Contrasting to CMN, the model generates the memory representations for each historical utterance using an embedding matrix B as used in equation 7, without sequential modeling.
for utterance u i , both memories are created as M λ using {m t λ = B.u t u t ∈ hist λ and t ∈ [1, K]} for λ ∈ {a, b}.