For the top-n accuracy, where n equals the number of beams, we observe that increasing either the number of images or the number of beams consistently increases the accuracy. Notably, with a beam size of 3 and 3 image inputs, the model achieves an impressive 80.3% accuracy, a significant improvement compared to 62.0%.