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Latent Alignment of Procedural Concepts in Multimodal Recipes

2021-01-12WS 2020Code Available0· sign in to hype

Hossein Rajaby Faghihi, Roshanak Mirzaee, Sudarshan Paliwal, Parisa Kordjamshidi

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Abstract

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.

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Benchmark Results

DatasetModelMetricClaimedVerifiedStatus
RecipeQAmultimodal+LXMERT+ConstrainedMaxPoolingAccuracy0.48Unverified

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