Accelerating Unified Multimodal Models with Core-Expansion Routing and Unified Computation Scheduling
CE-Router is proposed, which uses a task-shared core scorer and progress-conditioned generation expansions, optimized through generation decomposition and cross-task core alignment, and retains 98.03% of dense understanding performance with a 1.93-to-end inference speedup.
Wengyi Zhan, Chen-Qian Yan, Songwei Liu et al.
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