Before revision:  The experimental results carried out in this paper evidence that SML allows to reduce drastically the number of trainable parameters while still achieving state-of-the-art performance .
After revision:  The experimental results carried out in this paper evidence that SML allows to reduce drastically the number of trainable parameters while still achieving state-of-the-art performance on common benchmarks. We make our code and dataset available at URL