JIS University

Native Binary-Weight Training Outperforms Zero-Shot Sign Projection in MNIST Diffusion

Does severe failure after projecting a diffusion model to one-bit weights show that its binary representation is unusable? We test that implication, rather than propose a new quantizer, in a small MNIST residual U-Net. We compare floating-point training, zero-shot per-channel sig...