VeriEvol Decouples Prompt Difficulty and Answer Reliability for Visual Math RL
June 21, 2026
VeriEvol addresses reward label degradation when scaling RL for visual mathematical reasoning by separating prompt difficulty evolution from answer verification via offline hypothesis-test falsification. Type-aware evolution operators rewrite low-difficulty image-question seeds into harder, image-grounded prompts before any policy update.
HOW THIS AFFECTS YOU
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researcherThe decoupled verifiable data-construction approach is directly applicable to any multimodal RL pipeline where reward label noise becomes a bottleneck at scale.