New Compression Method SoLA Shrinks Large Language Models Without Retraining

Researchers unveiled SoLA, a training-free compression technique that reduces LLM size by 30% while improving performance compared to existing methods. The approach combines soft activation sparsity and low-rank decomposition to identify and retain critical components while compressing others, potentially making advanced AI models more accessible and affordable to deploy.