instruction:
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.
question:
Yet, it is possible that the precise interpretability scores that are measured here are biased by the dataset used. However, it should be noted that the change in the interpretability scores for different word coverages might be effected by non-ideal subsampling of category words. Although our word sampling method, based on words' distances to category centers, is expected to generate categories that are represented better compared to random sampling of category words, category representations might be suboptimal compared to human designed categories.
answer:
What are the weaknesses of their proposed interpretability quantification method?


question:
We use 300 Dimensional Glove Common Crawl Embeddings (840B Token) BIBREF11 and fine tune them for the task.
answer:
What data are the embeddings trained on?


question:
French and Russian, and Arabic can be regarded as high resource languages whereas Hindi has far less data and can be considered as low resource.
answer:

Is the system tested on low-resource languages?