The Fourth Arabic Natural Language Processing Workshop

(WANLP 2019)

co-located with ACL 2019, Florence, Italy, July 28-Aug 2, 2019

Workshop Description

Arabic is a challenging language for the field of computational linguistics. This is due to many factors including its complex and rich morphology, its high degree of ambiguity as well as the presence of a number of dialects that vary quite widely. Arabic is also a language with important geopolitical connections. It is spoken by over 400 million people in countries with varying degrees of prosperity and stability. It is the primary language of the latest world refugee problem affecting the Middle East and Europe. The opportunities that are made possible by working on this language and its dialects cannot be underestimated in their consequence on the Arab World, the Mediterranean Region and the rest of the World.

There has been a lot of progress in the last 20 years in the area of Arabic Natural Language Processing (NLP). Many Arabic NLP (or Arabic NLP-related) workshops and conferences have taken place, both in the Arab World and in association with international conferences. Examples include the following:

    • The First, Second and Third Arabic Natural Language Processing Workshop at EMNLP 2014, ACL 2015 and EACL 2017, respectively.
    • The First, Second, and Third Workshops on Arabic Corpora and Processing Tools at LREC 2014, LREC 2016, and LREC 2018, respectively.
    • The conference on Arabic Language Resources and Tools (MEDAR-2009, NEMLAR-2004).
    • The workshop on Computational Approaches to Semitic Languages (LREC 2010, EACL 2009, ACL 2007, ACL 2005, ACL 2002, ACL 1998).
    • The workshop on Computational Approaches to Arabic Script-based Languages (MTSummit XII 2009, LSA 2007, COLING 2004).
    • The International Symposium on Computer and Arabic Language (ISCAL 2009, ISCAL 2007)

This workshop follows in the footsteps of these efforts to provide a forum for researchers to share and discuss their ongoing work. This workshop is timely given the continued rise in research projects focusing on Arabic NLP.

We invite submissions on topics that include, but are not limited to, the following:

    • Basic core technologies: morphological analysis, disambiguation, tokenization, POS tagging, named entity detection, chunking, parsing, semantic role labeling, sentiment analysis, Arabic dialect modeling, etc.
    • Applications: machine translation, speech recognition, speech synthesis, optical character recognition, pedagogy, assistive technologies, social media, etc.
    • Resources: dictionaries, annotated data, corpus, etc.

Submissions may include work in progress as well as finished work. Submissions must have a clear focus on specific issues pertaining to the Arabic language whether it is standard Arabic, dialectal, or mixed. Papers on other languages sharing problems faced by Arabic NLP researchers such as Semitic languages or languages using Arabic script are welcome. Additionally, papers on efforts using Arabic resources but targeting other languages are also welcome. Descriptions of commercial systems are welcome, but authors should be willing to discuss the details of their work.

Associated with the workshop will be a shared task on Arabic dialect identification. As opposed to previous shared tasked which focused on regional level dialect labeling, this shared task will be the first to target a large set of dialect labels at the city and country levels.

Important Dates

May 3, 2019: Workshop Paper Due Date

May 10, 2019 (Deadline Extended): Workshop Paper Due Date

May 24, 2019: Notification of Acceptance

June 3, 2019: Camera-ready papers due

August 1, 2019: Workshop Date

Paper Submission Instructions

Paper Length: Submissions are expected to be up to 8 pages long plus any number of pages for references. Final versions of long papers will be given one additional page of content (up to 9 pages) so that reviewers’ comments can be taken into account. Shared Task papers are also welcomed; refer to the Shared Task section below for details.

Submission Format: Submissions must be in PDF and prepared using LaTeX. The format must conform with the official ACL 2019 style templates:

    1. Latex Template
    2. Word Template

Submission Website: submissions are done via softconf: https://www.softconf.com/acl2019/arabicnlp

Blind Reviewing Policy: The workshop follows a blind reviewing policy. The authors should omit their names and affiliations from the paper and avoid self-references that reveal their identity. Papers that do not conform to these requirements will be rejected without review.

Multiple Submission Policy: Papers that have been or will be submitted to other meetings or publications must indicate this at submission time. Authors must inform organizers immediately once a paper is to be withdrawn from the workshop for any reason. Attempting to publish the same paper or with a major overlap (50%) may lead to rejection of the paper even after an acceptance notification have gone out.

Anonymity and Supplementary Material (same as ACL 2019): As the reviewing will be blind, papers must not include authors' names and affiliations. Furthermore, self-references that reveal the author's identity, e.g., "We previously showed (Smith, 1991) ..." must be avoided. Instead, use citations such as "Smith previously showed (Smith, 1991) ..." Papers that do not conform to these requirements will be rejected without review.

Papers should not refer, for further detail, to documents that are not available to the reviewers. For example, do not omit or redact important citation information to preserve anonymity. Instead, use third person or named reference to this work, as described above (“Smith showed” rather than “we showed”).

Papers may be accompanied by a resource (software and/or data) described in the paper. Papers that are submitted with accompanying software/data may receive additional credit toward the overall evaluation, and the potential impact of the software and data will be taken into account when making the acceptance/rejection decisions.

WANLP 2019 also encourages the submission of supplementary material to report preprocessing decisions, model parameters, and other details necessary for the replication of the experiments reported in the paper. Seemingly small preprocessing decisions can sometimes make a large difference in performance, so it is crucial to record such decisions to precisely characterize state-of-the-art methods.

Nonetheless, supplementary material should be supplementary (rather than central) to the paper. It may include explanations or details of proofs or derivations that do not fit into the paper, lists of features or feature templates, sample inputs and outputs for a system, pseudo-code or source code, and data. The paper should not rely on the supplementary material: while the paper may refer to and cite the supplementary material and the supplementary material will be available to reviewers, they will not be asked to review or even download the supplementary material. Authors should refer to the contents of the supplementary material in the paper submission, so that reviewers interested in these supplementary details will know where to look.

Note: The supplementary material does not count towards page limit and should not be included in paper, but should be submitted separately using the appropriate field on the submission website

Workshop schedule

8:30 - 8:40: Opening remarks (Wassim El-Hajj)

8:40 - 9:30: Keynote (Ahmed Ali)

9:30 - 10:20: Session 1 - Machine Translation

    • Incremental Domain Adaptation for Neural Machine Translation in Low-Resource Settings, Authors: Marimuthu Kalimuthu, Michael Barz and Daniel Sonntag
    • Morphology-aware Word-Segmentation in Dialectal Arabic Adaptation of Neural Machine Translation, Authors: Ahmed Tawfik, Mahitab Emam, Khaled Essam, Robert Nabil and Hany Hass

10:20 – 10:30: Shared Task Overview

    • The MADAR Shared Task on Arabic Fine-Grained Dialect Identification, Authors: Houda Bouamor, Sabit Hassan and Nizar Habash

10:30-11:00: Coffee Break

11:00 - 12:40: Session 2 - Selected topics

    • POS Tagging for Improving Code-Switching Identification in Arabic, Authors: Mohammed Attia, Younes Samih, Ali Elkahky, Hamdy Mubarak, Ahmed Abdelali and Kareem Darwish
    • Syntax-Ignorant N-gram Embeddings for Sentiment Analysis of Arabic Dialects, Authors: Hala Mulki, Hatem Haddad, Mourad Gridach and Ismail Babaoğlu
    • ArbEngVec : An Arabic-English Cross-Lingual Word Embeddings Models, Authors: Raki Lachraf, El Moatez Billah Nagoudi, Youcef Ayachi, Ahmed Abdelali and Didier Schwab
    • Homograph Disambiguation Through Selective Diacritic Restoration, Authors: Sawsan Alqahtani, Hanan Aldarmaki and Mona Diab

12:40-2:00: Lunch

2:00 – 2:50: Session 3 - Applications Session

    • Arabic Named Entity Recognition: What Works and What’s Next, Authors: Liyuan Liu, Jingbo Shang and Jiawei Han
    • hULMonA: The Universal Language Model in Arabic, Authors: Obeida ElJundi, Wissam Antoun, Nour El Droubi, Hazem Hajj, Wassim El-Hajj and Khaled Shaban

2:50 - 3:30: Workshop Poster Boaster (~3 min per poster )

3:30-4:00: Coffee Break

4:00 – 6:00: Poster Session (Workshop papers and shared task)

Invited Speaker

Dr. Ahmed Ali of the Qatar Computing Research Institute (QCRI) has agreed to be the keynote speaker at the workshop. He will be talking about the latest research and advances in Arabic dialect speech recognition. The speaker will cover his own expenses.

Workshop Organizers

General Chair:

      • Wassim El-Hajj, American University of Beirut, Lebanon. Email: we07 AT aub.edu.lb

Program Chairs:

      • Lamia Hadrich Belguith, Sfax University, Tunisia. Email: lamia.belguith AT gmail.com
      • Fethi Bougares, University of Le Mans, France. Email: fethi.bougares AT univ-lemans.fr
      • Walid Magdy, University of Edinburgh, Scotland. Email: wmagdy AT inf.ed.ac.uk
      • Imed Zitouni, Microsoft, Email: izitouni@microsoft.com

Publication Chairs:

      • Nadi Tomeh, LIPN, Université Paris 13, Sorbonne Paris Cité. Email: nadi.tomeh AT lipn.univ-paris13.fr
      • Mahmoud El-Haj, Lancaster University, England. Email: m.el-haj AT lancaster.ac.uk

Publicity Chair:

      • Wajdi Zaghouani, Hamad Bin Khalifa University, Qatar. Email: wzaghouani AT hbku.edu.qa

Ex-General Chair / Advisor:

      • Nizar Habash, New York University Abu Dhabi, UAE. Email: nizar.habash AT nyu.edu

Advisory Committee:

      • Hend Al-Khalifa, King Saud University, KSA. Email: hendk AT ksu.edu.sa
      • Houda Bouamor, Fortia Financial Solutions, France. Email: houda.bouamor AT fortia.fr
      • Fethi Bougares, University of Le Mans, France. Email: fethi.bougares AT univ-lemans.fr
      • Kareem Darwish, Qatar Computing Research Institute, Qatar. Email: kdarwish AT qf.org.qa
      • Mona Diab, The George Washington University, USA. Email: mtdiab AT email.gwu.edu
      • Mahmoud El-Haj, Lancaster University, England. Email: m.el-haj AT lancaster.ac.uk
      • Wassim El-Hajj, American University of Beirut, Lebanon. Email: we07 AT aub.edu.lb
      • Nizar Habash, New York University Abu Dhabi, UAE. Email: nizar.habash AT nyu.edu
      • Nadi Tomeh, LIPN, Université Paris 13, Sorbonne Paris Cité. Email: nadi.tomeh AT lipn.univ-paris13.fr
      • Wajdi Zaghouani, Hamad Bin Khalifa University , Qatar. Email: wzaghouani AT hbku.edu.qa

Program Committee Members

  1. Ahmed Abdelali, Qatar Computing Research Institute, Qatar
  2. Muhammad Abdul-Mageed , UBC, Canada
  3. Haithem Afli, Cork Institute of Technology, Ireland
  4. Ahmad Al Sallab , Faculty of Enginneeing, Cairo university
  5. Ahmed Ali, Qatar Computing Research Institute, Qatar
  6. Hend Alkhalifa, King Saud University, Saudi Arabia
  7. Chafik Aloulou, Univeristé de Sfax, Tunisia
  8. Areeb Alowisheq, Imam University, KSA
  9. Almoataz Al-Said, Cairo University, Egypt
  10. Nora Al-Twairesh, King Saud University, Saudi Arabia
  11. Salha Alzahrani, Taif University, Saudi Arabia
  12. Walid Aransa, University du Maine, Le Mans, France
  13. Mohammed Attia, George Washington University
  14. Gilbert Badaro, American University of Beirut, Lebanon
  15. Alberto Barrón-Cedeño, Qatar Computing Research Institute, Qatar
  16. Abdelmajid Ben-Hamadou, University of Sfax, Tunisia
  17. Houda Bouamor, Fortia Financial Solutions, France
  18. Fethi Bougares, Le Mans University, France
  19. Karim Bouzoubaa, Mohammad V University, Morocco
  20. Tim Buckwalter, University of Maryland, USA
  21. Violetta Cavalli-Sforza, Al Akhawayn University, Morocco
  22. Khalid Choukri, ELDA, European Language Resource Association, France
  23. Kareem Darwish, Qatar Computing Research Institute, Qatar
  24. Abeer Dayel, King Saud University, Saudi Arabia
  25. Mona Diab, George Washington University, USA
  26. Joseph Dichy, Université Lyon 2 , France
  27. Mahmoud El Haj, Lancaster University, UK
  28. Shady Elbassuoni, American University of Beirut, Lebanon
  29. Wassim El-Hajj, American University of Beirut, Lebanon
  30. Ali Elkahky, Google AI
  31. Mariem Ellouze, University of Sfax, Tunisia
  32. AbdelRahim Elmadany, Jazan Univeristy, KSA
  33. Mohamed Elmahdy, Qatar University, Qatar
  34. Tamer Elsayed, Qatar University, Qatar
  35. Ossama Emam, IBM, USA
  36. Ramy Eskander, Columbia University, USA
  37. Aly Fahmy, Cairo University, Egypt
  38. Ali Farghaly, Monterey Peninsula College, USA
  39. Bilel Gargouri, University of Sfax, Tunisia
  40. Sahar Ghannay, LIUM Laboratory, France
  41. Nada Ghneim, Higher Institute for Applied Sciences and Technology, Syria
  42. Nizar Habash, New York University Abu Dhabi, UAE
  43. Bassam Haddad, University of Petra, Jordan
  44. Lamia Hadrich Belguith, University of Sfax, Tunisia
  45. Hazem Hajj, American University of Beirut, Lebanon
  46. Salwa Hamada, Cairo University, Egypt
  47. Maram Hasanain, Qatar University, Qatar
  48. Mustafa Jarrar, Bir Zeit University, Palestine
  49. Shahram Khadivi, Tehran Polytechnic, Iran
  50. Mohamed Maamouri, Linguistic Data Consortium, USA
  51. Walid Magdy, University of Edinburgh, Scotland
  52. Azzeddine Mazroui, University Mohamed I, Morocco
  53. Seif Mechti, University of Sfax, Tunisia
  54. Salima Medhaffar, Le Mans University, France
  55. Karine Megerdoomian, The MITRE Corporation, USA
  56. Emad Mohamed, Suez Canal University, Egypt
  57. Ghassan Mourad, Lebanese University, Lebanon
  58. Hamdy Mubarak, Qatar Computing Research Institute, Qatar
  59. Preslav Nakov, Qatar Computing Research Institute, Qatar
  60. Alexis Nasr, University of Marseille, France
  61. Abdelsalam Nwesri, University of Tripoli, Libya
  62. Kemal Oflazer, Carnegie Mellon University Qatar, Qatar
  63. Owen Rambow, Columbia University, USA
  64. Mohsen Rashwan, RDI Egypt
  65. Eshrag Refaee, The American University in Cairo, Egypt
  66. Eshrag Refaee, Jazan University, Saudi Arabia
  67. Mohammad Salameh, Carnegie Mellon University, Qatar
  68. Hassan Sawaf, eBay Inc., USA
  69. Khaled Shaalan, The British University in Dubai, UAE
  70. Khaled Shaban, Qatar University, Qatar
  71. Otakar Smrž, Institute of Formal and Applied Linguistics, Charles University in Prague , Czech Republic
  72. Reem Suwaileh, Qatar University, Qatar
  73. Nadi Tomeh, University Paris 13, France
  74. Omar Trigui , University of Sousse, Tunisia
  75. Stephan Vogel, Qatar Computing Research Institute, Qatar
  76. Samantha Wray, Qatar Computing Research Institute, Qatar
  77. Wajdi Zaghouani, Hamad Bin Khalifa University, Qatar
  78. Taha Zerrouki, University of Bouira, Algeria
  79. Imed Zitouni, Microsoft Research, USA
  80. Ines Zribi, Sfax University, Tunisia

MADAR Shared Task: Arabic Fine-Grained Dialect Identification

Introduction: Arabic dialect identification is the task of automatically labeling a segment of speech or text with the dialect it comes from. Most of previous work and shared tasks on dialect identification focused on regional level dialect labeling (efforts by Zaidan and Callison-Burch, Elfardy and Diab, and the VarDial ADI evaluation campaign (http://alt.qcri.org/vardial2018/index.php?id=campaign)). This new proposed shared task will be the first to target a large set of dialect labels at the city and country levels. The data for the shared task is created or collected under the Multi-Arabic Dialect Applications and Resources (MADAR) project. (MADAR Project Page: https://camel.abudhabi.nyu.edu/madar/)

Shared Task Page: https://sites.google.com/view/madar-shared-task/home

Main Workshop Accepted Papers

  1. Neural Models for Detecting Binary Semantic Textual Similarity for Algerian and MSA, Authors: Wafia Adouane, Jean-Philippe Bernardy and Simon Dobnik, (P)
    • Presenter: Wafia Adouane, CLASP- Gothenburg University-Sweden.
  2. Constrained Sequence-to-sequence Semitic Root Extraction for Enriching Word Embeddings, Authors: Ahmed El-Kishky, Xingyu Fu, Aseel Addawood, Nahil Sobh, Clare Voss and Jiawei Han, (P)
    • Presenter: Ahmed El-Kishky, The University of Illinois at Urbana-Champaign, USA
  3. Syntax-Ignorant N-gram Embeddings for Sentiment Analysis of Arabic Dialects, Authors: Hala Mulki, Hatem Haddad, Mourad Gridach and Ismail Babaoğlu, (O)
    • Presenter: Hatem Haddad, RIADI Laboratory, National School of Computer Sciences, University of Manouba, Tunisia
  4. En-Ar Bilingual word Embeddings without Word Alignment: Factors effects, Authors: Taghreed Alqaisi and Simon O'Keefe, (P)
    • Presenter: Taghreed Alqaisi, University of York, UK & Taibah University , Saudia Arabia
  5. Neural Arabic Question Answering, Authors: Hussein Mozannar, Elie Maamary, Karl El Hajal and Hazem Hajj, (P)
    • Presenter: Hussein Mozannar, American University of Beirut, Lebanon
  6. Segmentation for Domain Adaptation in Arabic, Authors: Mohammed Attia and Ali Elkahky, (P)
    • Presenter: Hamdy Mubarak, Qatar Computing Research Institute, Qatar
  7. POS Tagging for Improving Code-Switching Identification in Arabic, Authors: Mohammed Attia, Younes Samih, Ali Elkahky, Hamdy Mubarak, Ahmed Abdelali and Kareem Darwish, (O)
    • Presenter: Hamdy Mubarak, Qatar Computing Research Institute, Qatar
  8. Assessing Arabic Weblog Credibility via Deep Co-learning, Authors: Chadi Helwe, Shady Elbassuoni, Ayman Al Zaatari and Wassim El Hajj, (P)
    • Presenter: Wassim El-Hajj, American University of Beirut, Lebanon
  9. Homograph Disambiguation Through Selective Diacritic Restoration, Authors: Sawsan Alqahtani, Hanan Aldarmaki and Mona Diab, (O)
    • Presenter: Mona Diab, AWS, Amazon AI and The George Washington University , USA
  10. Morphology-aware Word-Segmentation in Dialectal Arabic Adaptation of Neural Machine Translation, Authors: Ahmed Tawfik, Mahitab Emam, Khaled Essam, Robert Nabil and Hany Hassan, (O)
    • Presenter: Ahmed Tawfik, Microsoft
  11. Morphologically Annotated Corpora for Seven Arabic Dialects: Taizi, Sanaani, Najdi, Jordanian, Syrian, Iraqi and Moroccan, Authors: Faisal Alshargi, Shahd Dibas, Sakhar Alkhereyf, Reem Faraj, Basmah Abdulkareem, Sane Yagi, Ouafaa Kacha, Nizar Habash and Owen Rambow, (P)
    • Presenter: Nizar Habash, NYUAD, UAE
  12. Construction and Annotation of the Jordan Comprehensive Contemporary Arabic Corpus (JCCA), Authors: Majdi Sawalha, Faisal ALSHARGI, Abdallah AlShdaifat, Sane Yagi and Mohammad A. Qudah, (P)
    • Presenter: Majdi Shaker Sawalha, Computer Information Systems Department, The University of Jordan, Amman, Jordan
  13. Translating Between Morphologically Rich Languages: An Arabic-to-Turkish Machine Translation System, Authors: İlknur Durgar El-Kahlout, Emre Bektaş, Naime Şeyma Erdem and Hamza Kaya, (P)
    • Presenter: İlknur Durgar El-Kahlout- TUBITAK
  14. Improved Generalization of Arabic Text Classifiers, Authors: Alaa Khaddaj, Hazem Hajj and Wassim El-Hajj, (P)
    • Presenter: Obeida Eljundi, American University of Beirut
  15. Arabic Named Entity Recognition: What Works and What’s Next, Authors: Liyuan Liu, Jingbo Shang and Jiawei Han, (O)
    • Presenter: Liyuan Liu, University of Illinois at Urbana Champaign, USA
  16. OSIAN: Open Source International Arabic News Corpus - Preparation and Integration into the CLARIN-infrastructure, Authors: Imad Zeroual, Dirk Goldhahn, Thomas Eckart and Abdelhak Lakhouaja, (P)
    • Presenter: Dirk Goldhahn, Natural Language Processing Group, Department of Computer Science, University of Leipzig, Leipzig, Germany
  17. Incremental Domain Adaptation for Neural Machine Translation in Low-Resource Settings, Authors: Marimuthu Kalimuthu, Michael Barz and Daniel Sonntag, (O)
    • Presenter: Marimuthu Kalimuthu, Research Assistant/DFKI, Saarland Informatics Campus OR Michael Barz, Researcher, PhD candidate DFKI, Saarland Informatics Campus
  18. ArbEngVec : An Arabic-English Cross-Lingual Word Embeddings Models, Authors: Raki Lachraf, El Moatez Billah Nagoudi, Youcef Ayachi, Ahmed Abdelali and Didier Schwab, (O)
    • Presenter: Ahmed Abdelali, QCRI, Qatar
  19. Arabic Tweet-Act: Speech Act Recognition for Arabic Asynchronous Conversations, Authors: Bushra Algotiml, AbdelRahim Elmadany and Walid Magdy, (P)
    • Presenter: Ibrahim Abu Farha, Institute for Language, Cognition and Computation, University of Edinburgh
  20. hULMonA: The Universal Language Model in Arabic, Authors: Obeida ElJundi, Wissam Antoun, Nour El Droubi, Hazem Hajj, Wassim El-Hajj and Khaled Shaban, (O)
    • Presenter: Obeida Eljundi, American University of Beirut
  21. Mazajak: An Online Arabic Sentiment Analyser, Authors: Ibrahim Abu Farha and Walid Magdy, (P)
    • Presenter: Ibrahim Abu Farha, Institute for Language, Cognition and Computation, University of Edinburgh
  22. The MADAR Shared Task on Arabic Fine-Grained Dialect Identification, Authors: Houda Bouamor, Sabit Hassan and Nizar Habash, (O)
    • Presenter: Nizar Habash, NYUAD, UAE

MADAR Shared Task Accepted Short Papers

  1. ZCU-NLP at MADAR 2019: Recognizing Arabic Dialects, Authors: Pavel Přibáň and Stephen Taylor
  2. Simple but not Na ̈ıve: Fine-Grained Arabic Dialect Identification using only N-Grams, Authors: Sohaila Eltanbouly, May Bashendy and Tamer Elsayed
  3. LIUM-MIRACL Participation in the MADAR Arabic Dialect Identification Shared Task, Authors: Saméh KCHAOU, Fethi Bougares and Lamia Hadrich-Belguith
  4. Arabic Dialect Identification with Deep learning and Hybrid Frequency Based Features, Authors: Youssef Fares, Zeyad El-Zanaty, Kareem Abdel-Salam, Muhammed Ezzeldin, Aliaa Mohamed, Karim El-Awaad and Marwan Torki
  5. MICHAEL: Mining Character-level Patterns for Arabic Dialect Identification (MADAR Challenge), Authors: GHOUL dhaou and Gaël Lejeune
  6. Arabic Dialect Identification for Travel and Twitter Text, Authors: Pruthwik Mishra and Vandan Mujadia
  7. Mawdoo3 AI at MADAR Shared Task: Arabic Tweet Dialect Identification, Authors: Bashar Talafha, Wael Farhan, Ahmed Altakrouri and Hussein Al-Natsheh
  8. Mawdoo3 AI at MADAR Shared Task: Arabic Fine-Grained Dialect Identification with Ensemble Learning, Authors: Ahmad Ragab, Haitham Seelawi, Mostafa Samir, Abdelrahman Mattar, Hesham Al-Bataineh, Mohammad Zaghloul, Ahmad Mustafa, Bashar Talafha, Abed Alhakim Freihat and Hussein Al-Natsheh
  9. Hierarchical Deep Learning for Arabic Dialect Identification, Authors: Gael de Francony, Victor Guichard, Praveen Joshi, Haithem Afli and Abdessalam Bouchekif
  10. ArbDialectID at MADAR Shared Task 1: Language Modelling and Ensemble Learning for Fine Grained Arabic Dialect Identification, Authors: Chatrine Qwaider and Motaz Saad
  11. The SMarT Classifier for Arabic Fine-Grained Dialect Identification, Authors: Karima Meftouh, Karima Abidi, Salima Harrat and Kamel Smaili
  12. JHU System Description for the MADAR Arabic Dialect Identification Shared Task, Authors: Tom Lippincott, Pamela Shapiro, Kevin Duh and Paul McNamee
  13. ST MADAR 2019 Shared Task: Arabic Fine-Grained Dialect Identification, Authors: Mourad Abbas, Mohamed Lichouri and Abed Alhakim Freihat
  14. A Character Level Convolutional BiLSTM for Arabic Dialect Identification, Authors: Mohamed Elaraby and Ahmed Zahran
  15. No Army, No Navy: BERT Semi-Supervised Learning of Arabic Dialects, Authors: Chiyu Zhang and Muhammad Abdul-Mageed
  16. Team JUST at the MADAR Shared Task on Arabic Fine-Grained Dialect Identification, Authors: Bashar Talafha, Ali Fadel, Mahmoud Al-Ayyoub, Yaser Jararweh, Mohammad AL-Smadi and Patrick Juola
  17. QC-GO Submission for MADAR Shared Task: Arabic Fine-Grained Dialect Identification, Authors: Younes Samih, Hamdy Mubarak, Ahmed Abdelali, Mohammed Attia, Mohamed Eldesouki and Kareem Darwish

Poster Preparation Guide

  • Dimensions: A0 landscape
  • A poster has to attract people: the main idea and the main findings should be clear even if you look at it during only 1 mn.
  • A poster is a base for a discussion, prepare a speech (about 2-5 mn) that goes quickly through the poster (main problem, main results), people will ask further details about what they are more interested in.
  • Font: the title should be readable from about 3-5 meters, the rest from about 1-2 meter.
  • It’s generally easier to keep a traditional reading path (left to right, up to bottom), either by columns or by raws, to ensure readability.
  • The sections generally follow the paper: a first frame about the motivations (what is the problem, why it is interesting) that may be based on an example, then the approach and the contributions, and then the experiments, the results and a conclusion (possibly acknowledgements and references, but not mandatory. No abstract.).
  • Time for networking: always give your name to people coming to see your poster, and try to ask their name and affiliation: you’re also there to meet people, and the people coming to see you are interested in your work, so you probably have things in common.
  • Come with at least one printed version of your paper, to be able to refer to it if needed.
  • If you can, print your poster on a fabric: you can fold it in your bag!
  • If you use LateX, tikzposter provides many ready-to-use templates, see the guide.
  • Many useful tips here, also some pieces of advice here and here.
  • See some examples made by the WiNLP chairs here, here (see the original powerpoint file), here (get the source files on Overleaf), and here.


Extracted from: http://www.winlp.org/winlp-2019-workshop/poster-slides-tips/