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P4Q: Co-designing Token Pruning and Quantization for Vision-Language Model Acceleration
Vision language models have achieved strong performance across a wide range of multimodal applications, yet their substantial computational and memory costs hinder efficient deployment. Visual token pruning and post-training quantization reduce inference overhead along two complementary dimensions,
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