Important Dates

Paper submission due January 6 (Tue), 2026
Notification of acceptance January 28 (Wed), 2026
Camera-ready due February 3 (Thu), 2026
Workshop March 28, 2026- March 29, 2026 (TBD) co-located with EACL 2026
* These dates are approximate dates based on EACL 2026 and are subject to changes.

First Call for Papers

Neural language models have revolutionised natural language processing (NLP) and have provided state-of-the-art results for many tasks. However, their effectiveness is largely dependent on the pre-training resources. Therefore, language models (LMs) often struggle with low-resource languages in both training and evaluation. Recently, there has been a growing trend in developing and adopting LMs for low-resource languages. Supporting this important shift, LoResLM aims to provide a forum for researchers to share and discuss their ongoing work on LMs for low-resource languages.

Topics

LoResLM 2026 invites submissions on a broad range of topics related to the development and evaluation of neural language models for low-resource languages. We welcome research that explores modalities beyond text and encourage work on low-resource dialects in addition to major language varieties. Topics of interest include, but are not limited to:

Submission Guidelines

We follow the EACL 2026 standards for submission format and guidelines. LoResLM 2026 invites the submission of long papers of up to eight pages and short papers of up to four pages. These page limits only apply to the main body of the paper. At the end of the paper (after the conclusions but before the references) papers need to include a mandatory section discussing the limitations of the work and, optionally, a section discussing ethical considerations. Papers can include unlimited pages of references and an unlimited appendix.

To prepare your submission, please make sure to use the EACL 2026 style files available here:

Papers should be submitted through OpenReview using the following link: https://openreview.net/group?id=eacl.org/EACL/2026/Workshop/LoResLM