AINeutralarXiv – CS AI · 7h ago6/10
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Boosting RL-Based Visual Reasoning with Selective Adversarial Entropy Intervention
Researchers propose Selective-adversarial Entropy Intervention (SaEI), a novel method that improves reinforcement learning-based visual reasoning in vision-language models by strategically introducing adversarial perturbations to visual inputs during RL sampling. The technique combines entropy-guided adversarial sampling with token-selective entropy computation to enhance policy exploration without compromising the models' factual knowledge.