Papers › Latent Alignment of Procedural Concepts in Multimodal Recipes
Latent Alignment of Procedural Concepts in Multimodal Recipes
Hossein Rajaby Faghihi, Roshanak Mirzaee, Sudarshan Paliwal, Parisa Kordjamshidi
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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Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Question Answering | RecipeQA | multimodal+LXMERT+ConstrainedMaxPooling | Accuracy | 0.475 | #1 of 1 | Archive leaderboard | report |
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