RUBi: Reducing Unimodal Biases for Visual Question Answering
Table 4: Ablation study of the question-only loss LQO on VQA-CP v2.
['Model', 'L [ITALIC] QO', 'Overall', 'Yes/No', 'Number', 'Other']
The absence of LQO implies that the question-only classifier cq is never used, and nnq only receives gradients from the main loss LQM. Using LQO leads to consistent gains on all three architectures. We report a gain of +0.89 for our Baseline architecture, +0.22 for SAN, +4.76 for UpDn.