  This paper describes our system designed for SemEval-2022 Task 8:
Multilingual News Article Similarity. We proposed a linguistics-inspired model
trained with a few task-specific strategies. The main techniques of our system
are: 1) data augmentation, 2) multi-label loss, 3) adapted R-Drop, 4) samples
reconstruction with the head-tail combination. We also present a brief analysis
of some negative methods like two-tower architecture. Our system ranked 1st on
the leaderboard while achieving a Pearson's Correlation Coefficient of 0.818 on
the official evaluation set.
