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相关论文: When Large Language Models are More PersuasiveThan…

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Large Language Models (LLMs) are already as persuasive as humans. However, we know very little about how they do it. This paper investigates the persuasion strategies of LLMs, comparing them with human-generated arguments. Using a dataset…

计算与语言 · 计算机科学 2024-04-23 Carlos Carrasco-Farre

The capabilities of large language models (LLMs) have raised concerns about their potential to create and propagate convincing narratives. Here, we study their performance in detecting convincing arguments to gain insights into LLMs'…

计算与语言 · 计算机科学 2024-10-07 Paula Rescala , Manoel Horta Ribeiro , Tiancheng Hu , Robert West

Large Language Models (LLMs) are increasingly regarded as having the potential to generate persuasive content at scale. While previous studies have focused on the risks associated with LLM-generated misinformation, the role of LLMs in…

计算机与社会 · 计算机科学 2026-04-06 John Caffier , Olga Stavrova , Bennett Kleinberg

Large language models (LLMs) possess strong persuasive capabilities that outperform humans in head-to-head comparisons. Users report consulting LLMs to inform major life decisions in relationships, medical settings, and when seeking…

人机交互 · 计算机科学 2026-04-28 Nalin Poungpeth , Nicholas Clark , Tanu Mitra

Large language models (LLMs) have demonstrated strong persuasive capabilities comparable to those of humans, offering promising benefits while raising societal concerns. However, systematically evaluating the persuasive capabilities of LLMs…

人工智能 · 计算机科学 2026-03-10 Zirui Cheng , Jiaxuan You

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 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

The rapid rise of Large Language Models (LLMs) has created new disruptive possibilities for persuasive communication, enabling fully-automated, personalized, and interactive content generation at an unprecedented scale. In this paper, we…

计算与语言 · 计算机科学 2026-04-22 Sander Noels , Alexander Rogiers , Maarten Buyl , Tijl De Bie

Large Language Models (LLMs) can generate content that is as persuasive as human-written text and appear capable of selectively producing deceptive outputs. These capabilities raise concerns about potential misuse and unintended…

计算与语言 · 计算机科学 2024-12-24 Cameron R. Jones , Benjamin K. Bergen

Large Language Models (LLMs) have started to demonstrate the ability to persuade humans, yet our understanding of how this dynamic transpires is limited. Recent work has used linear probes, lightweight tools for analyzing model…

计算与语言 · 计算机科学 2025-08-08 Brandon Jaipersaud , David Krueger , Ekdeep Singh Lubana

Large language models (LLMs) are increasingly used for persuasion, such as in political communication and marketing, where they affect how people think, choose, and act. Yet, empirical findings on the effectiveness of LLMs in persuasion…

人机交互 · 计算机科学 2025-12-02 Lukas Hölbling , Sebastian Maier , Stefan Feuerriegel

Warning: This research studies AI persuasion and bias amplification that could be misused; all experiments are for safety evaluation. Large Language Models (LLMs) now generate convincing, human-like text and are widely used in content…

计算与语言 · 计算机科学 2025-08-25 Saumya Roy

Large Language Models (LLMs) are effective at deceiving, when prompted to do so. But under what conditions do they deceive spontaneously? Models that demonstrate better performance on reasoning tasks are also better at prompted deception.…

计算与语言 · 计算机科学 2025-04-02 Samuel M. Taylor , Benjamin K. Bergen

Large language models (LLMs) have exploded in popularity in the past few years and have achieved undeniably impressive results on benchmarks as varied as question answering and text summarization. We provide a simple new prompting strategy…

计算与语言 · 计算机科学 2022-12-14 Joshua Albrecht , Ellie Kitanidis , Abraham J. Fetterman

Large Language Models (LLMs) have emerged as formidable instruments capable of comprehending and producing human-like text. This paper explores the potential of LLMs, to shape user perspectives and subsequently influence their decisions on…

人工智能 · 计算机科学 2024-09-04 Ganesh Prasath Ramani , Shirish Karande , Santhosh V , Yash Bhatia

Large language models (LLMs) have the potential to aid and improve human decision-making in classification tasks, not only by providing fairly accurate predictions, but also in their ability to generate cogent narrative explanations of…

人机交互 · 计算机科学 2026-05-25 Laura R. Marusich , Mary Grace Kozuch Dhooghe , Jonathan Z. Bakdash , Murat Kantarcioglu

Previous work has showcased the intriguing capabilities of Large Language Models (LLMs) in instruction-following and rhetorical fluency. However, systematic exploration of their dual capabilities to autonomously persuade and resist…

计算与语言 · 计算机科学 2025-06-10 Tianjie Ju , Yujia Chen , Hao Fei , Mong-Li Lee , Wynne Hsu , Pengzhou Cheng , Zongru Wu , Zhuosheng Zhang , Gongshen Liu

Large language models (LLMs) are excellent at maintaining high-level, convincing dialogue, but it remains unclear whether their persuasive success reflects genuine understanding of the discourse. We examine this question through informal…

计算与语言 · 计算机科学 2026-04-21 Adrian de Wynter , Tangming Yuan

Concerns persist regarding the capacity of Large Language Models (LLMs) to sway political views. Although prior research has claimed that LLMs are not more persuasive than standard political campaign practices, the recent rise of frontier…

计算与语言 · 计算机科学 2026-03-11 Zhongren Chen , Joshua Kalla , Quan Le

Deductive reasoning plays a pivotal role in the formulation of sound and cohesive arguments. It allows individuals to draw conclusions that logically follow, given the truth value of the information provided. Recent progress in the domain…

计算与语言 · 计算机科学 2024-06-04 Philipp Mondorf , Barbara Plank
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