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Found 5 papers, 3 papers with code
R2D2 at SemEval-2022 Task 5: Attention is only as good as its Values! A multimodal system for identifying misogynist memes
Our best performing system achieved an F1 score of 0. 757 and was ranked 3^{rd} in Subtask A.
R2D2 at SemEval-2022 Task 6: Are language models sarcastic enough? Finetuning pre-trained language models to identify sarcasm
Our model was ranked 7^{th} in Subtask B, 8^{th} in Subtask C (English), and performed well in Subtask A (English).
YoungSheldon at SemEval-2021 Task 5: Fine-tuning Pre-trained Language Models for Toxic Spans Detection using Token classification Objective
In this paper, we describe our system used for SemEval 2021 Task 5: Toxic Spans Detection.
YoungSheldon at SemEval-2021 Task 7: Fine-tuning Is All You Need
We used a simple fine-tuning approach using different Pre-trained Language Models (PLMs) to evaluate their performance for humor and offense detection.
Memebusters at SemEval-2020 Task 8: Feature Fusion Model for Sentiment Analysis on Memes Using Transfer Learning
Our model was ranked 5 in Subtask B and ranked 8 in Subtask C and performed nicely in Subtask A on the leader board.
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