Paper Submission Guidelines
System description papers should explain what your team built, how it was trained and evaluated, and what the results reveal about the task. Keep the paper concise, reproducible, and analysis-focused.
New: ArabicNLP ran a webinar on writing a strong system description paper, presented by Dr Usman Naseem. Watch the recording before you start writing.
Paper length Maximum 4 pages
Unlimited pages for references and appendix.
Required template EMNLP 2026 / ACL style
LaTeX or Word templates.
Deadlines Camera-ready: September 10
System description form: August 15.
Where to submit OpenReview
Create your account early, verification takes a few days.
Title format Team at ImageEval
<Team Name> at ImageEval 2026 Shared Tasks: <Your Contribution>
Key Principles
Replicability
Provide enough implementation detail for another researcher to reproduce the system.
Analysis
Emphasize results, error patterns, ablations, and design decisions rather than only rankings.
Clarity
Briefly describe the task setup, but do not duplicate the task overview paper.
Required Elements
- Cite the task overview paper.
- Follow the EMNLP/ACL templates exactly.
- Use the required title format:
<Team Name> at ImageEval 2026 Shared Tasks: <Your Contribution>. - Clearly state which task(s) and track(s) your team participated in.
- Describe external data, tools, APIs, or models used beyond the released task data.
- Distinguish official submitted results from post-submission experiments.
For popular algorithms, citation is usually sufficient. Full mathematical detail is only needed when it is central to your contribution. Move detailed hyperparameters and low-level implementation details to the appendix when space is limited.
Recommended Paper Structure
1. Abstract
Briefly summarize the task, your approach, and the main results in a few sentences.
2. Introduction
- Describe the task and why it matters.
- Mention the language varieties and track(s) covered.
- Cite the task overview paper.
- Summarize your main system strategy.
- Highlight key findings, ranking, and challenges discovered.
- Include a code URL if available.
3. Background
- Summarize the task setup, including input and output types.
- Describe dataset details such as language, genre, and size.
- State the tracks you participated in.
- Cite related work and explain what is different about your system.
4. System Overview
- Explain key algorithms and design decisions.
- List resources used beyond the provided training data.
- Describe how your system addressed task-specific challenges.
- Include equations or pseudocode for novel methods.
- Clearly distinguish multiple configurations or submitted runs.
5. Experimental Setup
- Explain how train, development, and test splits were used.
- Provide preprocessing details and hyperparameters needed for replication.
- List external tools and libraries with versions and URLs.
- Summarize the official evaluation metrics.
- Put low-level details in the appendix if space is limited.
6. Results and Analysis
- Report official metric performance and ranking.
- Include ablations, comparisons, and design-decision analysis where possible.
- Provide error analysis with representative examples.
- Clearly mark which data split is used for each analysis.
- Distinguish official results from post-submission results.
7. Conclusion
Summarize the system, limitations, results, and future work.
8. Acknowledgments
Thank contributors, grants, infrastructure providers, and reviewers where appropriate.
9. Appendix
Use the appendix for low-level replication details that are useful but not essential to the main paper.
Formatting
- Use the official EMNLP 2026 / ACL style templates in LaTeX.
- ACL style-files repository: github.com/acl-org/acl-style-files
- Overleaf template: Association for Computational Linguistics (ACL) conference template
- Authors should follow the general ACL formatting requirements.
- Do not modify style files or use templates from other conferences.
Submissions with non-conforming paper size, margins, or font size may be rejected without review.
Author Information and Review
ImageEval system description papers are not submitted anonymously. Authors should include their names, affiliations, and contact information in the submitted paper.
The papers will be reviewed to ensure that they:
- provide an adequate description of the submitted system;
- report the experimental setup and results clearly;
- follow the required paper format;
- include appropriate analysis or discussion;
- cite the ImageEval overview and dataset papers; and
- meet the basic standards required for inclusion in the proceedings.
A high leaderboard rank is not required for paper acceptance. The quality and clarity of the system description, analysis, and scientific discussion will be considered during review.
Paper Submission
Papers must be submitted through OpenReview, on the ImageEval shared task venue:
openreview.net/group?id=SIGARAB.org/ArabicNLP/2026/ImageEval_Shared_Task
Paper submission closed on August 19, 2026. Reviews and acceptance notifications were released on August 31, and camera-ready papers are due September 10, 2026 through the same OpenReview venue.
Before submitting, please confirm that:
- the paper uses the official ACL template;
- the paper contains no more than four pages of main content;
- the title follows the required naming format;
- all authors and affiliations are included;
- all external data and resources are disclosed;
- the official ImageEval papers are cited; and
- the submitted PDF opens and displays correctly.
Camera-ready Version
Camera-ready papers are due September 10, 2026 through the same OpenReview venue.
- Address the reviews. Revise your paper to incorporate the changes requested by your reviewers; where a request is not feasible, do your best to accommodate it. This is expected for the final version.
- Length. Camera-ready papers may use up to 5 content pages (one extra page over the submission limit, to accommodate revisions), with unlimited pages for references and appendix.
- De-anonymize. Add author names, affiliations, and any acknowledgments.
- Cite the required papers. See the mandatory citations in the task repository.
ACL PubCheck for Camera-ready
All camera-ready papers must be checked using ACL PubCheck before final submission. ACL PubCheck automatically identifies common formatting problems involving margins, fonts, page dimensions, spacing, and other ACL publication requirements. Authors are also encouraged to run PubCheck before the initial paper submission.
PubCheck Resources
- GitHub repository: github.com/acl-org/aclpubcheck
- Google Colab: Run ACL PubCheck in Google Colab
- Hugging Face interface: ACL PubCheck on Hugging Face Spaces
Please address all relevant PubCheck errors before submitting the camera-ready paper. Warnings should also be reviewed carefully.
Required Citations
System description papers must cite:
- the ImageEval shared-task overview paper; and
- the relevant ImageEval dataset papers.
Please find the BibTeX entries for the overview and dataset papers below.
@inproceedings{imageeval-2026,
title = "{ImageEval 2026}: Culturally Grounded {A}rabic
Multimodal Evaluation",
author = {Abdaljalil, Samir and
Bhatti, Hunzalah Hassan and
Bashiti, Ahlam and
Amir, Farina and
Hasan, Md Arid and
Mousi, Basel and
Durrani, Nadir and
Dalvi, Fahim and
Sheikh Ali, Zien and
Serpedin, Erchin and
Kurban, Hasan and
Jarrar, Mustafa and
Chowdhury, Shammur Absar and
Alam, Firoj},
booktitle = {Proceedings of the Fourth Arabic Natural Language
Processing Conference: Shared Tasks},
month = oct,
year = {2026},
address = {Budapest, Hungary},
publisher = {Association for Computational Linguistics}
}
@article{alam2025everydaymmqa,
title = "{OASIS}: A Multilingual and Multimodal Dataset for
Culturally Grounded Spoken Visual {QA}",
author = {Alam, Firoj and
Shahroor, Ali Ezzat and
Hasan, Md. Arid and
Ali, Zien Sheikh and
Bhatti, Hunzalah Hassan and
Kmainasi, Mohamed Bayan and
Chowdhury, Shammur Absar and
Mousi, Basel and
Dalvi, Fahim and
Durrani, Nadir and
Milic-Frayling, Natasa},
journal = {arXiv preprint arXiv:2510.06371},
year = {2025}
}
@inproceedings{mousi-etal-2026-correct,
title = {Once Correct, Still Wrong: Counterfactual Hallucination
in Multilingual Vision-Language Models},
author = {Mousi, Basel and
Dalvi, Fahim and
Chowdhury, Shammur Absar and
Alam, Firoj and
Durrani, Nadir},
editor = {Liakata, Maria and
Moreira, Viviane P. and
Zhang, Jiajun and
Jurgens, David},
booktitle = {Findings of the {A}ssociation for {C}omputational
{L}inguistics: {ACL} 2026},
month = jul,
year = {2026},
address = {San Diego, California, United States},
publisher = {Association for Computational Linguistics},
url = {https://aclanthology.org/2026.findings-acl.234/},
doi = {10.18653/v1/2026.findings-acl.234},
pages = {4763--4788},
isbn = {979-8-89176-395-1}
}
@inproceedings{mousi2026said,
title = {Said Aloud, Read Different: Cross-Modal Instability
in Multimodal Models},
author = {Mousi, Basel and
Dalvi, Fahim and
Chowdhury, Shammur and
Alam, Firoj and
Durrani, Nadir},
booktitle = {Proceedings of Interspeech 2026},
year = {2026},
address = {Sydney, Australia},
note = {Accepted}
}
Information Required for the Overview Paper
The ImageEval 2026 organizers will publish an overview paper summarizing the shared task, participating teams, submitted methods, and official results.
Each participating team must provide:
- the team name;
- participating subtasks;
- a short description of the system;
- models and external resources used;
- the official submission results;
- authors and affiliations; and
- the BibTeX entry for the system description paper.
Please submit this information using the following form:
ImageEval 2026 system description form by August 15, 2026
System Paper BibTeX Template
Please replace the placeholders with your paper information.
@inproceedings{imageeval-2026-team-name,
author = {Last-Name, First-Name and
Last-Name, First-Name},
title = "{Team Name} at {ImageEval 2026 Shared Tasks}:
Title of the Paper",
booktitle = {Proceedings of the Fourth Arabic Natural Language
Processing Conference: Shared Tasks},
address = {Budapest, Hungary},
month = oct,
year = {2026},
publisher = {Association for Computational Linguistics}
}
Use a short and unique citation key based on your team name. Please ensure that the author names and paper title exactly match the submitted paper.
Leaderboards
Official standings for all tasks and tracks are on the Leaderboard page.
Call for Reviewers
Researchers who have previously published at *ACL conferences and are interested in serving as reviewers for the shared-task proceedings are invited to complete the following form: https://forms.gle/Deg6QdwsuF6aFX2X9