Building Accurate Translation-Tailored LLMs with Language Aware Instruction Tuning

Understand

Translation-tailored Large language models (LLMs) exhibit remarkable translation capabilities, even competing with supervised-trained commercial translation systems.

• However, off-target translation remains an unsolved problem, especially for low-resource languages, hindering us from developing accurate LLMs-based translation models.
• To mitigate the off-target translation problem and enhance the performance of LLMs on translation, recent works have either designed advanced prompting strategies to highlight the functionality of translation instructions or exploited the in-context learning ability of LLMs by feeding few-shot demonstrations.
• However, these methods essentially do not improve LLM's ability to follow translation instructions, especially the language direction information.