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相关论文: LLM Safety for Children

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Large Language Models (LLMs) are increasingly embedded in child-facing contexts such as education, companionship, creative tools, but their deployment raises safety, privacy, developmental, and security risks. We conduct a systematic…

计算机与社会 · 计算机科学 2026-05-26 Junfeng Jiao , Saleh Afroogh , Kevin Chen , Abhejay Murali , David Atkinson , Amit Dhurandhar

As Large Language Models (LLMs) increasingly power applications used by children and adolescents, ensuring safe and age-appropriate interactions has become an urgent ethical imperative. Despite progress in AI safety, current evaluations…

计算机与社会 · 计算机科学 2026-05-26 Junfeng Jiao , Saleh Afroogh , Kevin Chen , Abhejay Murali , David Atkinson , Amit Dhurandhar

Large Language Models (LLMs) are increasingly used to control robotic systems such as drones, but their risks of causing physical threats and harm in real-world applications remain unexplored. Our study addresses the critical gap in…

机器学习 · 计算机科学 2026-02-20 Yung-Chen Tang , Pin-Yu Chen , Tsung-Yi Ho

Large Language Models (LLMs) are rapidly entering children's lives - through parent-driven adoption, schools, and peer networks - yet current AI ethics and safety research do not adequately address content-related risks specific to minors.…

计算与语言 · 计算机科学 2025-03-14 Shaun Khoo , Gabriel Chua , Rachel Shong

Current safety alignment for Large Language Models (LLMs) implicitly optimizes for a "modal adult user," leaving models vulnerable to distributional shifts in user cognition. We present ChildSafe, a benchmark that quantifies alignment…

计算机与社会 · 计算机科学 2026-01-21 Abhejay Murali , Saleh Afroogh , Kevin Chen , David Atkinson , Amit Dhurandhar , Junfeng Jiao

The rapid proliferation of large language models (LLMs) in applications targeting children and adolescents necessitates a fundamental reassessment of prevailing AI safety frameworks, which are largely tailored to adult users and neglect the…

计算与语言 · 计算机科学 2025-12-16 Wenpeng Xing , Lanyi Wei , Haixiao Hu , Jingyi Yu , Rongchang Li , Mohan Li , Changting Lin , Meng Han

Large Language Models (LLMs) are transforming education by enabling personalization, feedback, and knowledge access, while also raising concerns about risks to students and learning systems. Yet empirical evidence on these risks remains…

计算机与社会 · 计算机科学 2025-11-04 Iris Delikoura , Yi. R Fung , Pan Hui

Attracted by the impressive power of Multimodal Large Language Models (MLLMs), the public is increasingly utilizing them to improve the efficiency of daily work. Nonetheless, the vulnerabilities of MLLMs to unsafe instructions bring huge…

计算机视觉与模式识别 · 计算机科学 2024-06-21 Xin Liu , Yichen Zhu , Yunshi Lan , Chao Yang , Yu Qiao

Large language models (LLMs) have significantly transformed the landscape of Natural Language Processing (NLP). Their impact extends across a diverse spectrum of tasks, revolutionizing how we approach language understanding and generations.…

密码学与安全 · 计算机科学 2025-06-13 Sara Abdali , Richard Anarfi , CJ Barberan , Jia He , Erfan Shayegani

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…

This paper presents a systematic evaluation of Large Language Models' (LLMs) behavior on long-tail distributed (encrypted) texts and their safety implications. We introduce a two-dimensional framework for assessing LLM safety: (1)…

计算与语言 · 计算机科学 2025-06-05 Utsav Maskey , Mark Dras , Usman Naseem

Children increasingly have access to Large Language Models (LLMs), which may expose them to responses that are developmentally inappropriate or require age-sensitive safety, guidance, and boundaries. Existing LLM safety evaluations largely…

计算与语言 · 计算机科学 2026-05-27 Samee Arif , Angana Borah , Rada Mihalcea

In recent years, Large Language Models (LLMs) have garnered considerable attention for their remarkable abilities in natural language processing tasks. However, their widespread adoption has raised concerns pertaining to trust and safety.…

人工智能 · 计算机科学 2025-07-01 Doohee You , Dan Chon

Large Language Models (LLMs) are now commonplace in conversation applications. However, their risks of misuse for generating harmful responses have raised serious societal concerns and spurred recent research on LLM conversation safety.…

计算与语言 · 计算机科学 2024-03-28 Zhichen Dong , Zhanhui Zhou , Chao Yang , Jing Shao , Yu Qiao

Large Language Models have seen rapid progress in capability in recent years; this progress has been accelerating and their capabilities, measured by various benchmarks, are beginning to approach those of humans. There is a strong demand to…

计算与语言 · 计算机科学 2023-12-07 Brett Israelsen , Soumalya Sarkar

Spurred by the recent rapid increase in the development and distribution of large language models (LLMs) across industry and academia, much recent work has drawn attention to safety- and security-related threats and vulnerabilities of LLMs,…

计算与语言 · 计算机科学 2023-08-25 Maximilian Mozes , Xuanli He , Bennett Kleinberg , Lewis D. Griffin

Background Large language models (LLMs) are increasingly deployed in medical consultations, yet their safety under realistic user pressures remains understudied. Prior assessments focused on neutral conditions, overlooking vulnerabilities…

计算与语言 · 计算机科学 2026-01-16 Vahideh Zolfaghari

Large Language Models (LLMs) represent an advanced evolution of earlier, simpler language models. They boast enhanced abilities to handle complex language patterns and generate coherent text, images, audios, and videos. Furthermore, they…

密码学与安全 · 计算机科学 2024-03-01 Jun Huang , Jiawei Zhang , Qi Wang , Weihong Han , Yanchun Zhang

Large Language Models (LLMs) have demonstrated extraordinary capabilities and contributed to multiple fields, such as generating and summarizing text, language translation, and question-answering. Nowadays, LLM is becoming a very popular…

计算与语言 · 计算机科学 2024-11-18 Badhan Chandra Das , M. Hadi Amini , Yanzhao Wu

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
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