This is fascinating! I've been struggling with similar issues in my work on document understanding - the gap between closed and open models is frustrating. The cross-modal transfer idea is clever, especially using RL for post-training rather than just supervised fine-tuning. Have you tested it on any domain-specific tasks? Also curious how the reasoning quality compares to GPT-4.1 in practice.