Reducing Redundancy in LLM Embeddings with Structured Spectral Factorization
Reducing redundancy in large language model (LLM) embeddings directly impacts your ability to optimize performance, cut costs, and improve scalability. Embeddings-numerical representations of text-often carry overlapping or unnecessary information that bloats model size and slows inference. For…
