Li Xiang

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2022

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X-PuDu at SemEval-2022 Task 7: A Replaced Token Detection Task Pre-trained Model with Pattern-aware Ensembling for Identifying Plausible Clarifications
Junyuan Shang | Shuohuan Wang | Yu Sun | Yanjun Yu | Yue Zhou | Li Xiang | Guixiu Yang
Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)

This paper describes our winning system on SemEval 2022 Task 7: Identifying Plausible Clarifications ofImplicit and Underspecified Phrases in Instructional Texts. A replaced token detection pre-trained model is utilized with minorly different task-specific heads for SubTask-A: Multi-class Classification and SubTask-B: Ranking. Incorporating a pattern-aware ensemble method, our system achieves a 68.90% accuracy score and 0.8070 spearman’s rank correlation score surpassing the 2nd place with a large margin by 2.7 and 2.2 percent points for SubTask-A and SubTask-B, respectively. Our approach is simple and easy to implement, and we conducted ablation studies and qualitative and quantitative analyses for the working strategies used in our system.
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