2026
ENTROLLM: ENTROPY ENCODED WEIGHT COMPRESSION FOR EFFICIENT LARGE LANGUAGE MODEL INFERENCE ON EDGE DEVICES
ICASSP 2026poster
Large Language Models (LLMs) achieve strong performance across tasks, but face storage and compute challenges on edge devices. We propose EntroLLM, a compression framework combining mixed quantization and entropy coding to reduce storage while preserving accuracy. We use a combination of unsigned an…