Paraphrase Recognition

Paraphrase recognition is a critical step for nat- ural language interpretation. Accordingly, many NLP applications would benefit from high coverage knowledge bases of paraphrases. However, the scal- ability of state-of-the-art …...

We propose a supervised, two-phase framework to address the problem of para- phrase recognition (PR). Unlike most PR systems that focus on sentence similarity, our framework detects dissimilarities be- tween …...

Many problems in natural language process- ing can be viewed as variations of the task of measuring the semantic textual similarity be- tween short texts. However, many systems that address …...

This paper describes a study on the impact of the original signal (text, speech, visual scene, event) of a text pair on the task of both man- ual and automatic …...

In this paper we describe a system that rec- ognizes paraphrases in Twitter for tweets that refer to the same topic. The system partici- pated in Task1 of SEMEVAL-2015 and …...

This paper describes our approaches to para- phrase recognition in Twitter organized as task 1 in Semantic Evaluation 2015. Lots of ap- proaches have been proposed to address the paraphrasing …...

Paraphrase recognition is the task of iden- tifying whether two pieces of natural lan- guage represent similar meanings. This pa- per describes a system participating in the shared task 1 …...

Analyzing historical languages, such as Ancient Greek and Latin, is challenging. Such languages are often under-resourced and lack primary material for certain time periods. This prevents applying advanced natural-language processing …...

AbstractInducing diversity in the task of paraphrasing is an important problem in NLP with applications in data augmentation and conversational agents. Previous paraphrasing approaches have mainly focused on the issue …...

AbstractWhile pretrained language models have exhibited impressive generalization capabilities, they still behave unpredictably under certain domain shifts. In particular, a model may learn a reasoning process on in-domain training data …...