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.

In this paper, we present an extraction-then-synthesis framework for machine reading comprehension shown in Figure 1 , in which the answer is synthesized from the extraction results. We build an evidence extraction model to predict the most important sub-spans from the passages as evidence, and then develop an answer synthesis model which takes the evidence as additional features along with the question and passage to further elaborate the final answers.
Which framework they propose in this paper?

Last but not least, ethics and fairness are important considerations, that deserve to be studied. In that sense, detection of individual and global bias should be prioritized in order to give useful feedbacks to practitioners. Furthermore we are considering using adversarial learning as in BIBREF33 in order to ensure fairness during the training process.
Is there any ethical consideration in the research?

Cloze Track User Query Track

What two types the Chinese reading comprehension dataset consists of?