knowledge, this was the transformer-based framework with
the highest TC on Touchdown preceding our work. ORAR
(ResNet 4th-to-last) [31] is from work published shortly be-
fore the completion of this research and uses two types of
features to attain highest TC in prior work. Standalone Vi-
sualBERT models are evaluated in two versions with 4 and
8 layers and attention heads. A stronger performance by the
smaller version indicates that adding self-attention layers is
unlikely to improve VLN predictions. This is further sup-
ported by the closely matched results for the VLN Trans-
APriorityMapforVision-and-LanguageNavigation withTrajectoryPlansandFeature-LocationCues