software engineering. LLMs, characterized by their advanced natural language…

Large language models (LLMs) are rapidly changing learning processes, as they are readily available to students and quickly complete or augment several learning-related activities with non-trivial performance. Such major shifts in learning…

人机交互 · 计算机科学 2024-09-23 Rahul R. Divekar , Sophia Guerra , Lisette Gonzalez , Natasha Boos

This article examines the advantages and disadvantages of Large Language Models (LLMs) and Artificial Intelligence (AI) in research and education and proposes the urgent need for an international statement to guide their responsible use.…

其他定量生物学 · 定量生物学 2023-06-13 Ahmed S. BaHammam , Khaled Trabelsi , Seithikurippu R. Pandi-Perumal , Hiatham Jahrami

This paper explores the use of large language models (LLMs) as research tools in the history, philosophy, and sociology of science (HPSS). LLMs are remarkably effective at processing unstructured text and inferring meaning from context,…

计算与语言 · 计算机科学 2025-06-17 Arno Simons , Michael Zichert , Adrian Wüthrich

Adopting Large language models (LLMs) in organizations potentially revolutionizes our lives and work. However, they can generate off-topic, discriminating, or harmful content. This AI alignment problem often stems from misspecifications…

人工智能 · 计算机科学 2025-09-10 Sascha Kaltenpoth , Oliver Müller

Large Language Model (LLM) is changing the software development paradigm and has gained huge attention from both academia and industry. Researchers and developers collaboratively explore how to leverage the powerful problem-solving ability…

密码学与安全 · 计算机科学 2024-11-05 Qiang Hu , Xiaofei Xie , Sen Chen , Lei Ma

The rise of powerful large language models (LLMs) brings about tremendous opportunities for innovation but also looming risks for individuals and society at large. We have reached a pivotal moment for ensuring that LLMs and LLM-infused…

人机交互 · 计算机科学 2023-08-09 Q. Vera Liao , Jennifer Wortman Vaughan

Unmanned Aerial Vehicles (UAVs) have emerged as a transformative technology across diverse sectors, offering adaptable solutions to complex challenges in both military and civilian domains. Their expanding capabilities present a platform…

人工智能 · 计算机科学 2024-05-06 Shumaila Javaid , Nasir Saeed , Bin He
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