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: The MCD splits achieve a significantly higher compound divergence at a similar atom divergence when compared to the other experiments.

SOLUTION: What are results of comparison between novel method to other approaches for creating compositional generalization benchmarks?

PROBLEM: Follow the prior works BIBREF6, BIBREF7, BIBREF9, we adopt the BLEU and the Micro Entity F1 to evaluate our model performance. We provide human evaluation on our framework and the compared models. We hire several human experts and ask them to judge the quality of the responses according to correctness, fluency, and humanlikeness on a scale from 1 to 5.

SOLUTION: What were the evaluation metrics?

PROBLEM: Despite these shortcomings in using WER as a metric of success, the WER can reflect our model's effectiveness in generating questions that are similar to those of SQuAD based on the given reading passage and answer. WER can be used for initial analyses that can lead to deeper insights as discussed further below.

SOLUTION:
Why did they choose WER as evaluation metric?