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VLMs can achieve up to 36.95% higher accuracy in multi-image analytical reasoning tasks, outperforming GPT-4.1 by leveraging synthetic data and a novel reinforcement learning strategy.
Data referencing errors plague LLMs even in structured tasks, but a lightweight critic model can boost accuracy by up to 12%.
