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. LoResLM aims to provide a forum for researchers to share and discuss their ongoing work on LMs for low-resource languages. 

>> Topics

LoResLM 2025 invites submissions on a broad range of topics related to the development and evaluation of neural language models for low-resource languages, including but not limited to the following. 
>> Important Dates
>> Submission Guidelines

We follow the COLING 2025 standards for submission format and guidelines. LoResLM 2025 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 COLING 2025 style files available here: 
Papers should be submitted through Softconf/START using the following link: https://softconf.com/coling2025/LoResLM25/ 
>> Organising Committee
URL - https://loreslm.github.io/ 
Twitter - https://x.com/LoResLM2025 

Best Regards
Tharindu Ranasinghe