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This paper describes our system (Solomon) details and results ofparticipation in the SemEval 2020 Task 11 "Detection of Propaganda Techniquesin News Articles"\cite{DaSanMartinoSemeval20task11}. We participated in Task"Technique Classification" (TC) which is a multi-class classification task. Toaddress the TC task, we used RoBERTa based transformer architecture forfine-tuning on the propaganda dataset. The predictions of RoBERTa were furtherfine-tuned by class-dependent-minority-class classifiers. A special classifier,which employs dynamically adapted Least Common Sub-sequence algorithm, is usedto adapt to the intricacies of repetition class. Compared to the otherparticipating systems, our submission is ranked 4th on the leaderboard.

Solomon at SemEval-2020 Task 11: Ensemble Architecture for Fine-Tuned Propaganda Detection in News Articles