We propose a novel alignment mechanism to deal with procedural reasoning on a newly released multimodal QA dataset, named RecipeQA. Our model is solving the textual cloze task which is a reading comprehension on a recipe containing images and instructions. We exploit the power of attention networks, cross-modal representations, and a latent alignment space between instructions and candidate answers to solve the problem. We introduce constrained max-pooling which refines the max-pooling operation on the alignment matrix to impose disjoint constraints among the outputs of the model. Our evaluation result indicates a 19\% improvement over the baselines.
@article{arxiv.2101.04727,
title = {Latent Alignment of Procedural Concepts in Multimodal Recipes},
author = {Hossein Rajaby Faghihi and Roshanak Mirzaee and Sudarshan Paliwal and Parisa Kordjamshidi},
journal= {arXiv preprint arXiv:2101.04727},
year = {2021}
}