DaCoM: Strategies to Construct Domain-specific Low-resource Language Machine Translation Dataset (2025.coling-industry)
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| Challenge: | Existing models for low-resource languages struggle with domain-specific terms and lack of expert annotators for dataset creation. |
| Approach: | They propose a method for collecting low-resource language pairs from industrial domains using a large language model and neural machine translation framework. |
| Outcome: | The proposed model performs poorly on DaCoM-created datasets with up to 53.7 BLEURT points difference depending on domain inclusion. |
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