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: Adaptation to food domain captioning Consequently, the food dataset has 3,806 images for training and 1,775 for validation. The non-food dataset has 78,976 images for training and 38,749 for validation.

SOLUTION: How many examples are there in the target domain?

PROBLEM: However, what we did was more than this, and we also achieved great results on the second-level and third-level senses for the sake of our self-demand for high-quality, finally achieving agreement of 0.85 and Kappa value of 0.83 for these two deeper levels of senses.

SOLUTION: How high is the inter-annotator agreement?

PROBLEM: We perform experiments on document-level variants of the SQuAD dataset BIBREF1 .

SOLUTION:
What datasets have this method been evaluated on?