A 22-dataset benchmark compares existing multimodal AutoML tricks, and an automatic ensemble of those tricks achieves the most robust performance.
SemEval-2021 Task 6: Detection of Persuasion Techniques in Texts and Images
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abstract
We describe SemEval-2021 task 6 on Detection of Persuasion Techniques in Texts and Images: the data, the annotation guidelines, the evaluation setup, the results, and the participating systems. The task focused on memes and had three subtasks: (i) detecting the techniques in the text, (ii) detecting the text spans where the techniques are used, and (iii) detecting techniques in the entire meme, i.e., both in the text and in the image. It was a popular task, attracting 71 registrations, and 22 teams that eventually made an official submission on the test set. The evaluation results for the third subtask confirmed the importance of both modalities, the text and the image. Moreover, some teams reported benefits when not just combining the two modalities, e.g., by using early or late fusion, but rather modeling the interaction between them in a joint model.
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Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data
A 22-dataset benchmark compares existing multimodal AutoML tricks, and an automatic ensemble of those tricks achieves the most robust performance.