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    <abstract>Tibetan, spoken by some seven million people on and around the Qinghai-Xizang Plateau, remains underrepresented in natural language processing (NLP). We present, to our knowledge, the first peer-reviewed systematic bibliometric survey of Tibetan NLP: 140 publications from 2004 to 2026 in the ACL Anthology and DBLP, annotated for venue type, research area, first-affiliation country, and resource release. Output has grown rapidly, with 84% of the publications appearing since 2018, and has expanded bottom-up along the NLP pipeline, from corpora and word segmentation through script, speech, and applications to large language models (LLMs). Researchers based in China first-authored 87% of the publications, which span all 25 represented research areas, whereas work from other countries concentrates on Classical Tibetan. We argue that this full-pipeline paradigm, realized under the compounded constraints of a complex script, dialectal diversity, and geographic remoteness, offers a reference model for other low-resource languages of the Global South. We also identify gaps in dialect coverage, responsible NLP, native and comparable evaluation, cross-community visibility, and resource release (only 29% of the publications release data, code, or models), and recommend open science, shared standards, and community participation for the LLM era.</abstract>
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%0 Conference Proceedings
%T Towards the Roof of the World: NLP Progress in Tibetan Languages
%A Cao, Xi
%A Li, Yijie
%A Sun, Yuan
%A Dong, Shiwei
%A Huang, Zeguang
%A Qun, Nuo
%Y Zhang, Yue
%Y Xu, Ruifeng
%Y Purwarianti, Ayu
%Y Rong, Tong
%Y Suzuki, Jun
%S Findings of the Association for Computational Linguistics: IJCNLP-AACL 2026
%D 2026
%8 November
%I Association for Computational Linguistics
%C Hengqin, China
%@ 979-8-89176-444-6
%F cao-etal-2026-towards
%X Tibetan, spoken by some seven million people on and around the Qinghai-Xizang Plateau, remains underrepresented in natural language processing (NLP). We present, to our knowledge, the first peer-reviewed systematic bibliometric survey of Tibetan NLP: 140 publications from 2004 to 2026 in the ACL Anthology and DBLP, annotated for venue type, research area, first-affiliation country, and resource release. Output has grown rapidly, with 84% of the publications appearing since 2018, and has expanded bottom-up along the NLP pipeline, from corpora and word segmentation through script, speech, and applications to large language models (LLMs). Researchers based in China first-authored 87% of the publications, which span all 25 represented research areas, whereas work from other countries concentrates on Classical Tibetan. We argue that this full-pipeline paradigm, realized under the compounded constraints of a complex script, dialectal diversity, and geographic remoteness, offers a reference model for other low-resource languages of the Global South. We also identify gaps in dialect coverage, responsible NLP, native and comparable evaluation, cross-community visibility, and resource release (only 29% of the publications release data, code, or models), and recommend open science, shared standards, and community participation for the LLM era.
%U https://aclanthology.org/2026.findings-aacl.56/
%P 1088-1119

Markdown (Informal)

[Towards the Roof of the World: NLP Progress in Tibetan Languages](https://aclanthology.org/2026.findings-aacl.56/) (Cao et al., Findings 2026)

• Towards the Roof of the World: NLP Progress in Tibetan Languages (Cao et al., Findings 2026)

ACL

• Xi Cao, Yijie Li, Yuan Sun, Shiwei Dong, Zeguang Huang, and Nuo Qun. 2026. Towards the Roof of the World: NLP Progress in Tibetan Languages. In Findings of the Association for Computational Linguistics: IJCNLP-AACL 2026, pages 1088–1119, Hengqin, China. Association for Computational Linguistics.