Modeling Complex Behaviors: Multi-Personality Composition and Dynamic Switching in Vision-Language Models
With the widespread deployment of Multimodal Large Language Models (MLLMs) in social interaction, understanding and controlling their behavior under complex personality conditions is essential. This paper introduces explicit personality conditioning and establishes a systematic evaluation framework encompassing single-personality induction, multi-personality induction, and personality switching. Experiments show that personality induction improves image captioning performance but can impair performance on tasks requiring precise reasoning, such as visual question answering (VQA). Balancing and residual effects are observed during multi-trait composition and dynamic switching, indicating t...
| Authors | Peiqi Jia, Haonan Jia, Ziqi Miao et al. |
|---|---|
| Primary category | cs.CL |
| Published | 9 June 2026 |
| Last updated at source | 10 June 2026 |
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