Overview of the First Workshop on Language Models for Low-Resource Languages (LoResLM 2025)

TL;DR

The LoResLM 2025 workshop showcased recent research on developing and improving language models for low-resource languages, emphasizing inclusivity and addressing linguistic biases in NLP.

Contribution

This workshop provided a dedicated forum for sharing advances in low-resource language modeling, highlighting diverse languages and research areas to foster inclusivity in NLP.

Findings

Attracted 35 papers from 52 submissions

Covered 8 language families and 13 research areas

Promoted linguistic inclusivity in NLP

Abstract

The first Workshop on Language Models for Low-Resource Languages (LoResLM 2025) was held in conjunction with the 31st International Conference on Computational Linguistics (COLING 2025) in Abu Dhabi, United Arab Emirates. This workshop mainly aimed to provide a forum for researchers to share and discuss their ongoing work on language models (LMs) focusing on low-resource languages, following the recent advancements in neural language models and their linguistic biases towards high-resource languages. LoResLM 2025 attracted notable interest from the natural language processing (NLP) community, resulting in 35 accepted papers from 52 submissions. These contributions cover a broad range of low-resource languages from eight language families and 13 diverse research areas, paving the way for future possibilities and promoting linguistic inclusivity in NLP.