X-PuDu at SemEval-2022 Task 7: A Replaced Token Detection Task Pre-trained Model with Pattern-aware Ensembling for Identifying Plausible Clarifications
Computation and Language2022-11-29v1Artificial Intelligence
This paper describes our winning system on SemEval 2022 Task 7: Identifying Plausible Clarifications of Implicit 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.
@article{arxiv.2211.14734,
title = {X-PuDu at SemEval-2022 Task 7: A Replaced Token Detection Task Pre-trained Model with Pattern-aware Ensembling for Identifying Plausible Clarifications},
author = {Junyuan Shang and Shuohuan Wang and Yu Sun and Yanjun Yu and Yue Zhou and Li Xiang and Guixiu Yang},
journal= {arXiv preprint arXiv:2211.14734},
year = {2022}
}
Comments
Accepted at the 16th International Workshop on Semantic Evaluation (SemEval-2022), NAACL