arXiv AI
Do MLLMs Really See It: Reinforcing Visual Attention in Multimodal LLMs
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Reinforcing Multimodal Reasoning via Token-Level Perception-Grounded Advantage Estimation
arXiv:2609.39168v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has improved the reasoning capabilities of Multimodal Large Language Models (MLLMs), yet existing...
arXiv AI
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Skip the Talk, Re-Focus on Vision: Latent Reasoning for Reasoning Segmentation in Multimodal Large Language Models
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arXiv AI
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Think with Structured Grounding: Perceptual Reinforcement Learning for Chart and Visual-Tabular Understanding
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arXiv AI
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Balancing Efficiency and Efficacy: Training-Free Attention-Guided Switching Between Explicit and Latent Thoughts for MLLMs
arXiv:2608. 03450v1 Announce Type: cross Abstract: Reasoning in Multimodal Large Language Models (MLLMs) requires both fine-grained visual perception and rigorous logical deduction.