Recognizing and generating paraphrases is an important component in many natural
language processing applications. A well-established technique for automatically extracting …

In the last few years, a number of NLP researchers have developed and participated in the
task of Recognizing Textual Entailment (RTE). This task encapsulates Natural Language …

The quality of automatic metrics for machine translation has been increasingly called into
question, especially for high-quality systems. This paper demonstrates that, while choice of …

In this paper we describe a method for simplifying sentences using Phrase Based Machine
Translation, augmented with a re-ranking heuristic based on dissimilarity, and trained on a …

Paraphrasing methods recognize, generate, or extract phrases, sentences, or longer natural
language expressions that convey almost the same information. Textual entailment …

The task of paraphrasing is inherently familiar to speakers of all languages. Moreover, the
task of automatically generating or extracting semantic equivalences for the various units of …

The most widely adopted approaches for evaluation of summary content follow some
protocol for comparing a summary with gold-standard human summaries, which are …

Abstract Automatic Machine Translation (MT) evaluation metrics have traditionally been
evaluated by the correlation of the scores they assign to MT output with human judgments of …

We improve the quality of paraphrases extracted from parallel corpora by requiring that
phrases and their paraphrases be the same syntactic type. This is achieved by parsing the …

Untranslated words still constitute a major problem for Statistical Machine Translation (SMT),
and current SMT systems are limited by the quantity of parallel training texts. Augmenting the …