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.

[Q]: We use the $ extsc {BERT}_{ extsc {BASE}}$ ensemble from BIBREF3 as the single-hop QA model.
[A]: What off-the-shelf QA model was used to answer sub-questions?

[Q]: Table TABREF24 shows that while the acceleration of trading decoder layers for encoding layers in training is small, in decoding is significant. Specifically, the Transformer with 10 encoder layers and 2 decoder layers is $2.32$ times as fast as the 6-layer Transformer while achieving a slightly higher BLEU.
[A]: How much is decoding speed increased by increasing encoder and decreasing decoder depth?

[Q]: Figure FIGREF29 shows the $ ext{MPAs}$ of the proposed DP-LSTM and vanilla LSTM for comparison.
[A]:
Is the model compared against a linear regression baseline?