Counterfactual VQA: A Cause-Effect Look at Language Bias
Table 6: Ablations of (1) baseline models (SAN, UpDn and S-MRL), (2) fusion strategies (RUBi, Harmonic, Sum) on VQA-CP v2 test split using the simplified VQA causal graph. We reimplement the baselines for fair comparison.
['UpDn', 'All', 'Y/N', 'Num.', 'Other']
Similar to the results using the complete causal graph, CF-VQA achieves significant improvement for different baseline VQA architectures and fusion strategies.