Important Dates

  • 16 February, 2026
    Paper Submission Deadline
  • 16 March, 2026
    Notification of Acceptance
  • 30 March, 2026
    Camera-ready Papers Due
  • 11-16 May, 2026
    Workshop Dates

Note: All deadlines are 11:59 PM UTC-12:00 ("anywhere on Earth").


Submission Portal(Not available at the moment)

Templates:

The workshop proceedings will be part of the ACL anthology. All submissions should follow the LREC style guidelines. We strongly recommend the use of the LaTeX style files, OpenDocument, or Microsoft Word templates created for LREC: Templates All papers must be anonymous, i.e., not reveal author(s) on the title page or through self-references. So, e.g., “We previously showed (Smith, 2020)”, should be avoided. Instead, use citations such as “Smith (2020) previously showed”.

Submission Guidelines

Papers

Submissions should be 4 to 8 pages in length and follow the LREC stylesheet.

The maximum number of pages excludes potential ethics Statements and discussion on limitations, acknowledgements and references, as well as data and code availability statements.
Appendices or supplementary material are not permitted during the initial submission phase, as papers should be self-contained and reviewable on their own.

We invite the following types of submissions:

  • Original research contributions
  • Substantial empirical evaluations
  • Comprehensive literature reviews
  • In-depth analyses of gaze data in NLP contexts
  • Position papers
  • Ongoing research
  • Preliminary results
  • Demonstration of systems
  • Dataset descriptions

Ethics Statement and Limitations Section

We encourage all authors submitting to Gaze4NLP 2026 to include an explicit ethics statement on the broader impact of their work, or other ethical considerations after the conclusion but before the references. The ethics statement will not count toward the page limit

LRE-Map and Sharing Language Resources

When submitting a paper from the START page, authors will be asked to provide essential information about resources (in a broad sense, i.e. also technologies, standards, evaluation kits, etc.) that have been used for the work described in the paper or are a new result of your research. Moreover, ELRA encourages all LREC authors to share the described LRs (data, tools, services, etc.) to enable their reuse and replicability of experiments (including evaluation ones).

Reviewing Process

The reviewing process will be blind. The papers must not include the authors' names and affiliations, neither self-references that reveal the authors' identity. Please avoid "We previously proved (James, 2025) ...", and use instead citations such as "James previously proved (James 2025)...". Papers that do not conform with these requirements will be rejected without review.

Camera-ready Papers and Presentations

  • Please note that camera-ready papers are allowed an additional page.
  • Accepted papers will also be given an opportunity with an extended version to be published as part of an edited book.
  • Accepted papers will be presented in the form of either oral or poster presentations.
  • Frequently Asked Questions

    Can I submit a paper that has been previously published elsewhere? +

    No, submissions must be original and should not have been published elsewhere or be under review at another venue at the time of submission.

    Is it necessary to include eye-tracking data in my submission? +

    Not necessarily. We also welcome papers that discuss methodological approaches, theoretical frameworks, or applications related to the integration of eye-tracking and NLP, even if they don't include new eye-tracking data.

    Is funding available for young researchers? +

    Yes, we have a limited number of funding opportunities available through the MULTIPLEYE COST Action. If you would like to inquire about these opportunities, please do not hesitate to email us at gaze4nlp@gmail.com.

    Contact Information

    For any questions regarding submissions or the workshop, please contact the organizing committee at gaze4nlp@gmail.com