CUHK at SemEval-2020 Task 4: CommonSense Explanation, Reasoning and Prediction with Multi-task Learning
June 12, 2020 ยท Declared Dead ยท ๐ International Workshop on Semantic Evaluation
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Authors
Hongru Wang, Xiangru Tang, Sunny Lai, Kwong Sak Leung, Jia Zhu, Gabriel Pui Cheong Fung, Kam-Fai Wong
arXiv ID
2006.09161
Category
cs.CL: Computation & Language
Cross-listed
cs.AI,
cs.LG
Citations
4
Venue
International Workshop on Semantic Evaluation
Last Checked
5 months ago
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 it makes sense and require the model to explain it. Based on BERTarchitecture with a 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 chooses 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), andBLEU score of 12.9 in subtask C (rank 8)
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