arXiv Computer Vision
PETR: Prompt Ensembling with Training-free Routing for Vision-Language Models
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An Effective Router for Vision-Language Model Selection
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Pretrain Once, Route Anywhere: Towards a Foundation Model for LLM Routing
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ReLope: KL-Regularized LoRA Probes for Multimodal LLM Routing
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AdaVSkip: Adaptive Visual Token Skipping Across Layers For Efficient MLLMs Inference
arXiv:2609.15131v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) require substantial computation to process numerous visual tokens across all transformer layers. Most method...
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Self-Routing: Parameter-Free Expert Routing from Hidden States
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arXiv Computer Vision
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Beyond One-Size-Fits-All: Sample-Adaptive Strategy Routing for Vision Token Pruning in MLLMs
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