arXiv cs.LG
· Papers
Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models
arXiv:2607.18280v1 Announce Type: new Abstract: Large language models (LLMs) are often compressed through static parameter pruning or dynamic token-level computation, yet aggressive sparsification can trigger rapid performance degradation beyond an essential sparsity boundary. This work asks emph{whether combining the