forward-forward-algorithm

This paper introduces a learnable channel-class assignment mechanism for forward-only convolutional neural networks, combined with entropy and orthogonality regularization and a loss-aware layer contribution strategy. The method achieves state-of-the-art performance among forward-forward algorithms on CIFAR-10, CIFAR-100, and Tiny-ImageNet, significantly narrowing the gap with backpropagation.