mlsanityData to 7 Oct 2026

The Zeno's Paradox of `Low-Resource' Languages

arXiv 2410.20817 ↗First posted 28 Oct 2024cs.CLcited by 12

Not on the map. Why?

Abstract (arXiv)

The disparity in the languages commonly studied in Natural Language Processing (NLP) is typically reflected by referring to languages as low vs high-resourced. However, there is limited consensus on what exactly qualifies as a `low-resource language.' To understand how NLP papers define and study `low resource' languages, we qualitatively analyzed 150 papers from the ACL Anthology and popular speech-processing conferences that mention the keyword `low-resource.' Based on our analysis, we show how several interacting axes contribute to `low-resourcedness' of a language and why that makes it difficult to track progress for each individual language. We hope our work (1) elicits explicit definitions of the terminology when it is used in papers and (2) provides grounding for the different axes to consider when connoting a language as low-resource.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 77 of its 175 references that are in the map. First posted on arXiv 28 Oct 2024.

Builds on

77 of 175 references.

References · 77

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  2. 2021The FLORES-101 Evaluation Benchmark for Low-Resource and Multilingual Machine Translationcited by 556
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38 more
  1. 2020UDapter: Language Adaptation for Truly Universal Dependency Parsingcited by 77
  2. 2020ERNIE-M: Enhanced Multilingual Representation by Aligning Cross-lingual Semantics with Monolingual Corporacited by 63
  3. 2019Generalized Data Augmentation for Low-Resource Translationcited by 53
  4. 2020Not Low-Resource Anymore: Aligner Ensembling, Batch Filtering, and New Datasets for Bengali-English Machine Translationcited by 53
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  10. 2023Making More of Little Data: Improving Low-Resource Automatic Speech Recognition Using Data Augmentationcited by 30
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  12. 2022Overlap-based Vocabulary Generation Improves Cross-lingual Transfer Among Related Languagescited by 25
  13. 2021Long Document Summarization in a Low Resource Setting using Pretrained Language Modelscited by 24
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  16. 2020Parameter Space Factorization for Zero-Shot Learning across Tasks and Languagescited by 22
  17. 2020Simulated Multiple Reference Training Improves Low-Resource Machine Translationcited by 22
  18. 2021MetaXL: Meta Representation Transformation for Low-resource Cross-lingual Learningcited by 21
  19. 2020Soft Gazetteers for Low-Resource Named Entity Recognitioncited by 20
  20. 2022Language-Agnostic Meta-Learning for Low-Resource Text-to-Speech with Articulatory Featurescited by 20
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 5; 2026: 6.

12 papers.

  1. 2025The State of Multilingual LLM Safety Research: From Measuring the Language Gap to Mitigating Itcited by 42
  2. 2025One ruler to measure them all: Benchmarking multilingual long-context language modelscited by 18
  3. 2026Tiny Aya: Bridging Scale and Multilingual Depthcited by 14
  4. 2025Trustworthy Machine Learning via Memorization and the Granular Long-Tail: A Survey on Interactions, Tradeoffs, and Beyondcited by 6
  5. 2024Low-resource Machine Translation: what for? who for? An observational study on a dedicated Tetun language translation servicecited by 5
  6. 2025Steering LLMs toward Korean Local Speech: Iterative Refinement Framework for Faithful Dialect Translationcited by 1
  7. 2025NaijaNLP: A Survey of Nigerian Low-Resource Languagescited by 0
  8. 2026What Makes a Good Doctor Response? A Study on Text-Based Telemedicinecited by 0
  9. 2026Which Are the Low-Resource Languages of the Semantic Web?cited by 0
  10. 2026In Data or Invisible: Toward a Better Digital Representation of Low-Resource Languages with Knowledge Graphscited by 0
  11. 2026Beyond Catalogue Counts: the Dataset Visibility Asymmetry in Low-Resource Multilingual NLPcited by 0
  12. 2026Sometin Beta Pass Notin: Improving Multilingual ASR for Nigerian Languages via Knowledge Distillationcited by 0