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This paper introduces PRISM, a four-stage data synthesis framework for training multimodal LLMs to follow prioritized rubrics, and PRISM-Eval, a judge-free evaluation suite. With only 10K samples, PRISM lifts Qwen3-VL-4B from 9.5% to 30.1% Strict accuracy on PRISM-Eval while preserving general benchmark performance, and gains transfer to other open-source MLLMs.