Relative Kinetic Utility: Calibrating Cross-Layer Credit for Global Structured LLM Pruning
Global structured pruning requires channels from different layers to compete under a shared sparsity budget, raising two coupled challenges: identifying which channels should be retained and making their scores comparable across layers. Raw channel scores can contain block-common scale that leaves within-block ordering unchanged but distorts model-wide competition. Our experiment indicates that similar layer-wise allocations can retain substantially different FFN channels, so layer allocation alone does not determine channel identity. Motivated by this separation, we introduce Global Relative Kinetic Utility (Global RKU), a label-free criterion that separates channel importance estimation...
| Authors | Tianhao Qian, Guilin Qi, Jiayu Chen |
|---|---|
| Primary category | cs.LG |
| Published | 9 May 2026 |
| Last updated at source | 29 September 2026 |
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