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.

Q: Even if LangID-High does not present a more accurate result, it does present a more compact one: LangID-High is 15.4 MB, while the combined wFST high resource models are 197.5 MB.

A: how is model compactness measured?
****
Q: The training dataset contains 2,815 examples, where 1,940 (i.e., 69%) are fake news and 1,968 (i.e., 70%) are click-baits; we further have 761 testing examples.

A: what datasets were used?
****
Q: To study how the multimodal context can boost the performance compared to an unimodal context we evaluate different models: a Feature Concatenation Model (FCM), a Spatial Concatenation Model (SCM) and a Textual Kernels Model (TKM)

A:
What models do they propose?
****