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A major challenge in supervised sentence compression is making use of rich feature rep- resentations because of very scarce parallel data. We address this problem and present a method to …...

Our system combines text similarity measures with a textual entailment system. In the main task, we focused on the influence of lexical- ized versus unlexicalized features, and how they affect …...

This paper proposes a novel multilin- gual multistage fine-tuning approach for low-resource neural machine translation (NMT), taking a challenging Japanese– Russian pair for benchmarking. Al- though there are many solutions …...

AbstractRegularization of neural machine translation is still a significant problem, especially in low-resource settings. To mollify this problem, we propose regressing word embeddings (ReWE) as a new regularization technique in …...

AbstractPrevious studies demonstrated that a dynamic phone-informed compression of the input audio is beneficial for speech translation (ST). However, they required a dedicated model for phone recognition and did not …...

AbstractRelation schemas are often pre-defined for each relation dataset. Relation types can be related from different datasets and have overlapping semantics. We hypothesize we can combine these datasets according to …...

AbstractEvent temporal relation extraction (ETRE) is usually formulated as a multi-label classification task, where each type of relation is simply treated as a one-hot label. This formulation ignores the meaning …...