The Sponza Atrium is illuminated by extremely narrow directional illumination. In this scene, radiance-driven path-guiding approaches shine, with the bidirectionally trained GMMs by Vorba et al.  performing the best. The SDTree by Müller et al.  struggles with the extremely sparse unidirectional samples in this scene, performing the worst among the radiance-based path-guiding approaches. Training with the same sparse unidirectional samples, our neural path guiding (NPG-Radiance) performs surprisingly well at equal sample counts; almost as well as the bidirectionally trained GMMs. Incorporating the product (NPG-Product) only offers minor per-sample improvements over the GMMs. Primary-sample-space path-sampling techniques offer little to no benefit over unidirectional path tracing with our NPS slightly outperforming PSSPS [Guo et al. 2018] with an equal number of samples.