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Cross-lingual transfer learning has been studied at depth. While many methods have been developed for pretraining or fine-tuning on monolingual, multilingual and parallel corpora with the purpose of predicting on a low-resource monolingual test set; in this paper we investigate the feasibility of training a text classifier on a monolingual training set and predicting on a parallel test set, jointly utilizing both languages at inference time only.