In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.

Q: For English dataset, we crawl 687 cybersecurity articles from a collection of advanced persistent threats (APT) reports which are published from 2008 to 2018.
Question: Where are the cybersecurity articles used in the model sourced from?

A: from a collection of advanced persistent threats (APT) reports which are published from 2008 to 2018
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Q: We conducted an experiment to determine whether we could maintain or improve classifier performances by applying the following three-tiered feature elimination approach:

Reduction We reduced the dataset encoded for each class by eliminating features that occur less than twice in the full dataset.

Selection We iteratively applied Chi-Square feature selection on the reduced dataset, selecting the top percentile of highest ranked features in increments of 5 percent to train and test the support vector model using a linear kernel and 5-fold, stratified cross-validation.

Rank We cumulatively plotted the average F1-score performances of each incrementally added percentile of top ranked features. We report the percentile and count of features resulting in the first occurrence of the highest average F1-score for each class.
Question: What are the three steps to feature elimination?

A: Reduction Selection Rank
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Q: Following BIBREF21, we sample $K$ captions for each image when applying REINFORCE: ${\hat{c}}_1 \ldots {\hat{c}}_K$, ${\hat{c}}_k \sim p_{ heta }(c|I)$,

The baseline for each sampled caption is defined as the average reward of the rest samples.
Question: What baseline function is used in REINFORCE algorithm?

A:
baseline for each sampled caption is defined as the average reward of the rest samples
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