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Large Language Models (LLMs) have demonstrated remarkable capabilities, yet their transition to real-world applications reveals a critical limitation: the inability to adapt to individual preferences while maintaining alignment with…

Computation and Language · Computer Science 2025-05-06 Jian Guan , Junfei Wu , Jia-Nan Li , Chuanqi Cheng , Wei Wu

The advent of large language models (LLMs) has significantly advanced various fields, including natural language processing and automated dialogue systems. This paper explores the application of LLMs in psychological counseling, addressing…

Computation and Language · Computer Science 2024-06-21 Wenjie Li , Tianyu Sun , Kun Qian , Wenhong Wang

The recent surge of versatile large language models (LLMs) largely depends on aligning increasingly capable foundation models with human intentions by preference learning, enhancing LLMs with excellent applicability and effectiveness in a…

Computation and Language · Computer Science 2024-06-19 Ruili Jiang , Kehai Chen , Xuefeng Bai , Zhixuan He , Juntao Li , Muyun Yang , Tiejun Zhao , Liqiang Nie , Min Zhang

As Large Language Models (LLMs) continue to gain popularity due to their human-like traits and the intimacy they offer to users, their societal impact inevitably expands. This leads to the rising necessity for comprehensive studies to fully…

Artificial Intelligence · Computer Science 2025-01-07 Bojana Bodroza , Bojana M. Dinic , Ljubisa Bojic

Large Language Models (LLMs) have quickly become an invaluable assistant for a variety of tasks. However, their effectiveness is constrained by their ability to tailor responses to human preferences and behaviors via personalization. Prior…

Computation and Language · Computer Science 2024-11-21 Lucie Charlotte Magister , Katherine Metcalf , Yizhe Zhang , Maartje ter Hoeve

As LLMs become capable of complex tasks, there is growing potential for personalized interactions tailored to the subtle and idiosyncratic preferences of the user. We present a public benchmark, PersonalLLM, focusing on adapting LLMs to…

Machine Learning · Computer Science 2025-02-25 Thomas P. Zollo , Andrew Wei Tung Siah , Naimeng Ye , Ang Li , Hongseok Namkoong

We present a novel framework for designing emotionally agile robots with dynamic personalities and memory-based learning, with the aim of performing adaptive and non-deterministic interactions with humans while conforming to shared social…

Human-Computer Interaction · Computer Science 2025-03-25 Cheng Tang , Chao Tang , Steven Gong , Thomas M. Kwok , Yue Hu

Large language models (LLMs) have shown significant potential for robotics applications, particularly task planning, by harnessing their language comprehension and text generation capabilities. However, in applications such as household…

Robotics · Computer Science 2024-12-31 Dongge Han , Trevor McInroe , Adam Jelley , Stefano V. Albrecht , Peter Bell , Amos Storkey

This draft paper presents a workflow for creating User Personas with Large Language Models, using the results of a Thematic Analysis of qualitative interviews. The proposed workflow uses improved prompting and a larger pool of Themes,…

Human-Computer Interaction · Computer Science 2023-10-11 Stefano De Paoli

Large language models (LLMs) hold the potential to absorb and reflect personality traits and attitudes specified by users. In our study, we investigated this potential using robust psychometric measures. We adapted the most studied test in…

Computation and Language · Computer Science 2025-12-19 Anton Vasiliuk , Irina Abdullaeva , Polina Druzhinina , Anton Razzhigaev , Andrey Kuznetsov

Large Language Models (LLMs) are integral to applications such as conversational agents and content creation, where precise control over a model's personality is essential for maintaining tone, consistency, and user engagement. However,…

Computation and Language · Computer Science 2026-01-22 Seojin Hwang , Yumin Kim , Byeongjeong Kim , Donghoon Shin , Hwanhee Lee

Languages are shaped by the inductive biases of their users. Using a classical referential game, we investigate how artificial languages evolve when optimised for inductive biases in humans and large language models (LLMs) via Human-Human,…

Computation and Language · Computer Science 2025-05-29 Tom Kouwenhoven , Max Peeperkorn , Roy de Kleijn , Tessa Verhoef

A growing body of research examines personality traits in Large Language Models (LLMs), particularly in human-agent collaboration. Prior work has frequently applied the Big Five inventory to assess LLM behavior analogous to human…

Human-Computer Interaction · Computer Science 2026-03-20 Kim Zierahn , Cristina Cachero , Anna Korhonen , Nuria Oliver

The language generation and reasoning capabilities of large language models (LLMs) have enabled conversational systems with impressive performance in a variety of tasks, from code generation, to composing essays, to passing STEM and legal…

Artificial Intelligence · Computer Science 2025-02-28 Konstantina Christakopoulou , Iris Qu , John Canny , Andrew Goodridge , Cj Adams , Minmin Chen , Maja Matarić

Human cognition is constrained by processing limitations, leading to cognitive overload and inefficiencies in knowledge synthesis and decision-making. Large Language Models (LLMs) present an opportunity for cognitive augmentation, but their…

Human-Computer Interaction · Computer Science 2025-04-21 Xiangrong , Zhu , Yuan Xu , Tianjian Liu , Jingwei Sun , Yu Zhang , Xin Tong

Personalized large language models (LLMs) have attracted great attention in many applications, such as emotional support and role-playing. However, existing works primarily focus on modeling explicit character profiles, while ignoring the…

Computation and Language · Computer Science 2025-07-25 Yuhao Dan , Jie Zhou , Qin Chen , Junfeng Tian , Liang He

The rapid advancement of large language models (LLMs) has revolutionized role-playing, enabling the development of general role-playing models. However, current role-playing training has two significant issues: (I) Using a predefined role…

Computation and Language · Computer Science 2025-06-10 Yeyong Yu , Runsheng Yu , Haojie Wei , Zhanqiu Zhang , Quan Qian

Large Language Models (LLMs) are increasingly deployed in socially complex, interaction-driven tasks, yet their ability to mirror human behavior in emotionally and strategically complex contexts remains underexplored. This study assesses…

Computation and Language · Computer Science 2025-09-23 Deuksin Kwon , Kaleen Shrestha , Bin Han , Elena Hayoung Lee , Gale Lucas

Large Language Models (LLMs) are exhibiting emergent human-like abilities and are increasingly envisioned as the foundation for simulating an individual's communication style, behavioral tendencies, and personality traits. However, current…

Computation and Language · Computer Science 2025-10-31 Bangde Du , Minghao Guo , Songming He , Ziyi Ye , Xi Zhu , Weihang Su , Shuqi Zhu , Yujia Zhou , Yongfeng Zhang , Qingyao Ai , Yiqun Liu

Recent advances in Large Language Models (LLM) have led to a new class of autonomous agents, renewing and expanding interest in the area. LLM-powered Multiagent Systems (MAS) have thus emerged, both for assistive and simulation purposes,…

Multiagent Systems · Computer Science 2026-05-12 Paulo Salem , Robert Sim , Christopher Olsen , Prerit Saxena , Rafael Barcelos , Yi Ding
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