Traditional approaches focus on aligning models during the instruction tuning orreinforcement learning stages, referred tointhis paperas'postalignment'.

Intensity,as defined in the classical temporal point process(TPP) sense, can be interpreted as the expected number of eventsz z0 withinthetimeinterval[t,t+dt].

Unlike most vision tasks that have per-sample ground-truth, image synthesis tasks target generating unseen data and hence are usually evaluated through a distributional distance between one set of real samples and another set of generated samples.

Partial monitoring (PM) is a general sequential decision-making problem with limited feedback ( Rus-tichini, 1999; Piccolboni and Schindelhauer, 2001).

In Section 4, we argue that there exists a discrepancy between over-smoothing based theoretical results and the practical capabilities of deep GCN models, demonstrating that over-smoothing is not the key factor that leads to the performance degradation in deeper GCNs.