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:
We make copies of the monolingual model for each language and add additional crosslingual latent variables (CLVs) to couple the monolingual models, capturing crosslingual semantic role patterns. Concretely, when training on parallel sentences, whenever the head words of the arguments are aligned, we add a CLV as a parent of the two corresponding role variables.

Ex Output:
Do they add one latent variable for each language pair in their Bayesian model?


Ex Input:
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.

Ex Output:
How many examples are there in the target domain?


Ex Input:
We train MaLOPa on the concantenation of training sections of all seven languages.

Ex Output:

How many languages have this parser been tried on?