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CUHK at SemEval-2020 Task 4: CommonSense Explanation, Reasoning and Prediction with Multi-task Learning (2006.09161v2)

Published 12 Jun 2020 in cs.CL, cs.AI, and cs.LG

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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Authors (7)
  1. Hongru Wang (62 papers)
  2. Xiangru Tang (62 papers)
  3. Sunny Lai (1 paper)
  4. Kwong Sak Leung (1 paper)
  5. Jia Zhu (41 papers)
  6. Gabriel Pui Cheong Fung (5 papers)
  7. Kam-Fai Wong (92 papers)
Citations (4)

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