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Paper Proposes Exploration-Guided Prompt Scaffolding for Multimodal RL Post-Training
A new arXiv paper argues that training prompts in online reinforcement learning vary widely in how useful they are to the current policy, with some already solved and others too hard to give a dependable learning signal. The authors propose an exploration-guided prompt scaffolding method that selects or structures prompts for multimodal reinforcement post-training so rollouts are better spent. The work appears in both the cs.AI and cs.LG listings as arXiv:2609.15051v1.