WueDevils at SemEval-2022 Task 8: Multilingual News Article Similarity via Pair-Wise Sentence Similarity Matrices

@inproceedings{Wangsadirdja2022WueDevilsAS,
  title={WueDevils at SemEval-2022 Task 8: Multilingual News Article Similarity via Pair-Wise Sentence Similarity Matrices},
  author={Dirk Wangsadirdja and Felix Heinickel and Simon Trapp and Albin Zehe and Konstantin Kobs and Andreas Hotho},
  booktitle={International Workshop on Semantic Evaluation},
  year={2022}
}
We present a system that creates pair-wise cosine and arccosine sentence similarity matrices using multilingual sentence embeddings obtained from pre-trained SBERT and Universal Sentence Encoder (USE) models respectively. For each news article sentence, it searches the most similar sentence from the other article and computes an average score. Further, a convolutional neural network calculates a total similarity score for the article pairs on these matrices. Finally, a random forest regressor… 
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SemEval-2022 Task 8: Multilingual news article similarity

A new dataset of nearly 10,000 news article pairs spanning 18 language combinations annotated for seven dimensions of similarity as SemEval 2022 Task 8 is introduced, showing human annotators are capable of reaching higher correlations and suggesting space for further progress.

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