arXiv cs.AI
· Papers
When Compression Scores Cannot Decide: Information Boundaries for Group-Robust LLM Pruning
arXiv:2608.02940v1 Announce Type: new Abstract: A reproducible compression statistic can still select the wrong candidate. A dense pruning score with 0.906 split-half reliability predicted a 16.1% gain. Its selected endpoint was 6.0% and 7.7% worse than two controls. We model the gap through information interfaces that