In this regard, we propose a novel memory mechanism that represents past events in human language.

Our proposed formulation for neuron calibration is lightweight and applicable to general feed-forward neural networks-based models.

Sentence scoring aims at measuring the likelihood score of a sentence and is widely usedinnatural language processing scenarios, likereranking, which isto select the best sentence from multiple candidates.

Compared totheexisting sampling-based approaches, which are inapplicable to the infinite time horizon setting, wetrain aseparate deterministic neural networkthatservesasaninfinite timehorizon safety certificate.