SynDARin: Synthesising Datasets for Automated Reasoning in Low-Resource Languages

Challenge:	Question Answering datasets are scarce for languages other than English due to the cost and difficulties of collection and manual annotation.
Approach:	They propose a method for generating and validating QA datasets for low-resource languages . they use English data as context to generate synthetic multiple-choice (MC) question-answer pairs .
Outcome:	The proposed method maintains quality, reduces likelihood of factual errors, and circumvents costly annotation.

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