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This paper describes our contribution to SemEval-2020 Task 11: Detection OfPropaganda Techniques In News Articles. We start with simple LSTM baselines andmove to an autoregressive transformer decoder to predict long continuouspropaganda spans for the first subtask. We also adopt an approach from relationextraction by enveloping spans mentioned above with special tokens for thesecond subtask of propaganda technique classification. Our models report anF-score of 44.6% and a micro-averaged F-score of 58.2% for those tasksaccordingly.

NoPropaganda at SemEval-2020 Task 11: A Borrowed Approach to Sequence Tagging and Text Classification