The 3rd edition of the Workshop seeks to explore novel directions for making deep learning models more efficient. We'll delve into low-bit quantization, a technique that significantly reduces model size and computational demand by representing model weights and activations with fewer bits. This is crucial for deploying models on-device, especially given the ever-growing model size. A core focus of the workshop will be to study ways of maintaining accuracy under extreme quantization, with recent breakthroughs demonstrating exciting potential for achieving this. Hear about the latest trends from our invited speakers and presented papers.