mlsanityData to 14 Oct 2026

Ancestor-to-Creole Transfer is Not a Walk in the Park

arXiv 2206.04371 ↗First posted 9 Jun 2022cs.CLcited by 7

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Abstract (arXiv)

We aim to learn language models for Creole languages for which large volumes of data are not readily available, and therefore explore the potential transfer from ancestor languages (the 'Ancestry Transfer Hypothesis'). We find that standard transfer methods do not facilitate ancestry transfer. Surprisingly, different from other non-Creole languages, a very distinct two-phase pattern emerges for Creoles: As our training losses plateau, and language models begin to overfit on their source languages, perplexity on the Creoles drop. We explore if this compression phase can lead to practically useful language models (the 'Ancestry Bottleneck Hypothesis'), but also falsify this. Moreover, we show that Creoles even exhibit this two-phase pattern even when training on random, unrelated languages. Thus Creoles seem to be typological outliers and we speculate whether there is a link between the two observations.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 12 of its 29 references that are in the map. First posted on arXiv 9 Jun 2022.

Builds on

12 of 29 references.

References · 12

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2020Scaling Laws for Neural Language Modelscited by 6,586
  3. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,935
  4. 2015Neural Machine Translation of Rare Words with Subword Unitscited by 2,918
  5. 2016Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translationcited by 1,475
  6. 2019Cross-Lingual Ability of Multilingual BERT: An Empirical Studycited by 182
  7. 2021MasakhaNER: Named Entity Recognition for African Languagescited by 155
  8. 2020When Being Unseen from mBERT is just the Beginning: Handling New Languages With Multilingual Language Modelscited by 131
  9. 2020UNKs Everywhere: Adapting Multilingual Language Models to New Scriptscited by 113
  10. 2020Massive Choice, Ample Tasks (MaChAmp): A Toolkit for Multi-task Learning in NLPcited by 50
  11. 2021When is BERT Multilingual? Isolating Crucial Ingredients for Cross-lingual Transfercited by 42
  12. 2021On Language Models for Creolescited by 17

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 2; 2023: 1; 2024: 2; 2025: 1; 2026: 1.

7 papers.