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相关论文: Emotional Manipulation Through Prompt Engineering …

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Online disinformation poses a global challenge, placing significant demands on fact-checkers who must verify claims efficiently to prevent the spread of false information. A major issue in this process is the redundant verification of…

计算与语言 · 计算机科学 2025-04-30 Ivan Vykopal , Martin Hyben , Robert Moro , Michal Gregor , Jakub Simko

The rapid spread of misinformation on online platforms undermines trust among individuals and hinders informed decision making. This paper shows an explainable and computationally efficient pipeline to detect misinformation using…

计算与语言 · 计算机科学 2025-10-23 Jainee Patel , Chintan Bhatt , Himani Trivedi , Thanh Thi Nguyen

Human communication is motivated: people speak, write, and create content with a particular communicative intent in mind. As a result, information that large language models (LLMs) and AI agents process is inherently framed by humans'…

计算与语言 · 计算机科学 2026-02-03 Addison J. Wu , Ryan Liu , Kerem Oktar , Theodore R. Sumers , Thomas L. Griffiths

Large Language Models (LLMs) are recruited in applications that span from clinical assistance and legal support to question answering and education. Their success in specialized tasks has led to the claim that they possess human-like…

计算与语言 · 计算机科学 2024-07-10 Vittoria Dentella , Fritz Guenther , Elliot Murphy , Gary Marcus , Evelina Leivada

Journalists are among the many users of large language models (LLMs). To better understand the journalist-AI interactions, we conduct a study of LLM usage by two news agencies through browsing the WildChat dataset, identifying candidate…

计算与语言 · 计算机科学 2024-12-04 Natalie Grace Brigham , Chongjiu Gao , Tadayoshi Kohno , Franziska Roesner , Niloofar Mireshghallah

Large Language Models (LLMs) have made significant advances in natural language processing, but their underlying mechanisms are often misunderstood. Despite exhibiting coherent answers and apparent reasoning behaviors, LLMs rely on…

计算与语言 · 计算机科学 2024-08-05 Bo Zhou , Daniel Geißler , Paul Lukowicz

Large Language Models (LLMs) are a double-edged sword capable of generating harmful misinformation -- inadvertently, or when prompted by "jailbreak" attacks that attempt to produce malicious outputs. LLMs could, with additional research, be…

计算与语言 · 计算机科学 2025-08-15 Ayana Hussain , Patrick Zhao , Nicholas Vincent

Large Language Models (LLMs) have become integral to a wide spectrum of applications, ranging from traditional computing tasks to advanced artificial intelligence (AI) applications. This widespread adoption has spurred extensive research…

计算与语言 · 计算机科学 2024-05-14 Xu Wang , Cheng Li , Yi Chang , Jindong Wang , Yuan Wu

The rapid spread of misinformation, further amplified by recent advances in generative AI, poses significant threats to society, impacting public opinion, democratic stability, and national security. Understanding and proactively assessing…

人工智能 · 计算机科学 2025-06-02 Sania Nayab , Marco Simoni , Giulio Rossolini

Large language models (LLMs) require well-crafted prompts for effective use. Prompt engineering, the process of designing prompts, is challenging, particularly for non-experts who are less familiar with AI technologies. While researchers…

人机交互 · 计算机科学 2024-01-29 Zijie J. Wang , Aishwarya Chakravarthy , David Munechika , Duen Horng Chau

Large Language Models (LLMs), such as ChatGPT, exhibit advanced capabilities in generating text, images, and videos. However, their effective use remains constrained by challenges in prompt formulation, personalization, and opaque…

人机交互 · 计算机科学 2025-03-04 Si Thu , A. Baki Kocaballi

In recent years, Large language models (LLMs) have garnered significant attention due to their superior performance in complex reasoning tasks. However, recent studies may diminish their reasoning capabilities markedly when problem…

计算与语言 · 计算机科学 2025-05-26 Ming Jiang , Tingting Huang , Biao Guo , Yao Lu , Feng Zhang

Recent advances in Large Language Models (LLMs) have incorporated planning and reasoning capabilities, enabling models to outline steps before execution and provide transparent reasoning paths. This enhancement has reduced errors in…

计算与语言 · 计算机科学 2025-01-31 Sudarshan Kamath Barkur , Sigurd Schacht , Johannes Scholl

Prompt engineering enables Large Language Models (LLMs) to perform a variety of tasks. However, lengthy prompts significantly increase computational complexity and economic costs. To address this issue, we study six prompt compression…

计算与语言 · 计算机科学 2025-05-02 Zheng Zhang , Jinyi Li , Yihuai Lan , Xiang Wang , Hao Wang

Empathetic dialogue is an indispensable part of building harmonious social relationships and contributes to the development of a helpful AI. Previous approaches are mainly based on fine small-scale language models. With the advent of…

计算与语言 · 计算机科学 2024-07-29 Yushan Qian , Wei-Nan Zhang , Ting Liu

Large Language Models (LLMs) have demonstrated impressive fluency and reasoning capabilities, but their potential for misuse has raised growing concern. In this paper, we present ScamAgent, an autonomous multi-turn agent built on top of…

密码学与安全 · 计算机科学 2026-01-15 Sanket Badhe

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

Large language models (LLMs) have gained human trust due to their capabilities and helpfulness. However, this in turn may allow LLMs to affect users' mindsets by manipulating language. It is termed as gaslighting, a psychological effect. In…

密码学与安全 · 计算机科学 2024-10-15 Wei Li , Luyao Zhu , Yang Song , Ruixi Lin , Rui Mao , Yang You

Prompt engineering has emerged as an indispensable technique for extending the capabilities of large language models (LLMs) and vision-language models (VLMs). This approach leverages task-specific instructions, known as prompts, to enhance…

人工智能 · 计算机科学 2025-03-18 Pranab Sahoo , Ayush Kumar Singh , Sriparna Saha , Vinija Jain , Samrat Mondal , Aman Chadha

Despite recent advancements in detecting disinformation generated by large language models (LLMs), current efforts overlook the ever-evolving nature of this disinformation. In this work, we investigate a challenging yet practical research…

计算与语言 · 计算机科学 2024-06-27 Bohan Jiang , Chengshuai Zhao , Zhen Tan , Huan Liu