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.

Ex Input:
The model consists of one layer of LSTM followed by three dense layers. The LSTM layer uses a dropout value of 0.2.

Ex Output:
Do they use dropout?

Ex Input:
We crowdsourced multiple-choice questions in two parts, encouraging workers to be imaginative and varied in their use of language. First, workers were given a seed qualitative relation q+/-( INLINEFORM0 ) in the domain, expressed in English (e.g., "If a surface has more friction, then an object will travel slower"), and asked to enter two objects, people, or situations to compare.

Ex Output:
Do all questions in the dataset allow the answers to pick from 2 options?

Ex Input:
Adhering to the experimental settings of BIBREF1 , we concatenate sentence representations produced from our model with those obtained from the state-of-the-art unsupervised learning model (Layer Normalized Skip-Thoughts, ST-LN) BIBREF31 . Following the experimental design of BIBREF1 , we conduct experiments on three different learning objectives: Cap2All, Cap2Cap, Cap2Img.

Ex Output:
What baselines are the proposed method compared against?