Функции потерь

We present Minimum Bayes-Risk word alignment for machine translation. This statistical, model-based approach attempts to minimize the expected risk of align- ment errors under loss functions that mea- sure alignment …...

AbstractAn interesting aspect of structured prediction is the evaluation of an output structure against the gold standard. Especially in the loss-augmented setting, the need of finding the max-violating constraint has …...

AbstractCross-lingual summarization is the task of generating a summary in one language given a text in a different language. Previous works on cross-lingual summarization mainly focus on using pipeline methods …...

Learning disentangled representations of texts, which encode information pertaining to differ- ent aspects of the text in separate representa- tions, is an active area of research in NLP for controllable …...

AbstractSupervised learning assumes that a ground truth label exists. However, the reliability of this ground truth depends on human annotators, who often disagree. Prior work has shown that this disagreement …...

AbstractData augmentation is an effective way to improve the performance of many neural text generation models. However, current data augmentation methods need to define or choose proper data mapping functions …...

AbstractRecently, multimodal transformer models have gained popularity because their performance on downstream tasks suggests they learn rich visual-linguistic representations. Focusing on zero-shot image retrieval tasks, we study three important factors …...