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A main goal of Argument Mining (AM) is to analyze an author's stance. Unlikeprevious AM datasets focusing only on text, the shared task at the 10thWorkshop on Argument Mining introduces a dataset including both text andimages. Importantly, these images contain both visual elements and opticalcharacters. Our new framework, TILFA (A Unified Framework for Text, Image, andLayout Fusion in Argument Mining), is designed to handle this mixed data. Itexcels at not only understanding text but also detecting optical characters andrecognizing layout details in images. Our model significantly outperformsexisting baselines, earning our team, KnowComp, the 1st place in theleaderboard of Argumentative Stance Classification subtask in this shared task.

TILFA: A Unified Framework for Text, Image, and Layout Fusion in Argument Mining