Through the Lens of Character: Resolving Modality-Role Interference in Multimodal Role-Playing Agent
The advancement of Multimodal Large Language Models (MLLMs) has expanded Role-Playing Agents (RPAs) into visually grounded environments. However, human vision is inherently subjective and identity-driven, whereas existing MLLMs extract objective, character-agnostic features for general tasks. In RPAs, this generic visual noise overpowers fragile character traits, causing Modality-Role Interference (MRI), where agents struggle to integrate visual grounding and character consistency. To address this, we introduce the training-free Character-Aware Visual Intervention (CAVI) framework, enabling agents to perceive the world through the lens of character. CAVI systematically targets MRI: macros...
| Authors | Yihong Tang, Kehai Chen, Xuefeng Bai et al. |
|---|---|
| Primary category | cs.CV |
| Published | 10 May 2026 |
| Last updated at source | 10 May 2026 |
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