Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: PerCQA: Persian Community Question Answering Dataset   Community Question Answering (CQA) forums provide answers for many real-life
questions. Thanks to the large size, these forums are very popular among
machine learning researchers. Automatic answer selection, answer ranking,
question retrieval, expert finding, and fact-checking are example learning
tasks performed using CQA data. In this paper, we present PerCQA, the first
Persian dataset for CQA. This dataset contains the questions and answers
crawled from the most well-known Persian forum. After data acquisition, we
provide rigorous annotation guidelines in an iterative process, and then the
annotation of question-answer pairs in SemEvalCQA format. PerCQA contains 989
questions and 21,915 annotated answers. We make PerCQA publicly available to
encourage more research in Persian CQA. We also build strong benchmarks for the
task of answer selection in PerCQA by using mono- and multi-lingual pre-trained
language models

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The categories of this paper are: q-bio
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The categories of this paper are: hep-ex
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The categories of this paper are: nucl-th
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The categories of this paper are: math-ph
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The categories of this paper are: hep-lat
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The categories of this paper are: plasm-ph
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The categories of this paper are: ao-sci
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The categories of this paper are: adap-org
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The categories of this paper are: q-fin
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The categories of this paper are: stat
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The categories of this paper are: atom-ph
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The categories of this paper are: alg-geom
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The categories of this paper are: bayes-an
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The categories of this paper are: chao-dyn
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The categories of this paper are: nucl-ex
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The categories of this paper are: q-alg