Deep Exemplar Networks for VQA and VQG
TABLE XIX: VQG-COCO-dataset, Analysis of different number of Exemplars for addition model, hadamard model and joint model, R is random exemplar. All these experiment are for the differential image network. k=5 performs the best and hence we use this value for the results in main paper.
['[BOLD] Meth', '[BOLD] Exemplar', '[BOLD] BLEU-1', '[BOLD] Meteor', '[BOLD] Rouge', '[BOLD] CIDer']
We had similar concerns and validated this point by using random exemplars for the nearest neighbor for MDN. In this case, the method is similar to the baseline. This suggests that with random exemplar, the model learns to ignore the cue.