What is the difference between multi-layer perceptron and generalized feed forward neural network?
Well you missed the diagram they provided for the GFNN. Here is the diagram from their page:



Clearly you can see what the GFNN does, unlike MLP the inputs are applied to the hidden layers also. While in MLP the only way information can travel to hidden layers is through previous layers, in GFNN the input information is directly available to the hidden layers.

I might add this type of connections are used in ResNet CNN, which increased its performance dramatically compared to other CNN architectures.