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[Project page](https://mj-bench.github.io/)
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Multimodal judges reward models play a pivotal role in Reinforcement Learning from Human Feedback (RLHF) and Reinforcement Learning from AI Feedback (RLAIF). They serve as judges, providing crucial feedback to align foundation models (FMs) with desired behaviors. However, the evaluation of these multimodal judges often lacks thoroughness, leading to potential misalignment and unsafe fine-tuning outcomes.
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[Project page](https://mj-bench.github.io/)
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Multimodal judges reward models play a pivotal role in Reinforcement Learning from Human Feedback (RLHF) and Reinforcement Learning from AI Feedback (RLAIF). They serve as judges, providing crucial feedback to align foundation models (FMs) with desired behaviors. However, the evaluation of these multimodal judges often lacks thoroughness, leading to potential misalignment and unsafe fine-tuning outcomes.
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