By minimizing NLL, the supervision signals in D may not sufficiently flow to GTMN, as GTMN is nested within response decoding.
besides NLL, we propose a state update loss that directly supervises the learning of GTMN with D. The idea is to minimize the distance between the ground truth status of meta-word expression and the status stored in the state memory panel.