I'm one of the authors on the paper. Actually, sentence-by-sentence translation is important in a machine translation system because in many cases users will only provide single sentences. We also test document-level translation in Section 5, and find large improvements (but it isn't the focus of our paper).
Although, the paper argues that we can create artificial datasets using the LLMs which would improve the special-case translation models without having to pay for the inference and latency time of the large models.
Yes, but the translation model in the “Attention is All You Need” was trained on parallel sentences (input: English sentence, output: French). LLMs such as Claude are not trained on any labeled data. Yet, they still surpass the special-case models.
