The Cherenkov Telescope Array Observatory (CTAO) is an international observatory currently
under construction, which will consist of two sites (one in the Northern Hemisphere and one in the
Southern Hemisphere). It will eventually be the largest and most sensitive ground-based gamma-
ray observatory. In the meantime, a small subarray composed of four Large-Sized Telescopes
(LSTs) at the Northern site will begin collecting data in the coming year. In preparation, we
present a stereoscopic event reconstruction using graph neural networks (GNNs) to combine
information from several telescopes of this subarray. In our previous work, we explored the use of
GNNs for the stereoscopic reconstruction of gamma-ray events on simulated data from the Prod5
sample and showed that GNNs provide a better stereoscopic reconstruction. We now compare this
approach to the currently foreseen method that analytically combines the output of monoscopic
random forests, and explore how GNNs can be used in fusion with the Random forest algorithm
in order to provide a more sensitive stereoscopic system.