Paper Submission Guidelines

Paper Format

• Papers are expected to be up to 4 pages with unlimited references. Note that the review process is not double blind, so anonymity is not required.

• Papers must follow the Official EMNLP 2025 (ACL) style templates (LaTeX or Word)

• The templates can be downloaded from: https://github.com/acl-org/acl-style-files

• Non-conforming submissions (wrong paper size, margins, font size) will be rejected without review

• Generally speaking, shared task description papers should have the following format:

  • Abstract: Brief summary of your paper in a few sentences.

  • Introduction: ¾ a page expanding on the abstract mentioning key background such as why the task is challenging for current modeling techniques and why your approach is interesting/novel.

  • Background: Summarize the task setup and maybe add input/ouput examples if needed. Make sure to mention the track(s) you participate in. Make sure to also cite relevant related work to highlight your contributions.

  • System Overview: Outlines the key algorithms, design decisions, and resources utilized in our system. Make sure to highlight how you addressed major task challenges and provide concrete algorithmic examples, including equations and configurations for different system variants.

  • Experimental Setup: a description of the data you use (i.e., train/dev/test splits) along with any preprocessing. You should also outline any hyperparameters for reproducibility along with the external tools/libraries, if you use any. You should also mention the the evaluation metrics summary. If you're tight on space, implementation details could go to the appendix.

  • Results: a description of the key results of the paper. If you have done extra error analysis into what types of errors the system makes, this is extremely valuable for the reader. Unofficial results from after the submission deadline can be very useful as well.

  • Conclusion: a restatement of the introduction, highlighting what was learned about the task and how to model it.

  • Appendices: Low-level details for replication that are not essential for understanding main contribution.

Paper Submission

• PAPER SUBMISSION LINK 

• Submissions should be made via OpenReview. Please ensure you have an OpenReview account set up if you have not done so already. The submission link will be provided soon.

• Please note that if you register to participate and request the dataset, you agree to submit a paper! It's not just encouraged, it's a binding commitment you make when receiving the data.

Required Citations

• BibTex:

  • shared task paper. Coming soon!

  • BAREC Readability Corpus:

@inproceedings{elmadani-etal-2025-readability,

    title = "A Large and Balanced Corpus for Fine-grained Arabic Readability Assessment",

    author = "Elmadani, Khalid N.  and

      Habash, Nizar  and

      Taha-Thomure, Hanada",

    booktitle = "Findings of the Association for Computational Linguistics: ACL 2025",

    year = "2025",

    address = "Vienna, Austria",

    publisher = "Association for Computational Linguistics"

}

• • BAREC Readability Annotation Guidelines:

@inproceedings{habash-etal-2025-guidelines,

    title = "Guidelines for Fine-grained Sentence-level Arabic Readability Annotation",

    author = "Habash, Nizar  and

      Taha-Thomure, Hanada  and

      Elmadani, Khalid N.  and

      Zeino, Zeina  and

      Abushmaes, Abdallah",

    booktitle = "Proceedings of the 19th Linguistic Annotation Workshop (LAW-XIX)",

    year = "2025",

    address = "Vienna, Austria",

    publisher = "Association for Computational Linguistics"

}

• SAMER Corpus:

@inproceedings{alhafni-etal-2024-samer,

    title = "The {SAMER} {A}rabic Text Simplification Corpus",

    author = "Alhafni, Bashar  and

Hazim, Reem  and

Pineros Liberato, Juan David  and

Al Khalil, Muhamed  and

Habash, Nizar",

    booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",

    year = "2025",

    address = "Torino, Italia",

    publisher = "ELRA and ICCL",

    pages = "16079--16093"

}

• Word:

  • shared task paper. Coming soon!

  • Elmadani, K. N., Habash, N., & Taha-Thomure, H. (2025). A Large and Balanced Corpus for Fine-grained Arabic Readability Assessment. Findings of ACL 2025.

  • Habash, N., Taha-Thomure, H., Elmadani, K. N., Zeino, Z., Abushmaes, A. (2025). Guidelines for Fine-grained Sentence-level Arabic Readability Annotation. LAW-XIX.

  • Alhafni, B., Hazim, R., Pineros Liberato, J. D., Al Khalil, M., Habash, N. (2024). The SAMER Arabic Text Simplification Corpus. LREC-COLING 2024.