With the rise of a new open-source and cheap LLM, DeepSeek, I’ve started to wonder how applicable it may be to fixing src - tgt alignment between translations.
I do not trust LLMs to have the ability to complete the translation themselves, but provided with an incorrect or misaligned one, I do think an LLMs experience with language can correct un-natural over/under/mis translations, as well as decide when it doesn’t know how to fix something.
This will no doubt only be testable and functional with high-resource languages, the biggest benefit obviously being Chinese and English, then descending down to other high res languages.
To correct a million sentences (assuming avg of 50 chars per translation, and that a token is 3 chars) it would cost around $7 (with deepseek v-3 API), as opposed to around $166 with the chatgpt-4o that is similar in performance (according to their repo)