EMMR: Emotion-Mediated Multimodal Reasoning for Personality Assessment in Asynchronous Video Interviews
On the map: LLM reasoning → Audio-language model reasoning
Abstract (arXiv)
Asynchronous Video Interviews (AVIs) have become increasingly popular for personality assessment. Recent large language models (LLMs) have shown potential for personality assessment from transcribed interview responses. However, text-centered methods may overlook non-verbal behavioral cues conveyed through visual and audio modalities, even though such cues are highly relevant to personality assessment. In particular, emotion-related cues provide important social and affective evidence for understanding candidates' behavior related to personality traits. Thus, we propose EMMR (Emotion-Mediated Multimodal Reasoning), a two-stage framework for MLLMs-based personality assessment for AVIs. EMMR extracts emotion-related cues from multimodal interview data and incorporates them into personality assessment through structured reasoning as auxiliary social and behavioral evidence. Experiments on two AVIs datasets, OPVA and AVI-6, show that EMMR improves MAE, MSE, and PCC compared with baselines. Further analysis indicates that semantic descriptions of emotion cues enhance personality assessment, while their quality affects personality assessment reliability. These results suggest that integrating emotion-related cues into multimodal reasoning is a promising direction for more interpretable MLLMs-based personality assessment in AVIs.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Audio-language model reasoning, one of 17 directions in LLM reasoning. Builds on 7 of its 53 references that are in the map. First posted on arXiv 30 Jun 2026.
Builds on
7 of 53 references.
References · 7
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- 2025Kimi-VL Technical Reportcited by 381
- 2025Kimi-Audio Technical Reportcited by 210
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- 2025Emotion-Coherent Reasoning for Multimodal LLMs via Emotional Rationale Verifier
- 2023Personality-aware Human-centric Multimodal Reasoning: A New Task, Dataset and Baselines
- 2025EEmo-Bench: A Benchmark for Multi-modal Large Language Models on Image Evoked Emotion Assessment
- 2024Emotion-LLaMA: Multimodal Emotion Recognition and Reasoning with Instruction Tuning