Парное ранжирование

In this paper we investigate how to identify initiation-response pairs in asynchronous, multi-threaded, multi-party conversations. We formulate the task of identifying initia- tion-response pairs as a pairwise ranking problem. A …...

We propose a tuning method for statistical ma- chine translation, based on the pairwise rank- ing approach. Hopkins and May (2011) pre- sented a method that uses a binary classifier. …...

AbstractWe propose a local coherence model based on a convolutional neural network that operates over the entity grid representation of a text. The model captures long range entity transitions along …...

AbstractWe propose a novel discriminative ranking model that learns embeddings from multilingual and multi-modal data, meaning that our model can take advantage of images and descriptions in multiple languages to …...

AbstractPairwise ranking methods are the most widely used discriminative training approaches for structure prediction problems in natural language processing (NLP). Decomposing the problem of ranking hypotheses into pairwise comparisons enables …...

AbstractDocument-level evaluation of machine translation has raised interest in the community especially since responses to the claims of “human parity” (Toral et al., 2018; Läubli et al., 2018) with document-level …...

AbstractThis paper addresses the efficiency challenge of Neural Architecture Search (NAS) by formulating the task as a ranking problem. Previous methods require numerous training examples to estimate the accurate performance …...