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The increasing sophistication of large language models (LLMs) has sparked growing concerns regarding their potential role in exacerbating ideological polarization through the automated generation of persuasive and biased content. This study…

计算与语言 · 计算机科学 2025-06-18 . Pazzaglia , V. Vendetti , L. D. Comencini , F. Deriu , V. Modugno

Large language models (LLMs) distinguish themselves from previous technologies by functioning as collaborative ``thought partners,'' capable of engaging more fluidly in natural language on a range of tasks. As LLMs increasingly influence…

Large language models (LLMs) provide a new way to build chatbots by accepting natural language prompts. Yet, it is unclear how to design prompts to power chatbots to carry on naturalistic conversations while pursuing a given goal, such as…

人机交互 · 计算机科学 2024-05-08 Jing Wei , Sungdong Kim , Hyunhoon Jung , Young-Ho Kim

There is widespread optimism that frontier Large Language Models (LLMs) and LLM-augmented systems have the potential to rapidly accelerate scientific discovery across disciplines. Today, many benchmarks exist to measure LLM knowledge and…

The remarkable advancements in Large Language Models (LLMs) have revolutionized the content generation process in social media, offering significant convenience in writing tasks. However, existing applications, such as sentence completion…

社会与信息网络 · 计算机科学 2025-05-06 Yuying Zhao , Yu Wang , Xueqi Cheng , Anne Marie Tumlin , Yunchao Liu , Damin Xia , Meng Jiang , Tyler Derr

Significant advancements have occurred in the application of Large Language Models (LLMs) for social simulations. Despite this, their abilities to perform teaming in task-oriented social events are underexplored. Such capabilities are…

人工智能 · 计算机科学 2025-08-18 Yuan Li , Lichao Sun , Yixuan Zhang

Recent advancements in large language models (LLMs) have shown promise in generating psychotherapeutic dialogues, particularly in the context of motivational interviewing (MI). However, the inherent lack of transparency in LLM outputs…

计算与语言 · 计算机科学 2024-12-18 Xin Sun , Xiao Tang , Abdallah El Ali , Zhuying Li , Pengjie Ren , Jan de Wit , Jiahuan Pei , Jos A. Bosch

The advancement of large language models (LLMs) has outpaced traditional evaluation methodologies. This progress presents novel challenges, such as measuring human-like psychological constructs, moving beyond static and task-specific…

计算与语言 · 计算机科学 2026-03-12 Haoran Ye , Jing Jin , Yuhang Xie , Xin Zhang , Guojie Song

As large language models (LLMs) become increasingly capable of generating persuasive content, understanding their effectiveness across different advertising strategies becomes critical. This paper presents a two-part investigation examining…

计算机与社会 · 计算机科学 2025-12-04 Elyas Meguellati , Stefano Civelli , Lei Han , Abraham Bernstein , Shazia Sadiq , Gianluca Demartini

While existing benchmarks probe the reasoning abilities of large language models (LLMs) across diverse domains, they predominantly assess passive reasoning, providing models with all the information needed to reach a solution. By contrast,…

机器学习 · 计算机科学 2025-06-11 Zhanke Zhou , Xiao Feng , Zhaocheng Zhu , Jiangchao Yao , Sanmi Koyejo , Bo Han

Large Language Models (LLMs) have shown remarkable promise in communicating with humans. Their potential use as artificial partners with humans in sociological experiments involving conversation is an exciting prospect. But how viable is…

人工智能 · 计算机科学 2025-02-04 James Flamino , Mohammed Shahid Modi , Boleslaw K. Szymanski , Brendan Cross , Colton Mikolajczyk

Modern AI progress has been driven by ML methods that are generalizable across settings and scalable to larger regimes. As large language models demonstrate advanced capabilities in reasoning, coding, and engineering tasks, it is…

As large language models (LLMs) are increasingly used for work, personal, and therapeutic purposes, researchers have begun to investigate these models' implicit and explicit moral views. Previous work, however, focuses on asking LLMs to…

计算机与社会 · 计算机科学 2025-03-25 Andrew J. Peterson

Artificial Intelligence (AI) is increasingly being integrated into scientific research, particularly in the social sciences, where understanding human behavior is critical. Large Language Models (LLMs) have shown promise in replicating…

计算与语言 · 计算机科学 2025-06-23 Ziyan Cui , Ning Li , Huaikang Zhou

Psychological consultation is essential for improving mental health and well-being, yet challenges such as the shortage of qualified professionals and scalability issues limit its accessibility. To address these challenges, we explore the…

计算与语言 · 计算机科学 2024-08-30 Rafael Souza , Jia-Hao Lim , Alexander Davis

The widespread adoption of large language models (LLMs) such as ChatGPT, Gemini, and DeepSeek has significantly changed how people approach tasks in education, professional work, and creative domains. This paper investigates how the…

人机交互 · 计算机科学 2025-08-29 Rizal Khoirul Anam

The rise of Generative AI, and Large Language Models (LLMs) in particular, is fundamentally changing cognitive processes in knowledge work, raising critical questions about their impact on human reasoning and problem-solving capabilities.…

人机交互 · 计算机科学 2025-04-04 Joshua Holstein , Moritz Diener , Philipp Spitzer

The proliferation of large language models (LLMs) and autonomous AI agents has raised concerns about their potential for automated persuasion and social influence. While existing research has explored isolated instances of LLM-based…

We investigate whether large language models (LLMs) can generate effective, user-facing explanations from a mathematically interpretable recommendation model. The model is based on constrained matrix factorization, where user types are…

人工智能 · 计算机科学 2025-10-02 Maxime Manderlier , Fabian Lecron , Olivier Vu Thanh , Nicolas Gillis

Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) have ushered in a new era of AI capabilities, demonstrating near-human-level performance across diverse scenarios. While numerous benchmarks (e.g., MMLU) and…

人工智能 · 计算机科学 2025-09-03 Kangyu Wang , Hongliang He , Lin Liu , Ruiqi Liang , Zhenzhong Lan , Jianguo Li