I don’t find the paper suspicious. I believe it conveys a nice property of, “Almost all the time, if you give me a network, I can point you to a subnetwork that is capable of giving comparable accuracies”.
It is true that even though we call it a compression, it is still allocated in the memory as Zero and the shape is retained but it is more of an implementation flaw rather than the result it is trying to convey. As I mentioned earlier the result, “Almost all the time, if you give me a network, I can point you to a subnetwork that is capable of giving comparable accuracies” is loud and clear.
Also, by freezing weights, we are freezing it to zero, potentially removing that neuron, hence it starts to act like a new network altogether.
I think it’s a fascinating paper and the following follow-up papers of the Lottery Ticket Hypothesis will help you understand my fascination.

Stabilizing the Lottery Ticket Hypothesis 3
Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask 4