  Differentiable programming opens exciting new avenues in particle physics,
also affecting future event generators. These new techniques boost the
performance of current and planned MadGraph implementations. Combining
phase-space mappings with a set of very small learnable flow elements,
MadNIS-Lite, can improve the sampling efficiency while being physically
interpretable. This defines a third sampling strategy, complementing VEGAS and
the full MadNIS.
