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insight - Multilingual machine translation
다국어 기계 번역을 위한 뉴런 전문화: 내재적 과제 모듈성 활용
다국어 신경망 모델에 내재된 과제 특화 모듈성을 활용하여 언어 간 간섭을 줄이고 지식 전이를 향상시킬 수 있다.
Leveraging Monolingual Data for Multilingual Machine Translation: Exploring the Impact of Domain and Model Scale
Monolingual data can generally help improve multilingual machine translation, but the effectiveness of different methods like backtranslation and denoising autoencoding varies significantly depending on the domain similarity between the monolingual and test data, as well as the model scale.
The Role of Subword Segmentation in Promoting Synergy and Cross-Lingual Transfer in Multilingual Machine Translation
Decisions around subword segmentation significantly affect synergy, interference, and cross-lingual transfer in multilingual machine translation. Subword regularization boosts synergy, while deterministic segmentation like BPE enhances cross-lingual transferability.
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