@inproceedings{wang-etal-2020-cuhk,
title = "{CUHK} at {S}em{E}val-2020 Task 4: {C}ommon{S}ense Explanation, Reasoning and Prediction with Multi-task Learning",
author = "Wang, Hongru and
Tang, Xiangru and
Lai, Sunny and
Leung, Kwong Sak and
Zhu, Jia and
Fung, Gabriel Pui Cheong and
Wong, Kam-Fai",
editor = "Herbelot, Aurelie and
Zhu, Xiaodan and
Palmer, Alexis and
Schneider, Nathan and
May, Jonathan and
Shutova, Ekaterina",
booktitle = "Proceedings of the Fourteenth Workshop on Semantic Evaluation",
month = dec,
year = "2020",
address = "Barcelona (online)",
publisher = "International Committee for Computational Linguistics",
url = "https://aclanthology.org/2020.semeval-1.47/",
doi = "10.18653/v1/2020.semeval-1.47",
pages = "391--400",
abstract = "This paper describes our system submitted to task 4 of SemEval 2020: Commonsense Validation and Explanation (ComVE) which consists of three sub-tasks. The task is to directly validate the given sentence whether or not to make sense and require the model to explain it. Based on BERT architecture with the multi-task setting, we propose an effective and interpretable {\textquotedblleft}Explain, Reason and Predict{\textquotedblright} (ERP) system to solve the three sub-tasks about commonsense: (a) Validation, (b) Reasoning, and (c) Explanation. Inspired by cognitive studies of common sense, our system first generates a reason or understanding of the sentences and then choose which one statement makes sense, which is achieved by multi-task learning. During the post-evaluation, our system has reached 92.9{\%} accuracy in subtask A (rank 11), 89.7{\%} accuracy in subtask B (rank 9), and BLEU score of 12.9 in subtask C (rank 8)."
}
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<abstract>This paper describes our system submitted to task 4 of SemEval 2020: Commonsense Validation and Explanation (ComVE) which consists of three sub-tasks. The task is to directly validate the given sentence whether or not to make sense and require the model to explain it. Based on BERT architecture with the multi-task setting, we propose an effective and interpretable “Explain, Reason and Predict” (ERP) system to solve the three sub-tasks about commonsense: (a) Validation, (b) Reasoning, and (c) Explanation. Inspired by cognitive studies of common sense, our system first generates a reason or understanding of the sentences and then choose which one statement makes sense, which is achieved by multi-task learning. During the post-evaluation, our system has reached 92.9% accuracy in subtask A (rank 11), 89.7% accuracy in subtask B (rank 9), and BLEU score of 12.9 in subtask C (rank 8).</abstract>
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%0 Conference Proceedings
%T CUHK at SemEval-2020 Task 4: CommonSense Explanation, Reasoning and Prediction with Multi-task Learning
%A Wang, Hongru
%A Tang, Xiangru
%A Lai, Sunny
%A Leung, Kwong Sak
%A Zhu, Jia
%A Fung, Gabriel Pui Cheong
%A Wong, Kam-Fai
%Y Herbelot, Aurelie
%Y Zhu, Xiaodan
%Y Palmer, Alexis
%Y Schneider, Nathan
%Y May, Jonathan
%Y Shutova, Ekaterina
%S Proceedings of the Fourteenth Workshop on Semantic Evaluation
%D 2020
%8 December
%I International Committee for Computational Linguistics
%C Barcelona (online)
%F wang-etal-2020-cuhk
%X This paper describes our system submitted to task 4 of SemEval 2020: Commonsense Validation and Explanation (ComVE) which consists of three sub-tasks. The task is to directly validate the given sentence whether or not to make sense and require the model to explain it. Based on BERT architecture with the multi-task setting, we propose an effective and interpretable “Explain, Reason and Predict” (ERP) system to solve the three sub-tasks about commonsense: (a) Validation, (b) Reasoning, and (c) Explanation. Inspired by cognitive studies of common sense, our system first generates a reason or understanding of the sentences and then choose which one statement makes sense, which is achieved by multi-task learning. During the post-evaluation, our system has reached 92.9% accuracy in subtask A (rank 11), 89.7% accuracy in subtask B (rank 9), and BLEU score of 12.9 in subtask C (rank 8).
%R 10.18653/v1/2020.semeval-1.47
%U https://aclanthology.org/2020.semeval-1.47/
%U https://doi.org/10.18653/v1/2020.semeval-1.47
%P 391-400
Markdown (Informal)
[CUHK at SemEval-2020 Task 4: CommonSense Explanation, Reasoning and Prediction with Multi-task Learning](https://aclanthology.org/2020.semeval-1.47/) (Wang et al., SemEval 2020)
ACL