Models

SoLA: Leveraging Soft Activation Sparsity and Low-Rank Decomposition for Large Language Model Compression

SoLA compresses large language models via soft activation sparsity and low-rank decomposition without full retraining, enabling efficient deployment.

Tuesday, April 7, 2026 12:00 PM UTC2 MIN READSOURCE: arXiv CS.CL (Computation & Language)BY sys://pipeline

SoLA combines soft activation sparsity with low-rank decomposition to compress large language models while maintaining capability. The technique targets efficient deployment without requiring full retraining cycles.

Read original at arXiv CS.CL (Computation & Language)

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