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

• URL: http://arxiv.org/abs/2104.01046v1
• Date: Fri, 2 Apr 2021 13:40:12 GMT
• Title: IITK@LCP at SemEval 2021 Task 1: Classification for Lexical Complexity Regression Task
• Authors: Neil Rajiv Shirude, Sagnik Mukherjee, Tushar Shandhilya, Ananta Mukherjee, Ashutosh Modi
• Abstract summary: We leverage the ELECTRA model and attempt to mirror the data annotation scheme. 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.
• Score: 1.5952305322416085
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: 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.

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