mlsanityData to 14 Oct 2026

PerCQA: Persian Community Question Answering Dataset

arXiv 2112.13238 ↗First posted 25 Dec 2021cs.CLcited by 5

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Abstract (arXiv)

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

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 22 of its 47 references that are in the map. First posted on arXiv 25 Dec 2021.

Builds on

22 of 47 references.

References · 22

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10 more
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 2; 2024: 1; 2025: 1; 2026: 1.

5 papers.

  1. 2023PersianLLaMA: Towards Building First Persian Large Language Modelcited by 14
  2. 2024TIGQA:An Expert Annotated Question Answering Dataset in Tigrinyacited by 5
  3. 2023IslamicPCQA: A Dataset for Persian Multi-hop Complex Question Answering in Islamic Text Resourcescited by 1
  4. 2025FarsiMCQGen: a Persian Multiple-choice Question Generation Frameworkcited by 0
  5. 2026The Annotation Bottleneck in Persian Text NLP: Persian as an Annotation-Scarce Languagecited by 0