Bootstrapping Transliteration with Constrained Discovery for Low-Resource Languages (D18-1)
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| Challenge: | Existing approaches to transliteration generation require a large number of training examples. |
| Approach: | They propose a bootstrapping algorithm that uses constrained discovery to improve generation . they show that the model can be used with as few as 500 training examples . |
| Outcome: | The proposed method improves on nine languages written in a unique script. |
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| Challenge: | Transliteration is the process of expressing a proper name from a source language in the characters of a target language. |
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| Challenge: | Named entity recognition models rely on large amounts of labeled data, making them challenging to extend to new, lower-resource languages. |
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Cross-lingual Named Entity List Search via Transliteration (2020.lrec-1)
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| Challenge: | a common way to adapt out-of-vocabulary words is a challenge in cross-lingual tasks . intrinsic evaluation, i.e comparison to a single gold standard, might not be appropriate in the task of transliteration due to its high variability. |
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A Comparative Study of Extremely Low-Resource Transliteration of the World’s Languages (L18-1)
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| Challenge: | Cross-lingual transfer is often hindered by the "script barrier" where differences in writing systems inhibit transfer learning . transliteration is a powerful technique to bridge this gap by increasing lexical overlap . authors present a taxonomy of key motivations to utilize transliterations in language models . |
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Design Challenges in Named Entity Transliteration (C18-1)
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| Challenge: | Named entity transliteration is an important component in many search and language understanding tasks. |
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Efficient Entity Candidate Generation for Low-Resource Languages (2022.lrec-1)
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| Challenge: | Existing approaches for cross-lingual entity linking are not suitable for English. |
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Towards a Broad Coverage Named Entity Resource: A Data-Efficient Approach for Many Diverse Languages (2022.lrec-1)
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Part-of-Speech Tagging for Code-Switched, Transliterated Texts without Explicit Language Identification (D18-1)
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Enhancing Cross-Lingual Transfer through Reversible Transliteration: A Huffman-Based Approach for Low-Resource Languages (2025.acl-long)
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| Challenge: | Large language models demonstrate cross-lingual transfer capabilities, but these capabilities often fail to extend to low-resource languages, especially those utilizing non-Latin scripts. |
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