I would have thought if their description is shit then their results are shit too (cherry-picked from hundreds of runs, outright fabricated, misinterpreted, incorrectly graphed, whatever - just plain doesn't work, like a bad recipe.)
As a followup if this is the case then how do you know what new deep learning research is worth your time to implement?
