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I will talk about the classification of multi-partite entanglement in random tensor networks (RTN) via multipartite contractions of density matrices. In particular I will focus on two such quantities: the reflected entropy/Markov gap, and the multi-entropy. I will demonstrate how the calculation of such quantities in RTN naturally corresponds to a combinatorial optimization problem, and thus allowing explicit calculation in the large