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arXiv · 2007.10820

IITK at SemEval-2020 Task 10: Transformers for Emphasis Selection

Vipul Singhal·Sahil Dhull·Rishabh Agarwal·Ashutosh Modi
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Abstract

This paper describes the system proposed for addressing the research problem posed in Task 10 of SemEval-2020: Emphasis Selection For Written Text in Visual Media. We propose an end-to-end model that takes as input the text and corresponding to each word gives the probability of the word to be emphasized. Our results show that transformer-based models are particularly effective in this task. We achieved the best Matchm score (described in section 2.2) of 0.810 and were ranked third on the leaderboard.

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Vipul Singhal, Sahil Dhull, Rishabh Agarwal, Ashutosh Modi. 2020-07-21. IITK at SemEval-2020 Task 10: Transformers for Emphasis Selection. https://arxiv.org/abs/2007.10820

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