| | Session 1: Main Workshop |
| 9:00–9:10 | Workshop Opening
Hend Al-Khalifa, Tamer Elsayed, Hamdy Mubarak, Abdulmohsen Al-Thubaity, Walid Magdy, and Kareem Darwish |
| 9:10–9:50 | Keynote Talk: A proposal to accelerate innovation for Arabic Speech and Language Processing
Hassan Sawaf, aiXplain.com |
| 9:50–10:10 | TURJUMAN: A Public Toolkit for Neural Arabic Machine Translation
El Moatez Billah Nagoudi, AbdelRahim Elmadany and Muhammad Abdul-Mageed |
| 10:10–10:30 | Detecting Users Prone to Spread Fake News on Arabic Twitter
Zien Sheikh Ali, Abdulaziz Al-Ali and Tamer Elsayed |
| | Session 2: Main Workshop (Cont.) |
| 11:00–11:20 | AraSAS: The Open Source Arabic Semantic Tagger
Mahmoud El-Haj, Elvis de Souza, Nouran Khallaf, Paul Rayson and Nizar Habash |
| 11:20–11:40 | AraNPCC: The Arabic Newspaper COVID-19 Corpus
Abdulmohsen Al-Thubaity, Sakhar Alkhereyf and Alia O. Bahanshal |
| 11:40–12:00 | Pre-trained Models or Feature Engineering: The Case of Dialectal Arabic
Kathrein Abu Kwaik, Stergios Chatzikyriakidis and Simon Dobnik |
| 12:00–12:20 | A Context-free Arabic Emoji Sentiment Lexicon (CF-Arab-ESL)
Shatha Ali A. Hakami, Robert Hendley and Phillip Smith |
| 12:20–12:40 | Sa‘7r: A Saudi Dialect Irony Dataset
Halah AlMazrua, Najla AlHazzani, Amaal AlDawod, Lama AlAwlaqi, Noura AlReshoudi, Hend Al-Khalifa and Luluh AlDhubayi |
| 12:40–13:00 | Classifying Arabic Crisis Tweets using Data Selection and Pre-trained Language Models
Alaa Alharbi and Mark Lee |
| | Session 3: Qur’an QA Shared Task |
| 14:00–14:20 | Qur’an QA 2022: Overview of The First Shared Task on Question Answering over the Holy Qur’an
Rana Malhas, Watheq Mansour and Tamer Elsayed |
| 14:20–14:30 | DTW at Qur’an QA 2022: Utilising Transfer Learning with Transformers for Question Answering in a Low-resource Domain
Damith Premasiri, Tharindu Ranasinghe, Wajdi Zaghouani and Ruslan Mitkov |
| 14:30–14:40 | eRock at Qur’an QA 2022: Contemporary Deep Neural Networks for Qur’an based Reading Comprehension Question Answers
Esha Aftab and Muhammad Kamran Malik |
| 14:40–14:50 | 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
Ali Mostafa and Omar Mohamed |
| 14:50–15:00 | LARSA22 at Qur’an QA 2022: Text-to-Text Transformer for Finding Answers to Questions from Qur’an
Youssef MELLAH, Ibtissam Touahri, Zakaria Kaddari, Zakaria Haja, Jamal Berrich and Toumi Bouchentouf |
| 15:00–15:10 | LK2022 at Qur’an QA 2022: Simple Transformers Model for Finding Answers to Questions from Qur’an
Abdullah Alsaleh, Saud Althabiti, Ibtisam Alshammari, Sarah Alnefaie, Sanaa Alowaidi, Alaa Alsaqer, Eric Atwell, Abdulrahman Altahhan and Mohammad Alsalka |
| 15:10–15:20 | niksss at Qur’an QA 2022: A Heavily Optimized BERT Based Model for Answering Questions from the Holy Qu’ran
Nikhil Singh |
| 15:20–15:30 | QQATeam at Qur’an QA 2022: Fine-Tunning Arabic QA Models for Qur’an QA Task
Basem Ahmed, Motaz Saad and Eshrag A. Refaee, |
| 15:30–15:40 | SMASH at Qur’an QA 2022: Creating Better Faithful Data Splits for Low-resourced Question Answering Scenarios
Amr Keleg and Walid Magdy |
| 15:40–15:50 | Stars at Qur’an QA 2022: Building Automatic Extractive Question Answering Systems for the Holy Qur’an with Transformer Models and Releasing a New Dataset
Ahmed Sleem, Eman Mohammed lotfy Elrefai, Marwa Mohammed Matar and Haq Nawaz |
| 15:50–16:00 | TCE at Qur’an QA 2022: Arabic Language Question Answering Over Holy Qur’an Using a Post-Processed Ensemble of BERT-based Models
Mohamemd Elkomy and Amany M. Sarhan |
| | Session 4: Fine-Grained Hate Speech Detection Shared Task |
| 16:30–16:40 | Overview of OSACT5 Shared Task on Arabic Offensive Language and Hate Speech Detection
Hamdy Mubarak, Hend Al-Khalifa and Abdulmohsen Al-Thubaity |
| 16:40–16:50 | GOF at Arabic Hate Speech 2022: Breaking The Loss Function Convention For Data-Imbalanced Arabic Offensive Text Detection
Ali Mostafa, Omar Mohamed and Ali Ashraf |
| 16:50–17:00 | iCompass at Arabic Hate Speech 2022: Detect Hate Speech Using QRNN and Transformers
Mohamed Aziz Bennessir, Malek Rhouma, Hatem Haddad and Chayma Fourati |
| 17:00–17:10 | UPV at the Arabic Hate Speech 2022 Shared Task: Offensive Language and Hate Speech Detection using Transformers and Ensemble Models
Angel Felipe Magnossão de Paula, Paolo Rosso, Imene Bensalem and Wajdi Zaghouani |
| 17:10–17:20 | Meta AI at Arabic Hate Speech 2022: MultiTask Learning with Self-Correction for Hate Speech Classification
Badr AlKhamissi and Mona Diab |
| 17:20–17:30 | CHILLAX - at Arabic Hate Speech 2022: A Hybrid Machine Learning and Transformers based Model to Detect Arabic Offensive and Hate Speech
Kirollos Makram, Kirollos George Nessim, Malak Emad Abd-Almalak, Shady Zekry Roshdy, Seif Hesham Salem, Fady Fayek Thabet and Ensaf Hussien Mohamed |
| 17:30–17:40 | AlexU-AIC at Arabic Hate Speech 2022: Contrast to Classify
Ahmad Shapiro, Ayman Khalafallah and Marwan Torki |
| 17:40–17:50 | GUCT at Arabic Hate Speech 2022: Towards a Better Isotropy for Hatespeech Detection
Nehal Elkaref and Mervat Abu-Elkheir |
| 17:50–18:00 | aiXplain at Arabic Hate Speech 2022: An Ensemble Based Approach to Detecting Offensive Tweets
Salaheddin Alzubi, Thiago Castro Ferreira, Lucas Pavanelli and Mohamed Al-Badrashiny |
