  In this work, we perform a cosmological-model-independent test on the cosmic
distance duality relation (CDDR) by comparing the angular diameter distance
(ADD) obtained from the compact radio quasars (QSOs) with the luminosity
distance (LD) from the Pantheon Type Ia supernovae (SNIa) sample. The binning
method and Artificial Neural Network (ANN) are employed to match ADD data with
LD data at the same redshift, and three different parameterizations are adopted
to quantify the possible deviations from the CDDR. We initially investigate the
impacts of the specific prior values for the absolute magnitude $M_{\rm B}$
from SNIa and the linear size scaling factor $l$ from QSOs on the CDDR test,
demonstrating that these prior values introduce significant biases in the CDDR
test. To avoid the biases, we propose a method independent of $M_{\rm B}$ and
$l$ to test CDDR, which treats the fiducial value of a new variable
$\kappa\equiv10^{M_{\rm B} \over 5}\,l$ as a nuisance parameter and then
marginalize its impact with a flat prior in the statistical analysis. The
results show that the CDDR is consistent with the observational data, and QSOs
can serve as a powerful tool for testing the CDDR independent of cosmological
models.
