聚焦低资源语言的模型研究，推动NLP领域语言包容性
Overview of the First Workshop on Language Models for Low-Resource Languages (LoResLM 2025)
- 组织研讨会促交流，聚焦低资源语言的模型开发
- 收录35篇论文，覆盖8个语系13个研究方向
- 适合关注语言公平与小语种NLP的研究者
首届低资源语言语言模型研讨会（LoResLM 2025）于阿联酋阿布扎比举行的第31届国际计算语言学会议（COLING 2025）期间举办。研讨会旨在为研究人员提供平台，分享和讨论针对低资源语言的语言模型（LMs）相关工作，回应近年来神经语言模型在高资源语言上的语言偏见问题。本次研讨会受到自然语言处理（NLP）领域的广泛关注，共收到52篇投稿，录用35篇。论文涵盖来自8个语言家族、13个不同研究方向的低资源语言，为未来研究开辟新路径，助力NLP领域的语言多样性与包容性发展。
原文摘要 · Abstract (English)
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.
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