arXiv:1612.05555
공식 코드 · Papers with Code
Neural Networks Classifier for Data Selection in Statistical Machine Translation
원문 초록
We address the data selection problem in statistical machine translation (SMT) as a classification task. The new data selection method is based on a neural network classifier. We present a new method description and empirical results proving that our data selection method provides better translation quality, compared to a state-of-the-art method (i.e., Cross entropy). Moreover, the empirical results reported are coherent across different language pairs.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
CycleDistill: Bootstrapping Machine Translation using LLMs with Cyclical Distillation
Gender Bias in English-to-Greek Machine Translation
TACTIC: Translation Agents with Cognitive-Theoretic Interactive Collaboration
Translate With Care: Addressing Gender Bias, Neutrality, and Reasoning in Large Language Model Translations
Should I Share this Translation? Evaluating Quality Feedback for User Reliance on Machine Translation
Unsupervised Word-level Quality Estimation for Machine Translation Through the Lens of Annotators (Dis)agreement
토론
이 논문과 연결된 포럼 글이 아직 없습니다.