In this task, you will be presented with a context from an academic paper and a question separated with a 
. You have to answer the question based on the context.

To tackle this issue, we investigate how to improve the generalization of BERT-based MCQA models with the constraint of limited training data using four representative MCQA datasets: DREAM, MCTest, TOEFL, and SemEval-2018 Task 11. 
 Question: What four representative datasets are used for bechmark?
DREAM, MCTest, TOEFL, and SemEval-2018 Task 11

The ensembles were formed by simply averaging the predictions from the constituent single models. 
 Question: How does their ensemble method work?
simply averaging the predictions from the constituent single models

Of the 144 schemas in the collection at WinogradSchemas there are 33 that can plausibly be translated this way. 
 Question: Did they collect their own datasets?

No