Calibrating Attention-Based Token Pruning for Efficient Multi-Image Synthesis in UMMs
Unified Multimodal Models (UMMs) enable powerful multi-image synthesis but incur substantial computation from long visual contexts. While token pruning offers a direct route to accelerating inference, existing methods are primarily adapted from understanding tasks, suffering from insufficient reference image exploratio...