Matthew Staff refactored multimodal processor registration in the Blaizzy/mlx-vlm repository to decouple Torch dependencies for the qwen3_5 model and streamline processor integration for hunyuan_vl and kimi_vl. Using Python, he introduced an install_auto_processor_patch mechanism and registered Qwen3VLProcessor for qwen3_5, enabling deployment in environments with minimal Torch requirements. His work focused on dependency management and model integration, removing direct AutoImageProcessor and AutoProcessor registrations to improve modularity and startup performance. The targeted changes addressed deployment flexibility and maintainability, demonstrating a thoughtful approach to processor registration and dependency handling within the context of modern machine learning workflows.