Papers by Yuechan Li

1 papers
From Inheritance to Saturation: Disentangling the Evolution of Visual Redundancy for Architecture-Aware MLLM Inference Acceleration (2026.acl-long)

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Challenge: Existing acceleration strategies suffer from severe "backbone dependency" Existing strategies such as token pruning or layer sparsity suffer from this .
Approach: They propose a framework that decouples visual redundancy into IVR and architecture-dependent secondary saturation redundancies.
Outcome: The proposed framework outperforms existing frameworks on Qwen25-VL and Qwa25-LL.

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