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Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models

arXiv cs.LG · 2d ago Cached

This paper introduces a compound sparsity framework for LLMs that combines static parameter pruning with dynamic token-level computation, showing that mixing both mechanisms outperforms single-dimension compression and delays performance degradation.

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