Papers by Taejun Yun
Analysis of Multi-Source Language Training in Cross-Lingual Transfer (2024.acl-long)
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| Challenge: | Existing studies on cross-lingual transfer (XLT) methods address data scarcity problem . cross-linguistic transfer (xLT) techniques are effective at fine-tuning multilingual LMs . |
| Approach: | They propose to use multiple source languages to improve XLT by fine-tuning multilingual models . they propose to employ arbitrary combinations of source languages for XL to improve performance . |
| Outcome: | The proposed technique improves performance on language-agnostic or task-specific features by using multiple source languages. |
X-SNS: Cross-Lingual Transfer Prediction through Sub-Network Similarity (2023.findings-emnlp)
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| Challenge: | Cross-lingual transfer (XLT) is an emergent ability of multilingual language models that preserves their performance when evaluated in non-English languages. |
| Approach: | They propose to use sub-network similarity between two languages as a proxy for XLT prediction. |
| Outcome: | The proposed method shows proficiency in ranking candidates for zero-shot XLT, achieving an improvement of 4.6% on average in terms of NDCG@3. |