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:  At the moment defender can draw on methods from image area to text for improving the robustness of DNNs, e.g. adversarial training BIBREF107 , adding extra layer BIBREF113 , optimizing cross-entropy function BIBREF114 , BIBREF115 or weakening the transferability of adversarial examples.

A: Which strategies show the most promise in deterring these attacks?
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Q: We use 300 Dimensional Glove Common Crawl Embeddings (840B Token) BIBREF11 and fine tune them for the task.

A: What data are the embeddings trained on?
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Q: We use precision, recall and F-measure to evaluate the detected revisions.

A:
What metrics are used to evaluation revision detection?
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