ITNLP2022 at SemEval-2022 Task 8: Pre-trained Model with Data Augmentation and Voting for Multilingual News Similarity
Zhongan Chen, Weiwei Chen, YunLong Sun, Hongqing Xu, Shuzhe Zhou, Bohan Chen, Chengjie Sun, Yuanchao Liu · Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022) · 2022
This article introduces a system to solve the SemEval 2022 Task 8: Multilingual News Article Similarity.The task focuses on the consistency of events reported in two news articles.The system consists of a pre-trained model(e.g., INFOXLM and XLM-RoBERTa) to extract multilingual news features, following fully-connected networks to measure the similarity.In addition, data augmentation and Ten Folds Voting are used to enhance the model.Our final submitted model is an ensemble of three base models, with a Pearson value of 0.784 on the test dataset.