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News/Multimodal Reward Hacking in Reinforcement Learning
arxiv
PublishedJuly 13, 2026 at 4:00 AM

Multimodal Reward Hacking in Reinforcement Learning

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arXiv:2607.09492v1 Announce Type: new Abstract: Reinforcement learning (RL) is increasingly used to align multimodal large language models (MLLMs), but higher rewards do not always imply better task performance. This risk is amplified when visual evidence is evaluated by text-only or weakly grounded

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