We present a simple and effective approach to incorporating syntactic structure into neural
attention-based encoder-decoder models for machine translation. We rely on graph …

In this paper we examine the task of sentence simplification which aims to reduce the
reading complexity of a sentence by incorporating more accessible vocabulary and …

We offer a simple, effective, and scalable method for statistical machine translation
parameter tuning based on the pairwise approach to ranking (Herbrich et al., 1999). Unlike …

In this paper we examine the sentence simplification problem as an English-to-English
translation problem, utilizing a corpus of 137K aligned sentence pairs extracted by aligning …

We present an approach to semantics-based statistical machine translation that uses
synchronous hyperedge replacement grammars to translate into and from graph-shaped …

In adding syntax to statistical machine translation, there is a tradeoff between taking
advantage of linguistic analysis and allowing the model to exploit parallel training data with …

In machine translation, discriminative models have almost entirely supplanted the classical
noisychannel model, but are standardly trained using a method that is reliable only in low …

To adapt a translation model trained from the data in one domain to another, previous works
paid more attention to the studies of parallel corpus while ignoring the in-domain …

Word reordering is a difficult task for translation between languages with widely different
word orders, such as Japanese and English. A previously proposed post-ordering method …

This paper describes a novel technique for incorporating syntactic knowledge into
phrasebased machine translation through incremental syntactic parsing. Bottom-up and …