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相关论文: Characteristic AI Agents via Large Language Models

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Context: Manual qualitative data analysis is time-intensive and can compromise validity and replicability, affecting analysis design, implementation, and reporting. Large Language Models (LLMs) enable human-bot collaboration in Software…

This survey explores the burgeoning field of role-playing with language models, focusing on their development from early persona-based models to advanced character-driven simulations facilitated by Large Language Models (LLMs). Initially…

人工智能 · 计算机科学 2025-01-13 Nuo Chen , Yan Wang , Yang Deng , Jia Li

Large language models (LLMs) are increasingly deployed as autonomous agents, yet evaluations focus primarily on task success rather than cultural appropriateness or evaluator reliability. We introduce LiveCultureBench, a multi-cultural,…

人工智能 · 计算机科学 2026-03-03 Viet-Thanh Pham , Lizhen Qu , Thuy-Trang Vu , Gholamreza Haffari , Dinh Phung

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

The advances made by Large Language Models (LLMs) have led to the pursuit of LLM agents that can solve intricate, multi-step reasoning tasks. As with any research pursuit, benchmarking and evaluation are key corner stones to efficient and…

Multi-agent large language models (MA-LLMs) are a rapidly growing research area that leverages multiple interacting language agents to tackle complex tasks, outperforming single-agent large language models. This literature review…

多智能体系统 · 计算机科学 2025-06-03 Arne Tillmann

Large Language Models (LLMs) are increasingly used in everyday life and research. One of the most common use cases is conversational interactions, enabled by the language generation capabilities of LLMs. Just as between two humans, a…

计算与语言 · 计算机科学 2024-11-12 Jingyao Zheng , Xian Wang , Simo Hosio , Xiaoxian Xu , Lik-Hang Lee

The emergence of Generative AI (Gen AI) and Large Language Models (LLMs) has enabled more advanced chatbots capable of human-like interactions. However, these conversational agents introduce a broader set of operational risks that extend…

密码学与安全 · 计算机科学 2025-05-09 Pedro Pinacho-Davidson , Fernando Gutierrez , Pablo Zapata , Rodolfo Vergara , Pablo Aqueveque

Agent-Based Modelling (ABM) has emerged as an essential tool for simulating social networks, encompassing diverse phenomena such as information dissemination, influence dynamics, and community formation. However, manually configuring varied…

Computational experiments have emerged as a valuable method for studying complex systems, involving the algorithmization of counterfactuals. However, accurately representing real social systems in Agent-based Modeling (ABM) is challenging…

人工智能 · 计算机科学 2024-02-02 Qun Ma , Xiao Xue , Deyu Zhou , Xiangning Yu , Donghua Liu , Xuwen Zhang , Zihan Zhao , Yifan Shen , Peilin Ji , Juanjuan Li , Gang Wang , Wanpeng Ma

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

Large Language Models (LLMs) have the potential to fundamentally change the way people engage in computer programming. Agent-based modeling (ABM) has become ubiquitous in natural and social sciences and education, yet no prior studies have…

人机交互 · 计算机科学 2024-02-02 John Chen , Xi Lu , Michael Rejtig , David Du , Ruth Bagley , Michael S. Horn , Uri J. Wilensky

Large language models (LLMs) are increasingly used in human-AI interaction research and practice, yet existing capability and safety benchmarks reveal little about the value priorities these systems express or how those priorities…

人工智能 · 计算机科学 2026-05-19 Gabriel Rongyang Lau , Wei Yan Low , Seow Min Koh , Fiona Fui-Hoon Nah , Andree Hartanto

The impressive capabilities of Large Language Models (LLMs) raise the possibility that synthetic agents can serve as substitutes for real participants in human-subject research. To evaluate this claim, prior research has largely focused on…

Generative Artificial Intelligence is set to revolutionize healthcare delivery by transforming traditional patient care into a more personalized, efficient, and proactive process. Chatbots, serving as interactive conversational models, will…

Large-language models (LLMs) hold significant promise in improving human-robot interaction, offering advanced conversational skills and versatility in managing diverse, open-ended user requests in various tasks and domains. Despite the…

机器人学 · 计算机科学 2024-01-09 Callie Y. Kim , Christine P. Lee , Bilge Mutlu

Objective: This study aims to develop and validate an evaluation framework to ensure the safety and reliability of mental health chatbots, which are increasingly popular due to their accessibility, human-like interactions, and context-aware…

While Large Language Model (LLM)-based agents can be used to create highly engaging interactive applications through prompting personality traits and contextual data, effectively assessing their personalities has proven challenging. This…

人机交互 · 计算机科学 2025-10-29 Eswari Jayakumar , Niladri Sekhar Dash , Debasmita Mukherjee

Recently, the fast development of Large Language Models (LLMs) such as ChatGPT has significantly advanced NLP tasks by enhancing the capabilities of conversational models. However, the application of LLMs in the recommendation domain has…

信息检索 · 计算机科学 2023-08-24 Junling Liu , Chao Liu , Peilin Zhou , Qichen Ye , Dading Chong , Kang Zhou , Yueqi Xie , Yuwei Cao , Shoujin Wang , Chenyu You , Philip S. Yu

The literature and multiple experts point to many potential risks from large language models (LLMs), but there are still very few direct measurements of the actual harms posed. AI risk assessment has so far focused on measuring the models'…

人工智能 · 计算机科学 2025-03-11 Malcolm Murray , Henry Papadatos , Otter Quarks , Pierre-François Gimenez , Simeon Campos