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This study explores how the Large Language Models (LLMs) adjust linguistic features to create personalized persuasive outputs. While research showed that LLMs personalize outputs, a gap remains in understanding the linguistic features of…

Large Language Models (LLMs) have significantly improved personalized conversational capabilities. However, existing datasets like Persona Chat, Synthetic Persona Chat, and Blended Skill Talk rely on static, predefined personas. This…

计算与语言 · 计算机科学 2024-12-17 Sayantan Pal , Souvik Das , Rohini K. Srihari

Large Language Models (LLMs) can be conditioned with explicit personality prompts, yet their behavioral realization often varies depending on context. This study examines how identical personality prompts lead to distinct linguistic,…

计算与语言 · 计算机科学 2026-02-03 Bin Han , Deuksin Kwon , Jonathan Gratch

Large Language Models (LLMs) have recently demonstrated impressive capabilities across various real-world applications. However, due to the current text-in-text-out paradigm, it remains challenging for LLMs to handle dynamic and complex…

人工智能 · 计算机科学 2024-10-25 Timothy Wei , Annabelle Miin , Anastasia Miin

Recent studies have shown that prompting can enable large language models (LLMs) to simulate specific personality traits and produce behaviors that align with those traits. However, there is limited understanding of how these simulated…

计算与语言 · 计算机科学 2026-01-06 Nuo Chen , Hanpei Fang , Piaohong Wang , Jiqun Liu , Tetsuya Sakai , Xiao-Ming Wu

Large language models (LLMs) are increasingly being used in human-centered social scientific tasks, such as data annotation, synthetic data creation, and engaging in dialog. However, these tasks are highly subjective and dependent on human…

Large language models (LLMs) offer emerging opportunities for psychological and behavioral research, but methodological guidance is lacking. This article provides a framework for using LLMs as psychological simulators across two primary…

计算机与社会 · 计算机科学 2026-04-07 Zhicheng Lin

Large Language Models (LLMs) have demonstrated exceptional capabilities in solving various tasks, progressively evolving into general-purpose assistants. The increasing integration of LLMs into society has sparked interest in whether they…

计算与语言 · 计算机科学 2025-10-20 Yuan Li , Yue Huang , Hongyi Wang , Ying Cheng , Xiangliang Zhang , James Zou , Lichao Sun

This paper explores the advancements in making large language models (LLMs) more human-like. We focus on techniques that enhance natural language understanding, conversational coherence, and emotional intelligence in AI systems. The study…

计算与语言 · 计算机科学 2026-02-03 Ethem Yağız Çalık , Talha Rüzgar Akkuş

A long-standing challenge in developing accurate recommendation models is simulating user behavior, mainly due to the complex and stochastic nature of user interactions. Towards this, one promising line of work has been the use of Large…

信息检索 · 计算机科学 2025-09-15 Himanshu Thakur , Eshani Agrawal , Smruthi Mukund

The ongoing revolution in language modeling has led to various novel applications, some of which rely on the emerging social abilities of large language models (LLMs). Already, many turn to the new cyber friends for advice during the…

计算机与社会 · 计算机科学 2025-08-05 Ivan Zakazov , Mikolaj Boronski , Lorenzo Drudi , Robert West

The capabilities of Large Language Models (LLMs) are limited to some extent by pre-training, so some researchers optimize LLMs through post-training. Existing post-training strategies, such as memory-based retrieval or preference…

计算与语言 · 计算机科学 2025-07-22 Haoran Sun , Zekun Zhang , Shaoning Zeng

Humans shift between different personas depending on social context. Large Language Models (LLMs) demonstrate a similar flexibility in adopting different personas and behaviors. Existing approaches, however, typically adapt such behavior…

计算与语言 · 计算机科学 2026-02-10 Ruimeng Ye , Zihan Wang , Zinan Ling , Yang Xiao , Manling Li , Xiaolong Ma , Bo Hui

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

Personality is a crucial factor that shapes human communication patterns, thereby regulating the personalities of large language models (LLMs) holds significant potential in enhancing their user experiences. Previous approaches either…

计算与语言 · 计算机科学 2025-09-10 Tianlong Li , Wenhao Liu , Muling Wu , Shihan Dou , Zhenghua Wang , Changze Lv , Xiaohua Wang , Xiaoqing Zheng , Xuanjing Huang

Recent advances in large language models (LLMs) have enabled human-like social simulations at unprecedented scale and fidelity, offering new opportunities for computational social science. A key challenge, however, is the construction of…

计算与语言 · 计算机科学 2025-10-07 Zhengyu Hu , Jianxun Lian , Zheyuan Xiao , Max Xiong , Yuxuan Lei , Tianfu Wang , Kaize Ding , Ziang Xiao , Nicholas Jing Yuan , Xing Xie

Psychological assessment tools have long helped humans understand behavioural patterns. While Large Language Models (LLMs) can generate content comparable to that of humans, we explore whether they exhibit personality traits. To this end,…

计算与语言 · 计算机科学 2025-02-11 Pranav Bhandari , Usman Naseem , Amitava Datta , Nicolas Fay , Mehwish Nasim

Large Language Models (LLMs) have demonstrated promising capabilities to generate responses that simulate consistent personality traits. Despite the major attempts to analyze personality expression through output-based evaluations, little…

计算与语言 · 计算机科学 2025-07-30 Tianjie Ju , Zhenyu Shao , Bowen Wang , Yujia Chen , Zhuosheng Zhang , Hao Fei , Mong-Li Lee , Wynne Hsu , Sufeng Duan , Gongshen Liu

Large language models (LLMs) increasingly serve as interactive social agents, yet their ability to maintain coherent and authentic persona-level role-playing remains limited, particularly in realistic social scenarios. Existing research…

人工智能 · 计算机科学 2026-05-19 Wenlong Shi , Jianxun Lian , Mingqi Wu , Haiming Qin , Mingyang Zhou , Xing Xie , Naipeng Chao , Hao Liao

Large language models have emerged as a promising approach towards achieving general-purpose AI agents. The thriving open-source LLM community has greatly accelerated the development of agents that support human-machine dialogue interaction…

计算机视觉与模式识别 · 计算机科学 2023-11-07 Zhenfei Yin , Jiong Wang , Jianjian Cao , Zhelun Shi , Dingning Liu , Mukai Li , Lu Sheng , Lei Bai , Xiaoshui Huang , Zhiyong Wang , Jing Shao , Wanli Ouyang