I am looking for a paper, serious blog post or something similar to know the state of the art in NMT in a pair of common languages (for example, english-spanish). I am trying to see what BLEU (or another valid metric) do the Transformer Base, Transformer Big and Transformer-based models (BERT, GPT-2, GPT-3, T5) or even deeper Transformers achieve in comparison. Addicional techniques such as training with guided alignements would be useful. However, I have not been able to find any resource, nor even in competitions such as WMT. Maybe I am missing something. Can I except to see big improvements with the latest transformers-based models over Transformer Base? Is it possible to train a language model like GPT-2 to do machine translation?
Any help would be appreciated, thank you so much.