@inproceedings{shang-etal-2022-x,
title = "{X}-{P}u{D}u at {S}em{E}val-2022 Task 7: A Replaced Token Detection Task Pre-trained Model with Pattern-aware Ensembling for Identifying Plausible Clarifications",
author = "Shang, Junyuan and
Wang, Shuohuan and
Sun, Yu and
Yu, Yanjun and
Zhou, Yue and
Xiang, Li and
Yang, Guixiu",
editor = "Emerson, Guy and
Schluter, Natalie and
Stanovsky, Gabriel and
Kumar, Ritesh and
Palmer, Alexis and
Schneider, Nathan and
Singh, Siddharth and
Ratan, Shyam",
booktitle = "Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)",
month = jul,
year = "2022",
address = "Seattle, United States",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.semeval-1.152",
doi = "10.18653/v1/2022.semeval-1.152",
pages = "1078--1083",
abstract = "This paper describes our winning system on SemEval 2022 Task 7: $\textit{Identifying Plausible Clarifications ofImplicit and Underspecified Phrases in Instructional Texts}$. A replaced token detection pre-trained model is utilized with minorly different task-specific heads for SubTask-A: $\textit{Multi-class Classification}$ and SubTask-B: $\textit{Ranking}$. 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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%0 Conference Proceedings
%T X-PuDu at SemEval-2022 Task 7: A Replaced Token Detection Task Pre-trained Model with Pattern-aware Ensembling for Identifying Plausible Clarifications
%A Shang, Junyuan
%A Wang, Shuohuan
%A Sun, Yu
%A Yu, Yanjun
%A Zhou, Yue
%A Xiang, Li
%A Yang, Guixiu
%Y Emerson, Guy
%Y Schluter, Natalie
%Y Stanovsky, Gabriel
%Y Kumar, Ritesh
%Y Palmer, Alexis
%Y Schneider, Nathan
%Y Singh, Siddharth
%Y Ratan, Shyam
%S Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
%D 2022
%8 July
%I Association for Computational Linguistics
%C Seattle, United States
%F shang-etal-2022-x
%X 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.
%R 10.18653/v1/2022.semeval-1.152
%U https://aclanthology.org/2022.semeval-1.152
%U https://doi.org/10.18653/v1/2022.semeval-1.152
%P 1078-1083
Markdown (Informal)
[X-PuDu at SemEval-2022 Task 7: A Replaced Token Detection Task Pre-trained Model with Pattern-aware Ensembling for Identifying Plausible Clarifications](https://aclanthology.org/2022.semeval-1.152) (Shang et al., SemEval 2022)
ACL