mlsanityData to 7 Oct 2026

Toward More Meaningful Resources for Lower-resourced Languages

arXiv 2202.12288 ↗First posted 24 Feb 2022cs.CL cs.AIcited by 14

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Abstract (arXiv)

In this position paper, we describe our perspective on how meaningful resources for lower-resourced languages should be developed in connection with the speakers of those languages. We first examine two massively multilingual resources in detail. We explore the contents of the names stored in Wikidata for a few lower-resourced languages and find that many of them are not in fact in the languages they claim to be and require non-trivial effort to correct. We discuss quality issues present in WikiAnn and evaluate whether it is a useful supplement to hand annotated data. We then discuss the importance of creating annotation for lower-resourced languages in a thoughtful and ethical way that includes the languages' speakers as part of the development process. We conclude with recommended guidelines for resource development.

Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). Builds on 10 of its 21 references that are in the map. First posted on arXiv 24 Feb 2022.

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10 of 21 references.

References · 10

  1. 2020XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalizationcited by 738
  2. 2021Datasets: A Community Library for Natural Language Processingcited by 526
  3. 2021Dealing with Disagreements: Looking Beyond the Majority Vote in Subjective Annotationscited by 306
  4. 2021Quality at a Glance: An Audit of Web-Crawled Multilingual Datasetscited by 241
  5. 2020Participatory Research for Low-resourced Machine Translation: A Case Study in African Languagescited by 159
  6. 2021MasakhaNER: Named Entity Recognition for African Languagescited by 155
  7. 2021On Releasing Annotator-Level Labels and Information in Datasetscited by 123
  8. 2020Masakhane -- Machine Translation For Africacited by 48
  9. 2021SeqScore: Addressing Barriers to Reproducible Named Entity Recognition Evaluationcited by 8
  10. 2021Contextual Text Embeddings for Twicited by 1

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Citing papers per year: 2022: 3; 2023: 4; 2024: 6; 2025: 1.

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  1. 2024Aya Model: An Instruction Finetuned Open-Access Multilingual Language Modelcited by 292
  2. 2024Aya Dataset: An Open-Access Collection for Multilingual Instruction Tuningcited by 174
  3. 2023Universal NER: A Gold-Standard Multilingual Named Entity Recognition Benchmarkcited by 26
  4. 2022Exploring Predictive Uncertainty and Calibration in NLP: A Study on the Impact of Method & Data Scarcitycited by 24
  5. 2023BHASA: A Holistic Southeast Asian Linguistic and Cultural Evaluation Suite for Large Language Modelscited by 16
  6. 2022Intriguing Properties of Compression on Multilingual Modelscited by 15
  7. 2024Targeted Multilingual Adaptation for Low-resource Language Familiescited by 9
  8. 2024Constrained Decoding for Cross-lingual Label Projectioncited by 8
  9. 2023Towards Bridging the Digital Language Dividecited by 7
  10. 2022LR-Sum: Summarization for Less-Resourced Languagescited by 5
  11. 2023Diversity and Language Technology: How Techno-Linguistic Bias Can Cause Epistemic Injusticecited by 4
  12. 2024How Good is Your Wikipedia? Auditing Data Quality for Low-resource and Multilingual NLPcited by 3
2 more
  1. 2024Ethics Whitepaper: Whitepaper on Ethical Research into Large Language Modelscited by 1
  2. 2025Does Synthetic Data Help Named Entity Recognition for Low-Resource Languages?cited by 0