GA-SVD: Generation-aware Singular Value Decomposition for LLM Compression
GA-SVD is a low-rank compression method for large language models that improves performance over existing SVD methods by considering how the model generates text. It uses generation-aware whitening statistics derived from the model's own outputs to guide the compression process. This approach successfully preserves both generative and discriminative abilities, scaling effectively to models up to 70B parameters.