A bstract Using two benchmark models containing extended scalar sectors beyond the Standard Model, we study deep learning techniques to enhance the sensitivity of resonant triple Higgs boson searches in the fully hadronic 6 b channel, which suffers from the combinatorial challenge of reconstructing the Higgs bosons correctly from the multiple b -jets. More specifically, we employ the framework of Symmetry Preserving Attention Network (S pa -N et ), which takes into account the permutational symm