Attribute Controlled Translation

Attribute-controlled translation (ACT) focuses on generating translations that precisely match specified linguistic or stylistic attributes, such as formality or gender. Current research emphasizes developing methods that achieve this control, even with limited training data, often leveraging large language models and techniques like prompt engineering and retrieval-augmented generation. This area is significant because it addresses biases in machine translation and enables more nuanced and context-aware applications, impacting fields like cross-cultural communication and fairness in AI.