---
title: "Who cites GOF at Qur'an QA 2022: Towards — 4 citing papers"
description: "4 papers of the Elamur Research library cite «GOF at Qur'an QA 2022: Towards an Efficient Question Answering For The Holy Qu'ran In The…"
canonical: "https://research.elamur.ai/free/en/papers/mostafa-2022-gof-qur-qa-2022-efficient/cited-by/"
---
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# Who cites «GOF at Qur'an QA 2022: Towards an Efficient Question Answering For The Holy Qu'ran In The Arabic Language Using Deep Learning-Based Approach»

4 papers of our library cite it (of the 149,439 whose bibliographies we read) · 4 with a page here, the most cited first · [← back to «GOF at Qur'an QA 2022: Towards an Efficient Question Answering For The Holy Qu'ran In The Arabic Language Using Deep Learning-Based Approach»](https://md.research.elamur.ai/free/en/papers/mostafa-2022-gof-qur-qa-2022-efficient/)

1. **[Qur'an QA 2023 Shared Task: Overview of Passage Retrieval and Reading Comprehension Tasks over the Holy Qur'an](https://md.research.elamur.ai/free/en/papers/malhas-2023-qur-qa-2023-shared-task/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Rana Malhas, Watheq Mansour, Tamer Elsayed*2023 · 33 citations*
2. **[Qur'an QA 2022: Overview of The First Shared Task on Question Answering over the Holy Qur'an](https://md.research.elamur.ai/free/en/papers/malhas-2022-qur-qa-2022-overview-first/) [Workshop on Open-Source Arabic Corpora and Processing Tools with Shared Tasks](https://md.research.elamur.ai/free/en/venues/osact/)**Rana Malhas, Watheq Mansour, Tamer Elsayed*2022 · 32 citations*
3. **[TCE at Qur'an QA 2023 Shared Task: Low Resource Enhanced Transformer-based Ensemble Approach for Qur'anic QA](https://md.research.elamur.ai/free/en/papers/elkomy-2023-tce-qur-qa-2023-shared/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Mohammed Elkomy, Amany Sarhan*2023 · 11 citations*
4. **[ADAPT–MTU HAI at PalmX 2025: Leveraging Full and Parameter-Efficient LLM Fine-Tuning for Arabic Cultural QA](https://md.research.elamur.ai/free/en/papers/hossain-2025-adapt-mtu-hai-palmx-2025/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Shehenaz Hossain, Haithem Afli*2025 · 1 citation*
- [← back to](https://md.research.elamur.ai/free/en/papers/mostafa-2022-gof-qur-qa-2022-efficient/) — GOF at Qur'an QA 2022: Towards an Efficient Question Answering For The Holy Qu'ran In The Arabic Language Using Deep Learning-Based Approach