TASK DEFINITION: In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
PROBLEM: Evaluating FastText, GloVe and word2vec, we show that compared to other word representation learning algorithms, the FastText performs best.

SOLUTION: What do you use to calculate word/sub-word embeddings

PROBLEM: The above pseudocode is agnostic with respect to the choice of fragmentation and environment functions; task-specific choices are described in more detail for each experiment below.

Discussion

SOLUTION: Which languages do they test on?

PROBLEM: The question generation model provides each candidate answer with a score by measuring semantic relevance between the question and the generated question based on the semantics of the candidate answer. 

SOLUTION:
Where is a question generation model used?