Multi-agent Learning for Neural Machine Translation
Table 5: BLEU score for the L2R model in multi-agent training on large-scale corpus of Chinese-English translation. Because we only use L2R model in Baidu Translate, so part of results are presented.
['Models', 'AVERAGE']
In order to prove that multi-agent learning can yield improvement in large-scale corpus, we conducted experiments on 40M Chinese-English sentence pairs with the same data processing method as NIST. We built test sets of more than 10K sentences which cover various domains such as news, spoken language and query logs. This technique has already been applied to Baidu Translate.