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Large Language Models (LLMs) behave non-deterministically, and prompting has become a common method for steering their outputs. A popular strategy is to assign a persona to the model to produce more varied, context-sensitive responses,…

计算与语言 · 计算机科学 2026-04-21 Bruce W. Lee , Yeongheon Lee , Hyunsoo Cho

Large Language Models (LLMs) acting as artificial agents offer the potential for scalable behavioral research, yet their validity depends on whether LLMs can maintain stable personas across extended conversations. We address this point…

人机交互 · 计算机科学 2026-05-21 Jana Gonnermann-Müller , Jennifer Haase , Nicolas Leins , Thomas Kosch , Sebastian Pokutta

Student simulation with Large language models (LLMs) offers a scalable alternative for educational research and teacher training. Yet, its validity depends on whether models maintain stable personas across extended interactions. We test…

人机交互 · 计算机科学 2026-05-25 Jana Gonnermann-Müller , Jennifer Haase , Nicolas Leins , Thomas Kosch , Sebastian Pokutta

Large language models require consistent behavioral patterns for safe deployment, yet there are indications of large variability that may lead to an instable expression of personality traits in these models. We present PERSIST (PERsonality…

Large Language Models (LLM) technology is constantly improving towards human-like dialogue. Values are a basic driving force underlying human behavior, but little research has been done to study the values exhibited in text generated by…

计算与语言 · 计算机科学 2024-10-16 Naama Rozen , Liat Bezalel , Gal Elidan , Amir Globerson , Ella Daniel

Large language models (LLMs) are increasingly used as decision-support tools in data-constrained scientific workflows, where correctness and validity are critical. However, evaluation practices often emphasize stability or reproducibility…

机器学习 · 计算机科学 2026-03-18 Nazia Riasat

Personalized Large Language Models (LLMs) are increasingly used in diverse applications, where they are assigned a specific persona - such as a happy high school teacher - to guide their responses. While prior research has examined how well…

计算与语言 · 计算机科学 2025-09-10 Manon Reusens , Bart Baesens , David Jurgens

There has been extensive research on assessing the value orientation of Large Language Models (LLMs) as it can shape user experiences across demographic groups. However, several challenges remain. First, while the Multiple Choice Question…

计算与语言 · 计算机科学 2025-07-21 Siqi Shen , Mehar Singh , Lajanugen Logeswaran , Moontae Lee , Honglak Lee , Rada Mihalcea

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…

人工智能 · 计算机科学 2025-01-07 Bojana Bodroza , Bojana M. Dinic , Ljubisa Bojic

Large Language Models (LLMs) demonstrate a remarkable capacity to adopt different personas and roles; however, it remains unclear whether they can manifest behavior that adheres to a coherent, human-like value structure. In this work, we…

人工智能 · 计算机科学 2026-05-29 Asaf Yehudai , Naama Rozen , Ariel Gera

In this work, we conduct an analysis to examine the consistency of Large Language Models (LLMs) with respect to their own generated responses in an emotionally-driven conversational context. Specifically, the text generated by LLM is framed…

计算与语言 · 计算机科学 2026-05-08 Sneha Oram , Ojaswita Bhushan , Pushpak Bhattacharyya

Large Language Models (LLMs) have shown remarkable capabilities across various tasks, but their deployment in high-stake domains requires consistent and coherent behavior across multiple rounds of user interaction. This paper introduces a…

计算与语言 · 计算机科学 2025-07-08 Yubo Li , Yidi Miao , Xueying Ding , Ramayya Krishnan , Rema Padman

Large Language Models (LLMs) are often misleadingly recognized as having a personality or a set of values. We argue that an LLM can be seen as a superposition of perspectives with different values and personality traits. LLMs exhibit…

计算与语言 · 计算机科学 2023-11-08 Grgur Kovač , Masataka Sawayama , Rémy Portelas , Cédric Colas , Peter Ford Dominey , Pierre-Yves Oudeyer

Value trade-offs are an integral part of human decision-making and language use, however, current tools for interpreting such dynamic and multi-faceted notions of values in language models are limited. In cognitive science, so-called…

计算与语言 · 计算机科学 2026-03-03 Sonia K. Murthy , Rosie Zhao , Jennifer Hu , Sham Kakade , Markus Wulfmeier , Peng Qian , Tomer Ullman

Large Language Models (LLMs) are increasingly used to simulate human users in interactive settings such as therapy, education, and social role-play. While these simulations enable scalable training and evaluation of AI agents, off-the-shelf…

计算与语言 · 计算机科学 2025-11-04 Marwa Abdulhai , Ryan Cheng , Donovan Clay , Tim Althoff , Sergey Levine , Natasha Jaques

The rapid advancement of Large Language Models (LLMs) has attracted much attention to value alignment for their responsible development. However, how to define values in this context remains a largely unexplored question. Existing work…

计算与语言 · 计算机科学 2023-11-21 Jing Yao , Xiaoyuan Yi , Xiting Wang , Yifan Gong , Xing Xie

Persona-driven large language models (LLMs) require consistent behavioral tendencies across interactions to simulate human-like personality traits, such as persistence or reliability. However, current LLMs often lack stable internal…

计算与语言 · 计算机科学 2026-03-27 Yifan Luo , Kangping Xu , Yanzhen Lu , Yang Yuan , Andrew Chi-Chih Yao

Large Language Models (LLMs) have demonstrated human-like capabilities in language comprehension and generation, becoming active participants in social and cognitive domains. This study investigates whether LLMs exhibit personality-like…

计算与语言 · 计算机科学 2025-05-22 Wang Jiaqi , Wang bo , Guo fa , Cheng cheng , Yang li

Large language models (LLMs) appear to bias their survey answers toward certain values. Nonetheless, some argue that LLMs are too inconsistent to simulate particular values. Are they? To answer, we first define value consistency as the…

计算与语言 · 计算机科学 2024-10-03 Jared Moore , Tanvi Deshpande , Diyi Yang

Large Language Models (LLMs) often exhibit pronounced context-dependent variability that undermines predictable multi-agent behavior in tasks requiring strategic thinking. Focusing on models that range from 7 to 9 billion parameters in size…

多智能体系统 · 计算机科学 2026-02-09 Nunzio Lore , Babak Heydari
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