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YNU-HPCC at SemEval-2022 Task 5: Multi-Modal and Multi-label Emotion Classification Based on LXMERT

Chaoran HanJin WangXuejie Zhang • @Lexical and Computational Semantics and Semantic Evaluation (formerly Workshop on Sense Evaluation) • 01 January 2022

TLDR: A multi-label emotion classification model based on pre-trained LXMERT is proposed based on Faster-RCNN to extract visual representation and utilize LXMert’s cross-attention for multi-modal alignment and the Bilinear-interaction layer to fuse these features.

Citations: 2
Abstract: This paper describes our system used in the SemEval-2022 Task5 Multimedia Automatic Misogyny Identification (MAMI). This task is to use the provided text-image pairs to classify emotions. In this paper, We propose a multi-label emotion classification model based on pre-trained LXMERT. We use Faster-RCNN to extract visual representation and utilize LXMERT’s cross-attention for multi-modal alignment. Then we use the Bilinear-interaction layer to fuse these features. Our experimental results surpass the F_1 score of baseline. For Sub-task A, our F_1 score is 0.662 and Sub-task B’s F_1 score is 0.633. The code of this study is available on GitHub.

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