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cs.CV2026
VisionPulse: Dynamic Visual Sparsity for Efficient Multimodal Reasoning
Hengbo Xu, Shengjie Jin, Yanbiao Ma +1
With the rapid advancement of large multimodal models (LMMs), inference-time overhead has become a key bottleneck for real-world deployment. Existing methods typically prune visual…
cs.CV2024
Awaker2.5-VL: Stably Scaling MLLMs with Parameter-Efficient Mixture of Experts
Jinqiang Long, Yanqi Dai, Guoxing Yang +4
As the research of Multimodal Large Language Models (MLLMs) becomes popular, an advancing MLLM model is typically required to handle various textual and visual tasks (e.g., VQA, De…