Statistical machine translation (SMT) treats the translation of natural language as a machine
learning problem. By examining many samples of human-produced translation, SMT …

The ability to analyse online user-generated content related to sentiments (eg, thoughts and
opinions) on products or policies has become a de-facto skillset for many companies and …

Word alignments are useful for tasks like statistical and neural machine translation (NMT)
and cross-lingual annotation projection. Statistical word aligners perform well, as do …

Attention is a key component of Transformers, which have recently achieved considerable
success in natural language processing. Hence, attention is being extensively studied to …

Multiword expressions (MWEs) are a class of linguistic forms spanning conventional word
boundaries that are both idiosyncratic and pervasive across different languages. The …

The state of the art in machine translation (MT) is governed by neural approaches, which
typically provide superior translation accuracy over statistical approaches. However, on the …

We propose a new phrase-based translation model and decoding algorithm that enables us
to evaluate and compare several, previously proposed phrase-based translation models …

An obstacle to research in automatic paraphrase identification and generation is the lack of
large-scale, publiclyavailable labeled corpora of sentential paraphrases. This paper …

We study question answering as a machine learning problem, and induce a function that
maps open-domain questions to queries over a database of web extractions. Given a large …

We investigate unsupervised techniques for acquiring monolingual sentence-level
paraphrases from a corpus of temporally and topically clustered news articles collected from …