BLEU might be Guilty but References are not Innocent - https://arxiv.org/abs/2004.06063 - We show that it is possible to calculate reliable automatic scores (even with BLEU) for high quality MT output by using a novel reference generation method.
Typical references exhibit poor diversity, concentrating around translationese language. Paraphrased references cover a wider diversity of target sentences and thus do not penalize alternative but equally accurate translations.
Releasing all reference translations gives the community a chance to revisit some of their decisions and measure quality differences for modeling techniques that produce more natural or fluent output which is penalized by standard references.
BLEU might be Guilty but References are not Innocent - https://arxiv.org/abs/2004.06063 - We show that it is possible to calculate reliable automatic scores (even with BLEU) for high quality MT output by using a novel reference generation method.
Typical references exhibit poor diversity, concentrating around translationese language. Paraphrased references cover a wider diversity of target sentences and thus do not penalize alternative but equally accurate translations.
Releasing all reference translations gives the community a chance to revisit some of their decisions and measure quality differences for modeling techniques that produce more natural or fluent output which is penalized by standard references.
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