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: $LS \cup KLD \cup CONN$ and $KLD \cup LS \cup LS_{inter}$ are the best systems with the highest recall and F1-score respectively.

A: What was previous state-of-the-art approach?
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Q: If we re-train the skip-gram model and update the emoji map periodically on new escort ads, when traffickers switch to new emojis, the map can link the new emojis to the old ones, assisting anti-trafficking experts in expanding the lexicon of trafficking flags. This approach also works for acronyms and deliberate typos.

A: How is the lexicon of trafficking flags expanded?
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Q: Our first task is the recently-introduced Visual Question Answering challenge (VQA) BIBREF22 . The next set of experiments we consider focuses on GeoQA, a geographical question-answering task first introduced by Krish2013Grounded.

A:
What benchmark datasets they use?
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