Machine translation has made rapid advances in recent years. Millions of people are using it
today in online translation systems and mobile applications in order to communicate across …

High quality source code is often paired with high level summaries of the computation it
performs, for example in code documentation or in descriptions posted in online forums …

It has been shown that the performance of neural machine translation (NMT) drops starkly in
low-resource conditions, underperforming phrase-based statistical machine translation …

Cloze-style queries are representative problems in reading comprehension. Over the past
few months, we have seen much progress that utilizing neural network approach to solve …

In this paper, we present Farasa, a fast and accurate Arabic segmenter. Our approach is
based on SVM-rank using linear kernels. We measure the performance of the segmenter in …

We present the IIT Bombay English-Hindi Parallel Corpus. The corpus is a compilation of
parallel corpora previously available in the public domain as well as new parallel corpora …

We examine how various types of noise in the parallel training data impact the quality of
neural machine translation systems. We create five types of artificial noise and analyze how …

We present an efficient algorithm to estimate large modified Kneser-Ney models including
interpolation. Streaming and sorting enables the algorithm to scale to much larger models by …

Neural machine translation represents an exciting leap forward in translation quality. But
what longstanding weaknesses does it resolve, and which remain? We address these …

Given the rise of the new neural approach to machine translation (NMT) and its promising
performance on different text types, we assess the translation quality it can attain on what is …