mlsanityData to 7 Oct 2026

Comparing LLM prompting with Cross-lingual transfer performance on Indigenous and Low-resource Brazilian Languages

arXiv 2404.18286 ↗First posted 28 Apr 2024cs.CLcited by 4

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Abstract (arXiv)

Large Language Models are transforming NLP for a variety of tasks. However, how LLMs perform NLP tasks for low-resource languages (LRLs) is less explored. In line with the goals of the AmericasNLP workshop, we focus on 12 LRLs from Brazil, 2 LRLs from Africa and 2 high-resource languages (HRLs) (e.g., English and Brazilian Portuguese). Our results indicate that the LLMs perform worse for the part of speech (POS) labeling of LRLs in comparison to HRLs. We explain the reasons behind this failure and provide an error analysis through examples observed in our data set.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 16 of its 29 references that are in the map. First posted on arXiv 28 Apr 2024.

Builds on

16 of 29 references.

References · 16

  1. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,907
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  3. 2024Aya Model: An Instruction Finetuned Open-Access Multilingual Language Modelcited by 292
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  5. 2023ChatGPT Beyond English: Towards a Comprehensive Evaluation of Large Language Models in Multilingual Learningcited by 203
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  7. 2021Composable Sparse Fine-Tuning for Cross-Lingual Transfercited by 144
  8. 2020When Being Unseen from mBERT is just the Beginning: Handling New Languages With Multilingual Language Modelscited by 131
  9. 2020Low-resource Languages: A Review of Past Work and Future Challengescited by 90
  10. 2023MEGAVERSE: Benchmarking Large Language Models Across Languages, Modalities, Models and Taskscited by 57
  11. 2021How to Adapt Your Pretrained Multilingual Model to 1600 Languagescited by 54
  12. 2020Transfer Learning and Distant Supervision for Multilingual Transformer Models: A Study on African Languagescited by 52
4 more
  1. 2023AfroBench: How Good are Large Language Models on African Languages?cited by 43
  2. 2019Massive vs. Curated Word Embeddings for Low-Resourced Languages. The Case of Yor`ub'a and Twicited by 33
  3. 2021Specializing Multilingual Language Models: An Empirical Studycited by 21
  4. 2022On Building Spoken Language Understanding Systems for Low Resourced Languagescited by 4

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Citing papers per year: 2025: 3; 2026: 1.

4 papers.