arXiv 2007.108202020-07-21cs.CLcs.AIcs.LG

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

Indian Institute of Technology Kanpur（印度理工学院坎普尔分校）

Vipul Singhal, Sahil Dhull, Rishabh Agarwal, Ashutosh Modi

备注：: 6 pages, 3 figures, 3 tables. Accepted at Proceedings of 14th International Workshop on Semantic Evaluation (SemEval-2020)

英文摘要：

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.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。