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Large language models (LLMs) can reproduce a wide variety of rhetorical styles and generate text that expresses a broad spectrum of sentiments. This capacity, now available at low cost, makes them powerful tools for manipulation and…

社会与信息网络 · 计算机科学 2024-05-08 Yaqub Chaudhary , Jonnie Penn

We live in the era of Generative Artificial Intelligence (GenAI). Deepfakes and Large Language Models (LLMs) are two examples of GenAI. Deepfakes, in particular, pose an alarming threat to society as they are capable of spreading…

计算机与社会 · 计算机科学 2024-02-08 Alakananda Mitra , Saraju P. Mohanty , Elias Kougianos

Recent years have witnessed remarkable progress made in large language models (LLMs). Such advancements, while garnering significant attention, have concurrently elicited various concerns. The potential of these models is undeniably vast;…

计算与语言 · 计算机科学 2023-09-27 Tianhao Shen , Renren Jin , Yufei Huang , Chuang Liu , Weilong Dong , Zishan Guo , Xinwei Wu , Yan Liu , Deyi Xiong

There is growing interest in the use of Large Language Models (LLMs) in policing, but there are potential risks. We have developed a practical approach to identifying risks, grounded in the policing and legal system of England and Wales. We…

计算机与社会 · 计算机科学 2026-03-20 Muffy Calder , Marion Oswald , Elizabeth McClory-Tiarks , Michele Sevegnani , Evdoxia Taka

Large Language Models (LLMs) are advancing quickly and impacting people's lives for better or worse. In higher education, concerns have emerged such as students' misuse of LLMs and degraded education outcomes. To unpack the ethical concerns…

This study addresses critical gaps in Automated Essay Scoring (AES) systems and Large Language Models (LLMs) with regard to their ability to effectively identify and score harmful essays. Despite advancements in AES technology, current…

计算与语言 · 计算机科学 2026-01-12 Hongjin Kim , Jeonghyun Kang , Harksoo Kim

Model editing techniques are essential for efficiently updating knowledge in large language models (LLMs). However, the effectiveness of existing approaches degrades in massive editing scenarios, particularly when evaluated with practical…

计算与语言 · 计算机科学 2026-02-25 Yanbo Dai , Zhenlan Ji , Zongjie Li , Shuai Wang

Large Language Models (LLMs) represent a significant advancement in artificial intelligence, finding applications across various domains. However, their reliance on massive internet-sourced datasets for training brings notable privacy…

In-context knowledge editing (IKE) enables efficient modification of large language model (LLM) outputs without parameter changes and at zero-cost. However, it can be misused to manipulate responses opaquely, e.g., insert misinformation or…

计算与语言 · 计算机科学 2025-04-11 Paul Youssef , Zhixue Zhao , Jörg Schlötterer , Christin Seifert

Large Language Models (LLMs) are swiftly advancing in architecture and capability, and as they integrate more deeply into complex systems, the urgency to scrutinize their security properties grows. This paper surveys research in the…

计算与语言 · 计算机科学 2023-10-18 Erfan Shayegani , Md Abdullah Al Mamun , Yu Fu , Pedram Zaree , Yue Dong , Nael Abu-Ghazaleh

Large Language Models (LLMs) have revolutionized artificial intelligence and machine learning through their advanced text processing and generating capabilities. However, their widespread deployment has raised significant safety and…

密码学与安全 · 计算机科学 2024-12-03 Jing Cui , Yishi Xu , Zhewei Huang , Shuchang Zhou , Jianbin Jiao , Junge Zhang

Recent advancements in artificial intelligence (AI), particularly in large language models (LLMs), have unlocked significant potential to enhance the quality and efficiency of medical care. By introducing a novel way to interact with AI and…

Large Language Models (LLMs) are transforming mental health care by enhancing accessibility, personalization, and efficiency in therapeutic interventions. These AI-driven tools empower mental health professionals with real-time support,…

计算机与社会 · 计算机科学 2025-01-22 Hari Mohan Pandey

The last two years have seen a rapid growth in concerns around the safety of large language models (LLMs). Researchers and practitioners have met these concerns by creating an abundance of datasets for evaluating and improving LLM safety.…

计算与语言 · 计算机科学 2025-01-13 Paul Röttger , Fabio Pernisi , Bertie Vidgen , Dirk Hovy

The rapid development and deployment of large language models (LLMs) have introduced a new frontier in artificial intelligence, marked by unprecedented capabilities in natural language understanding and generation. However, the increasing…

Large language models (LLMs) show promise for supporting systematic reviews (SR), even complex tasks such as qualitative synthesis (QS). However, applying them to a stage that is unevenly reported and variably conducted carries important…

软件工程 · 计算机科学 2025-10-21 Sebastián Pizard , Ramiro Moreira , Federico Galiano , Ignacio Sastre , Lorena Etcheverry

Knowledge editing aims to change language models' performance on several special cases (i.e., editing scope) by infusing the corresponding expected knowledge into them. With the recent advancements in large language models (LLMs), knowledge…

计算与语言 · 计算机科学 2024-05-31 Jiaan Wang , Yunlong Liang , Zengkui Sun , Yuxuan Cao , Jiarong Xu , Fandong Meng

LLMs(Large Language Models) nowadays have widespread adoption as a tool for solving issues across various domain/tasks. These models since are susceptible to produce harmful or toxic results, inference-time adversarial attacks, therefore…

计算与语言 · 计算机科学 2024-10-01 Sachin Kumar

As large language models (LLMs) have been deployed in various real-world settings, concerns about the harm they may propagate have grown. Various jailbreaking techniques have been developed to expose the vulnerabilities of these models and…

计算与语言 · 计算机科学 2025-02-19 Yubin Ge , Neeraja Kirtane , Hao Peng , Dilek Hakkani-Tür

While large language models (LLMs) present significant potential for supporting numerous real-world applications and delivering positive social impacts, they still face significant challenges in terms of the inherent risk of privacy…

人工智能 · 计算机科学 2025-01-17 Huandong Wang , Wenjie Fu , Yingzhou Tang , Zhilong Chen , Yuxi Huang , Jinghua Piao , Chen Gao , Fengli Xu , Tao Jiang , Yong Li