arXiv AI August 19, 2026 By Huanhuan Ma, Haisong Gong, Xiaoyuan Yi, Xing Xie, Philip S. Yu, Dongkuan Xu

Beyond BFI: The CSI for Enhanced Reliability and Validity in Evaluating LLM Personality Traits

arXiv:2503. 20182v2 Announce Type: replace-cross Abstract: As large language models (LLMs) increasingly function as human-like assistants exhibiting human-like personality traits, understanding their behavioral characteristics becomes essential for responsible AI development.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

llms

arXiv AI

Jul 31

Measure what Matters: Psychometric Evaluation of AI with Situational Judgment Tests

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

llms benchmarks

arXiv AI

1d ago

A validity-guided workflow for robust large language model research in psychology

arXiv:2507. 04491v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are rapidly being integrated into psychological and behavioral research as research tools, evaluation targets, human simulators, and cognitive models.

By Zhicheng Lin

llms

arXiv AI

Jun 30

LLM-based Multimodal Personality Recognition via Facial Action Unit-Text Semantic Fusion

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

llms rag multimodal benchmarks safety

arXiv AI

Jun 30

LLM Agents Grounded in Self-Reports Enable General-Purpose Simulation of Individuals

arXiv:2411. 10109v3 Announce Type: replace Abstract: Machine learning can predict human behavior well when substantial structured data are available for well-defined outcomes.

By Joon Sung Park, Carolyn Q. Zou, Jonne Kamphorst, Niles Egan, Aaron Shaw, Benjamin Mako Hill, Carrie Cai, Meredith Ringel Morris, Percy Liang, Robb Willer, Michael S. Bernstein

llms agents benchmarks

arXiv AI

Aug 11

EMMR: Emotion-Mediated Multimodal Reasoning for Personality Assessment in Asynchronous Video Interviews

arXiv:2608. 07512v1 Announce Type: cross Abstract: Asynchronous Video Interviews (AVIs) have become increasingly popular for personality assessment.

By Dongsheng Hu, Tianyi Zhang, Chuang Liu, Yuan Zong Yong Li, Wenming Zheng, Xiu-xiu Zhan

llms multimodal

Hugging Face Trending Papers

Jun 29

LLM-based Multimodal Personality Recognition via Facial Action Unit-Text Semantic Fusion

Personality recognition in asynchronous video interviews (AVIs) has become increasingly important due to their widespread adoption in modern recruitment. Existing approaches often rely on large language models (LLMs) to analyze textual responses of interviewees in AVI.

llms rag multimodal benchmarks safety

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Measure what Matters: Psychometric Evaluation of AI with Situational Judgment Tests

A validity-guided workflow for robust large language model research in psychology

LLM-based Multimodal Personality Recognition via Facial Action Unit-Text Semantic Fusion

LLM Agents Grounded in Self-Reports Enable General-Purpose Simulation of Individuals

EMMR: Emotion-Mediated Multimodal Reasoning for Personality Assessment in Asynchronous Video Interviews

LLM-based Multimodal Personality Recognition via Facial Action Unit-Text Semantic Fusion