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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…

计算与语言 · 计算机科学 2024-11-11 Zhehui Liao , Maria Antoniak , Inyoung Cheong , Evie Yu-Yen Cheng , Ai-Heng Lee , Kyle Lo , Joseph Chee Chang , Amy X. Zhang

Large Language Models (LLMs) have shown capabilities close to human performance in various analytical tasks, leading researchers to use them for time and labor-intensive analyses. However, their capability to handle highly specialized and…

计算与语言 · 计算机科学 2024-10-08 Alexander S. Choi , Syeda Sabrina Akter , JP Singh , Antonios Anastasopoulos

Large Language Models(LLMs) have revolutionized various applications in natural language processing (NLP) by providing unprecedented text generation, translation, and comprehension capabilities. However, their widespread deployment has…

计算与语言 · 计算机科学 2024-09-26 Rajesh Ranjan , Shailja Gupta , Surya Narayan Singh

Large Language Models (LLMs) have shown powerful performance and development prospects and are widely deployed in the real world. However, LLMs can capture social biases from unprocessed training data and propagate the biases to downstream…

计算与语言 · 计算机科学 2024-02-22 Yingji Li , Mengnan Du , Rui Song , Xin Wang , Ying Wang

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…

计算与语言 · 计算机科学 2024-10-18 Humza Naveed , Asad Ullah Khan , Shi Qiu , Muhammad Saqib , Saeed Anwar , Muhammad Usman , Naveed Akhtar , Nick Barnes , Ajmal Mian

The pervasive spread of misinformation and disinformation in social media underscores the critical importance of detecting media bias. While robust Large Language Models (LLMs) have emerged as foundational tools for bias prediction,…

计算机与社会 · 计算机科学 2024-12-11 Luyang Lin , Lingzhi Wang , Jinsong Guo , Kam-Fai Wong

Large Language Models (LLMs) are increasingly used to generate and edit scientific abstracts, yet their integration into academic writing raises questions about trust, quality, and disclosure. Despite growing adoption, little is known about…

计算机与社会 · 计算机科学 2026-01-23 Nil-Jana Akpinar , Sandeep Avula , CJ Lee , Brandon Dang , Kaza Razat , Vanessa Murdock

Large language models (LLMs) are revolutionizing every aspect of society. They are increasingly used in problem-solving tasks to substitute human assessment and reasoning. LLMs are trained on what humans write and are thus exposed to human…

软件工程 · 计算机科学 2025-10-14 Fengfei Sun , Ningke Li , Kailong Wang , Lorenz Goette

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…

计算与语言 · 计算机科学 2025-06-24 Weixin Liang

Large language models (LLMs) have been positioned to revolutionize HCI, by reshaping not only the interfaces, design patterns, and sociotechnical systems that we study, but also the research practices we use. To-date, however, there has…

Large Language Models (LLMs) have emerged as powerful candidates to inform clinical decision-making processes. While these models play an increasingly prominent role in shaping the digital landscape, two growing concerns emerge in…

计算与语言 · 计算机科学 2024-04-24 Raphael Poulain , Hamed Fayyaz , Rahmatollah Beheshti

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

Research has shown that while large language models (LLMs) can generate their responses based on cultural context, they are not perfect and tend to generalize across cultures. However, when evaluating the cultural bias of a language…

计算与语言 · 计算机科学 2025-12-29 Vitthal Bhandari

Rapid advancements of large language models (LLMs) have enabled the processing, understanding, and generation of human-like text, with increasing integration into systems that touch our social sphere. Despite this success, these models can…

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…

Large Language Models (LLMs) represent a major step toward artificial general intelligence, significantly advancing our ability to interact with technology. While LLMs perform well on Natural Language Processing tasks -- such as…

计算与语言 · 计算机科学 2025-05-15 Brandon Smith , Mohamed Reda Bouadjenek , Tahsin Alamgir Kheya , Phillip Dawson , Sunil Aryal

Advancements in Large Language Models (LLMs) have increased the performance of different natural language understanding as well as generation tasks. Although LLMs have breached the state-of-the-art performance in various tasks, they often…

Large Language Models (LLMs) have made substantial progress in the past several months, shattering state-of-the-art benchmarks in many domains. This paper investigates LLMs' behavior with respect to gender stereotypes, a known issue for…

计算与语言 · 计算机科学 2023-08-30 Hadas Kotek , Rikker Dockum , David Q. Sun

There have been rapid advancements in the capabilities of large language models (LLMs) in recent years, greatly revolutionizing the field of natural language processing (NLP) and artificial intelligence (AI) to understand and interact with…

计算与语言 · 计算机科学 2024-09-26 Zeyneb N. Kaya , Souvick Ghosh

Large language models (LLMs) have rapidly become indispensable tools for acquiring information and supporting human decision-making. However, ensuring that these models uphold fairness across varied contexts is critical to their safe and…

计算机与社会 · 计算机科学 2026-03-05 Xulang Zhang , Rui Mao , Erik Cambria
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