[R] ASVD: New Method for LLM Compression Yields Up to 20% Additional Weight Reduction

New Paper: ASVD: Activation-aware Singular Value Decomposition for Compressing Large Language Models

[https://arxiv.org/abs/2312.05821](https://arxiv.org/abs/2312.05821)

This research explores a novel paradigm aimed at reducing the memory footprint of large language models (LLMs) to facilitate their broader adoption in various computing environments. The challenges associated with traditional low-rank decomposition methods in LLM compression are examined, particularly their reliance on extensive training data and computational resources. In response to these limitations, a training-free approach is proposed, incorporating an innovative technique known as Activation-aware Singular …

adoption challenges compression computing environments language language models large language large language models llm llms low machinelearning memory novel paper paradigm research singular value