arXiv Computer Vision

Traits Run Deeper: Trait-Specific Asymmetric Fusion for Personality Assessment

arXiv Computer Vision
Sep 21

Traits Run Deeper: Trait-Specific Asymmetric Fusion for Multimodal Personality Assessment

Traits Run Deeper introduces a personality assessment framework that tailors multimodal fusion to each trait dimension. It comprises a Multimodal Foundation Representation module that uses psychology-informed semantic templates, a Trait-Specific Modality Fusion module that asymmetrically fuses modalities to reduce cross‑modal interference, and a Distribution‑Calibrated Personality Regression module that corrects label imbalance. The approach achieves a ~25% reduction in mean squared error on the AVI Challenge 2026 validation set and wins the Personality Assessment Track.

By Jia Li, Qian Chen, Wei Wang, Xinyu Li, Zhenzhen Hu, Dongsheng Shao, Richang Hong, Meng Wang
arXiv AI
Jun 11

Frozen Multimodal Embeddings for Personality and Cognitive Ability Assessment in Asynchronous Video Interviews

arXiv:2606. 11930v1 Announce Type: cross Abstract: Predicting psychological traits from asynchronous video interviews (AVIs) is a challenging multimodal learning problem because labeled datasets are limited while each response contains high-dimensional visual, acoustic, and verbal signals.

By Kuo-En Hung, Hung-Yue Suen, Shih-Ching Yeh, Hsiang-Wen Wang
arXiv AI
Jun 12

Frozen Multimodal Embeddings for AI-Assisted Interview Assessment of Personality and Cognitive Ability

arXiv:2606. 11930v2 Announce Type: replace-cross Abstract: Predicting psychological traits from asynchronous video interviews (AVIs) is a challenging problem in AI-assisted interview assessment because labeled datasets are limited while each response contains high-dimensional visual, acoustic, and verbal signals.

By Kuo-En Hung, Hung-Yue Suen, Shih-Ching Yeh, Hsiang-Wen Wang
arXiv AI
Jun 10

Modeling Complex Behaviors: Multi-Personality Composition and Dynamic Switching in Vision-Language Models

arXiv:2606. 11074v1 Announce Type: cross Abstract: With the widespread deployment of Multimodal Large Language Models (MLLMs) in social interaction, understanding and controlling their behavior under complex personality conditions is essential.

By Peiqi Jia (Xi'an Jiaotong University), Haonan Jia (Beihang University), Ziqi Miao (Beihang University), Linkang Du (Xi'an Jiaotong University), Yuntao Wang (Xi'an Jiaotong University), Zhou Su (Xi'an Jiaotong University)
arXiv Computer Vision
Sep 17

Face-voice Association across LAnguages and Gender (FLAG) 2027 Challenge Evaluation Plan

arXiv:2609.17913v1 Announce Type: new Abstract: Face--voice association models may rely on language or gender cues in the voice rather than on speaker-specific voice characteristics, which can lead t...

By Marta Moscati, Swapnil Khandoker, Muhammad Saad Saeed, Shah Nawaz, Fatima Noor, Rohan Kumar Das, Mubashir Noman, Junaid Mir, Muhammad Haroon Yousaf, Khalid Malik, Markus Schedl