Call for Tutorial Proposals at EACL and ACL 2026: Focus on NLP and CL

Date:

Overview

The Association for Computational Linguistics (ACL) and the European Chapter of the ACL (EACL) are inviting proposals for tutorials to be held in conjunction with the upcoming ACL 2026 and EACL 2026 conferences. This initiative aims to enhance the understanding of computational linguistics (CL) and natural language processing (NLP) among researchers by addressing significant scientific challenges and their implications.

Background & Relevance

The fields of computational linguistics and natural language processing are rapidly evolving, with new methodologies and technologies emerging regularly. Tutorials play a crucial role in disseminating knowledge about these advancements, making them accessible to a broader audience. By fostering a deeper understanding of both foundational and cutting-edge topics, these tutorials can significantly contribute to the growth of the CL/NLP community. The emphasis on diversity and inclusion within tutorial proposals is particularly important, as it encourages a richer exchange of ideas and perspectives.

Key Details

  • Proposal Submission Deadline: October 20, 2025
  • Notification of Acceptance: December 08, 2025
  • Tutorial Dates:
  • EACL 2026: March 24-29, 2026, Rabat, Morocco
  • ACL 2026: July 2-7, 2026, San Diego, California
  • Format: Hybrid conferences
  • Fee Waivers: Up to 3 instructors per tutorial can have their registration fees waived.

Eligibility & Participation

This call for proposals is open to all researchers and educators interested in contributing to the fields of CL and NLP. The tutorials are designed for a diverse audience, including both newcomers and experienced professionals in the field. The organizers particularly encourage submissions from underrepresented groups to promote inclusivity within the community.

Submission or Application Guidelines

Proposals must adhere to the ACL paper submission format and should be submitted as PDF documents. Key components of the proposal include:
1. Title, authors, affiliations, and contact information.
2. A brief description of the tutorial content and its relevance.
3. Identification of the tutorial type: either cutting-edge in CL/NLP or introductory to related fields.
4. Target audience and any prerequisites for attendees.
5. An outline of the tutorial structure and content for a three-hour slot.
6. Inclusion of work by other researchers alongside the presenters’ work.
7. Considerations for diversity in content and participation.
8. A reading list for expected pre-tutorial preparation.
9. A paragraph on each presenter’s research interests and teaching experience.
10. An estimate of the expected audience size.
11. Any special technical requirements for the tutorial.
12. An ethics statement regarding the tutorial topics.
13. Limitations that may restrict the tutorial to a specific venue.
14. Optional: Alignment with special conference themes or inclusion of pedagogical materials.

Proposals should be submitted online via the softconf system at this link.

More Information

The tutorials at EACL and ACL 2026 will serve as a platform for sharing knowledge and fostering collaboration among researchers in computational linguistics and natural language processing. By addressing both cutting-edge and foundational topics, these tutorials can enhance the overall quality of research and application in the field. The emphasis on diversity and inclusion is essential for ensuring a balanced representation of ideas and experiences.

Conclusion

Researchers and educators are encouraged to submit their tutorial proposals for EACL and ACL 2026. This is an excellent opportunity to contribute to the advancement of the CL/NLP community while promoting diversity and inclusion. For further inquiries, please contact the tutorial chairs via email at eaclacl2026_tutorials@googlegroups.com.


Category: CFP & Deadlines
Tags: nlp, computational linguistics, acl, eacl, tutorials, machine learning, human-computer interaction, bioinformatics, diversity, inclusion, large language models, tutorial proposals

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