2025
SeedLM: Compressing LLM Weights into Seeds of Pseudo-Random Generators
ICLR 2025poster
Large Language Models (LLMs) have transformed natural language processing, but face significant challenges in widespread deployment due to their high runtime cost. In this paper, we introduce SeedLM, a novel post-training compression method that uses seeds of a pseudo-random generator to encode and…