Quantile smoothing splines provide nonparametric estimation of conditional quantile functions. Like other nonparametric smoothing techniques, the choice of smoothing parameters considerably affects the performance of quantile smoothing splines. The robust cross-validation (RCV) has been commonly used as a tuning criterion in practice. To explain its success, Oh et al. (J. Roy. Statist. Soc. Ser. A, in press) argued that the RCV curve, as a function of smoothing parameters in quantile smoothing splines, differs from the mean squared error (MSE) curve only by a constant. In this article, we consider an alternative loss function, the generalized comparative Kullback