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cs.AI2026
STAR: SpatioTemporal Adaptive Reward Allocation for Text-to-Image RL Post-Training
Jinjie Shen, Wei Deng, Xian Hu +2
Existing RL post-training methods for text-to-image generation usually convert the final-image reward into a single scalar advantage and apply it with the same strength to the enti…
cs.AI2026
Teaching the Way, Not the Answer: Privileged Tutoring Distillation for Multimodal Policy Optimization
Shizhe Xiang, Ke An, Wenlong Yu +5
Recent post-training methods, particularly Reinforcement Learning with Verifiable Rewards (RLVR), have significantly enhanced the reasoning ability of Large Vision-Language Models…
cs.AI2026
EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models
Yiyang Fang, Wenke Huang, Pei Fu +5
Multimodal Large Language Models (MLLMs) have shown remarkable progress in visual reasoning and understanding tasks but still struggle to capture the complexity and subjectivity of…