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arXiv 2104.01046cs.CL

IITK@LCP at SemEval 2021 Task 1: Classification for Lexical Complexity Regression Task

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

Neil Rajiv Shirude, Sagnik Mukherjee, Tushar Shandhilya, Ananta Mukherjee, Ashutosh Modi

英文摘要:

This paper describes our contribution to SemEval 2021 Task 1: Lexical Complexity Prediction. In our approach, we leverage the ELECTRA model and attempt to mirror the data annotation scheme. Although the task is a regression task, we show that we can treat it as an aggregation of several classification and regression models. This somewhat counter-intuitive approach achieved an MAE score of 0.0654 for Sub-Task 1 and MAE of 0.0811 on Sub-Task 2. Additionally, we used the concept of weak supervision signals from Gloss-BERT in our work, and it significantly improved the MAE score in Sub-Task 1.

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。

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