mlsanityData to 14 Oct 2026

What a Creole Wants, What a Creole Needs

arXiv 2206.00437 ↗First posted 1 Jun 2022cs.CL cs.CYcited by 27

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Abstract (arXiv)

In recent years, the natural language processing (NLP) community has given increased attention to the disparity of efforts directed towards high-resource languages over low-resource ones. Efforts to remedy this delta often begin with translations of existing English datasets into other languages. However, this approach ignores that different language communities have different needs. We consider a group of low-resource languages, Creole languages. Creoles are both largely absent from the NLP literature, and also often ignored by society at large due to stigma, despite these languages having sizable and vibrant communities. We demonstrate, through conversations with Creole experts and surveys of Creole-speaking communities, how the things needed from language technology can change dramatically from one language to another, even when the languages are considered to be very similar to each other, as with Creoles. We discuss the prominent themes arising from these conversations, and ultimately demonstrate that useful language technology cannot be built without involving the relevant community.

Key facts. Cited by 27 papers in the map (data through 14 Oct 2026). Builds on 19 of its 71 references that are in the map. First posted on arXiv 1 Jun 2022.

Builds on

19 of 71 references.

References · 19

  1. 2018XNLI: Evaluating Cross-lingual Sentence Representationscited by 915
  2. 2020The State and Fate of Linguistic Diversity and Inclusion in the NLP Worldcited by 798
  3. 2019On the Cross-lingual Transferability of Monolingual Representationscited by 578
  4. 2021Visually Grounded Reasoning across Languages and Culturescited by 189
  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. 2019Distributionally Robust Language Modelingcited by 143
  8. 2020Translation Artifacts in Cross-lingual Transfer Learningcited by 96
  9. 2022NaijaSenti: A Nigerian Twitter Sentiment Corpus for Multilingual Sentiment Analysiscited by 64
  10. 2020Mind Your Inflections! Improving NLP for Non-Standard Englishes with Base-Inflection Encodingcited by 22
  11. 2021A Large-Scale Study of Machine Translation in the Turkic Languagescited by 21
  12. 2021On Language Models for Creolescited by 17
7 more
  1. 2020Semantic Enrichment of Nigerian Pidgin English for Contextual Sentiment Classificationcited by 12
  2. 2019PidginUNMT: Unsupervised Neural Machine Translation from West African Pidgin to Englishcited by 11
  3. 2017Universal Dependencies Parsing for Colloquial Singaporean Englishcited by 10
  4. 2021NaijaNER : Comprehensive Named Entity Recognition for 5 Nigerian Languagescited by 10
  5. 2020Towards Supervised and Unsupervised Neural Machine Translation Baselines for Nigerian Pidgincited by 8
  6. 2020Towards End-to-End Training of Automatic Speech Recognition for Nigerian Pidgincited by 6
  7. 2017Developing a concept-level knowledge base for sentiment analysis in Singlishcited by 5

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 2; 2023: 5; 2024: 9; 2025: 8; 2026: 3.

27 papers.

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  1. 2023Language Model Tokenizers Introduce Unfairness Between Languagescited by 214
  2. 2024Aya Dataset: An Open-Access Collection for Multilingual Instruction Tuningcited by 177
  3. 2024RLHF Can Speak Many Languages: Unlocking Multilingual Preference Optimization for LLMscited by 43
  4. 2023A Material Lens on Coloniality in NLPcited by 21
  5. 2024What Do Dialect Speakers Want? A Survey of Attitudes Towards Language Technology for German Dialectscited by 21
  6. 2023A Survey of Corpora for Germanic Low-Resource Languages and Dialectscited by 16
  7. 2025The AI Gap: How Socioeconomic Status Affects Language Technology Interactionscited by 15
  8. 2022JamPatoisNLI: A Jamaican Patois Natural Language Inference Datasetcited by 11
  9. 2024Krey`ol-MT: Building MT for Latin American, Caribbean and Colonial African Creole Languagescited by 10
  10. 2023CreoleVal: Multilingual Multitask Benchmarks for Creolescited by 9
  11. 2023How Good are Commercial Large Language Models on African Languages?cited by 8
  12. 2024Does Generative AI speak Nigerian-Pidgin?: Issues about Representativeness and Bias for Multilingualism in LLMscited by 5
15 more
  1. 2024Low-resource Machine Translation: what for? who for? An observational study on a dedicated Tetun language translation servicecited by 5
  2. 2024Building Better: Avoiding Pitfalls in Developing Language Resources when Data is Scarcecited by 4
  3. 2025Designing Speech Technologies for Australian Aboriginal English: Opportunities, Risks and Participationcited by 3
  4. 2025What Do Indonesians Really Need from Language Technology? A Nationwide Surveycited by 3
  5. 2022Towards a general purpose machine translation system for Sranantongocited by 2
  6. 2025NLP Security and Ethics, in the Wildcited by 2
  7. 2025Beyond Weaponization: NLP Security for Medium and Lower-Resourced Languages in Their Own Rightcited by 2
  8. 2024Guylingo: The Republic of Guyana Creole Corporacited by 1
  9. 2024Moly'e: A Corpus-based Approach to Language Contact in Colonial Francecited by 1
  10. 2025Kr'eyoLID From Language Identification Towards Language Miningcited by 0
  11. 2025Deconstructing Jazz Piano Style Using Machine Learningcited by 0
  12. 2025Limited-Resource Adapters Are Regularizers, Not Linguistscited by 0
  13. 2026Saar-Voice: A Multi-Speaker Saarbr"ucken Dialect Speech Corpuscited by 0
  14. 2026Beyond Good Intentions: When Does the Framing of Multilingual and Low-Resource NLP Research Become a Caricature?cited by 0
  15. 2026The University of Melbourne WMT 2026 CreoleMT Submission: A Domain-Balanced Approach to Low-Resource Pacific Creole Machine Translationcited by 0