AINeutralarXiv – CS AI · May 16/10
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PRISM: Pre-alignment via Black-box On-policy Distillation for Multimodal Reinforcement Learning
Researchers introduce PRISM, a three-stage training pipeline that addresses distributional drift in large multimodal models by inserting a distribution-alignment stage between supervised fine-tuning and reinforcement learning. The method uses a Mixture-of-Experts discriminator to correct perception and reasoning errors, achieving 4.4-6.0 percentage point improvements on multimodal benchmarks compared to standard SFT-to-RLVR approaches.
🧠 Gemini