The paper introduces the Core Sentiment Inventory (CSI), a new personality trait evaluation tool for large language models (LLMs) that addresses reliability and validity issues found in existing methods like the Big Five Inventory (BFI). CSI is designed specifically for LLMs, supports both English and Chinese, and provides detailed psychological portraits of model behavior. Experiments show that CSI captures nuanced behavioral patterns, improves reliability, and correlates strongly (above 0.85) with real-world LLM outputs.
By Huanhuan Ma, Haisong Gong, Xiaoyuan Yi, Xing Xie, Philip S. Yu, Dongkuan Xu
arXiv:2609.00310v1 Announce Type: new
Abstract: Emotional labor is the effortful management of emotional displays to meet social or professional expectations. Personality traits have been correlated...
By Mohammad Saim, Tianyu Jiang
arXiv:2608. 16196v1 Announce Type: new Abstract: Personalized game generation requires inferring a player's abilities and behavioral style from how they play.
By Yifan Lu, Xiaopeng Yuan, Haohan Wang
arXiv:2510. 22170v3 Announce Type: replace Abstract: Persona conditioning is widely used to steer large language model (LLM) behavior, but it is unclear whether it induces stable behavioral structure or superficial variation.
By Alexandra Yost, Shreyans Jain, Shivam Raval, Grant Corser, Allen Roush, Nina Xu, Jacqueline Hammack, Ravid Shwartz-Ziv, Amirali Abdullah
arXiv:2606.11269v2 Announce Type: replace
Abstract: Personality assessment aims to infer stable traits from dynamic behaviors across modalities like language, voice, and facial expressions. Existing...
By Jia Li, Qian Chen, Wei Wang, Xinyu Li, Zhenzhen Hu, Dongsheng Shao, Richang Hong, Meng Wang
arXiv:2608. 06485v1 Announce Type: cross Abstract: Personality-conditioned LLM agents (PC-Agents) are increasingly used in emotional support, social simulation, and role-playing, motivating the development of lifelong agents that remain coherent over extended interactions.
By Ming Wang, Peidong Wang, Xiaocui Yang, Daling Wang, Shi Feng, Fiona Fui-Hoon Nah, Ee-Peng Lim
arXiv:2607. 07916v1 Announce Type: new Abstract: Large language models exhibit recurring behavioural patterns -- personas -- that shape generalisation and safety, but we lack reliable tools for decomposing, measuring, and controlling them.
By Luke Baines, Anton Gonzalvez Hawthorne, Mariia Koroliuk, Irakli Shalibashvili, Cl\'ement Dumas, Konstantinos Voudouris, David Demitri Africa
The paper presents a systematic MBTI analysis of open‑source large language models (LLMs) across various quantization levels, including mainstream 4‑bit and extreme 2‑bit settings. It examines how personality traits emerge layer‑by‑layer through entropy and confidence‑gap dynamics, and introduces Uncertainty‑Amplified Layer Decoding (UALD) to study decoding‑induced personality drift. Findings show that personality is not static but depends on layer, quantization, prompting, and decoding, with ENFJ traits dominating, 4‑bit quantization preserving coarse structure, and 2‑bit quantization disrupting fine‑grained consistency.
By Yao Fu, Lijia Huang, Xiaomin Li, Runchao Li, Yu Yin, Kenneth A. Loparo
arXiv:2603. 03915v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have shown remarkable potential in developing role-playing agents (RPAs).
By Ji-Lun Peng, Yun-Nung Chen
arXiv:2412.12144v5 Announce Type: replace-cross
Abstract: Personality assessment through situational judgment tests (SJTs) offers unique advantages over traditional Likert-type self-report scales, ye...
By Chang-Jin Li, Jiyuan Zhang, Yun Tang, Jian Li
LLM companions are deployed at scale in personally consequential settings, yet poorly evaluated. Existing benchmarks use hand-authored scenarios and prompted simulators, aggregate empathy into one score, and overlook judge biases such as same-family favoritism and scale drift.
arXiv:2606. 29900v1 Announce Type: cross Abstract: Personality recognition in asynchronous video interviews (AVIs) has become increasingly important due to their widespread adoption in modern recruitment.
By Tianyi Zhang, Wei Shan, Yuan Zong, Tianhua Qi, Wenming Zheng