Figure 1. Conceptual illustration. (a) Without priors, grounding
detectors trained with limited labels often ignore spatial/semantic
cues (e.g., “on the left”). (b) HeROD injects heuristic-inspired
reasoning priors (spatial + semantic), guiding the detector toward
correct localization and improving data-efficient learning.