Multimodal Understanding

Fast-dDrive: Efficient Block-Diffusion VLM for Autonomous Driving
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Fast-dDrive: Efficient Block-Diffusion VLM for Autonomous Driving
Fast-dVLM: Efficient Block-Diffusion VLM via Direct Conversion from Autoregressive VLM
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Fast-dVLM: Efficient Block-Diffusion VLM via Direct Conversion from Autoregressive VLM
Cross-modal Identity Mapping: Minimizing Information Loss in Modality Conversion via Reinforcement Learning
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Cross-modal Identity Mapping: Minimizing Information Loss in Modality Conversion via Reinforcement Learning
INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling
Hallucinations in large vision-language models (LVLMs) pose significant challenges for real-world applications, as LVLMs may generate …
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INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling
Diagnosing the Compositional Knowledge of Vision Language Models from a Game-Theoretic View
Compositional reasoning capabilities are usually considered as fundamental skills to characterize human perception. Recent studies show …
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Diagnosing the Compositional Knowledge of Vision Language Models from a Game-Theoretic View