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

arXiv: https://arxiv.org/abs/2412.16365 · HTML: https://mlsanity.com/paper/2412.16365/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 28 of its 64 references that are in the map.
- First posted on arXiv 20 Dec 2024.

## Builds on (most cited first, 28 of 28)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer](https://mlsanity.com/paper/1910.10683/) (2019)
- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [Llama 2: Open Foundation and Fine-Tuned Chat Models](https://mlsanity.com/paper/2307.09288/) (2023)
- [BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension](https://mlsanity.com/paper/1910.13461/) (2019)
- [Unsupervised Cross-lingual Representation Learning at Scale](https://mlsanity.com/paper/1911.02116/) (2019)
- [Mistral 7B](https://mlsanity.com/paper/2310.06825/) (2023)
- [BLOOM: A 176B-Parameter Open-Access Multilingual Language Model](https://mlsanity.com/paper/2211.05100/) (2022)
- [mT5: A massively multilingual pre-trained text-to-text transformer](https://mlsanity.com/paper/2010.11934/) (2020)
- [PhoBERT: Pre-trained language models for Vietnamese](https://mlsanity.com/paper/2003.00744/) (2020)
- [Systematic Inequalities in Language Technology Performance across the World's Languages](https://mlsanity.com/paper/2110.06733/) (2021)
- [Neural Machine Translation for Low-Resource Languages: A Survey](https://mlsanity.com/paper/2106.15115/) (2021)
- [Low-resource Languages: A Review of Past Work and Future Challenges](https://mlsanity.com/paper/2006.07264/) (2020)
- [Square One Bias in NLP: Towards a Multi-Dimensional Exploration of the Research Manifold](https://mlsanity.com/paper/2206.09755/) (2022)
- [Multi Task Learning For Zero Shot Performance Prediction of Multilingual Models](https://mlsanity.com/paper/2205.06130/) (2022)
- [BERTifying Sinhala -- A Comprehensive Analysis of Pre-trained Language Models for Sinhala Text Classification](https://mlsanity.com/paper/2208.07864/) (2022)
- [Atlas-Chat: Adapting Large Language Models for Low-Resource Moroccan Arabic Dialect](https://mlsanity.com/paper/2409.17912/) (2024)
- [BnSentMix: A Diverse Bengali-English Code-Mixed Dataset for Sentiment Analysis](https://mlsanity.com/paper/2408.08964/) (2024)
- [Controlled Evaluation of Syntactic Knowledge in Multilingual Language Models](https://mlsanity.com/paper/2411.07474/) (2024)
- [When Every Token Counts: Optimal Segmentation for Low-Resource Language Models](https://mlsanity.com/paper/2412.06926/) (2024)
- [NSINA: A News Corpus for Sinhala](https://mlsanity.com/paper/2403.16571/) (2024)
- [Recent Advancements and Challenges of Turkic Central Asian Language Processing](https://mlsanity.com/paper/2407.05006/) (2024)
- [Filipino Benchmarks for Measuring Sexist and Homophobic Bias in Multilingual Language Models from Southeast Asia](https://mlsanity.com/paper/2412.07303/) (2024)
- [Beyond Data Quantity: Key Factors Driving Performance in Multilingual Language Models](https://mlsanity.com/paper/2412.12500/) (2024)
- [Automated Collection of Evaluation Dataset for Semantic Search in Low-Resource Domain Language](https://mlsanity.com/paper/2412.10008/) (2024)
- [Empowering Persian LLMs for Instruction Following: A Novel Dataset and Training Approach](https://mlsanity.com/paper/2407.11186/) (2024)
- [Comparative Analysis of Static and Contextual Embeddings for Analyzing Semantic Changes in Medieval Latin Charters](https://mlsanity.com/paper/2410.09283/) (2024)

## Built on by (most cited first, 2 of 2)

- [Between Circuits and Chomsky: Pre-pretraining on Formal Languages Imparts Linguistic Biases](https://mlsanity.com/paper/2502.19249/) (2025)
- [Do LLMs Judge Distantly Supervised Named Entity Labels Well? Constructing the JudgeWEL Dataset](https://mlsanity.com/paper/2601.00411/) (2026)

## Abstract (arXiv)

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.