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]: Since we do not have an end-to-end dataset, the generated English poem may not work well with Shakespeare style transfer as shown in Figure FIGREF12 for "Starry Night" with a low average content score. This happens when the style transfer dataset does not have similar words in the training set of sentences. A solution would be to expand the style transfer dataset, for a better representation of the poem data.
[A]: What limitations do the authors demnostrate of their model?


[Q]: However, the coherence of the topics produced by LDA is poorer than expected.

To address this lack of coherence, we applied non-negative matrix factorization (NMF).
[A]: How are prominent topics idenified in Dabiq and Rumiyah?


[Q]: Based on annotated corpora and token-based features, studies used machine learning approaches to build word segmentation systems with accuracy about 94%-97%.
[A]:
How successful are the approaches used to solve word segmentation in Vietnamese?