purpose: the present study seeks to explore the effects of general language proficiency, text readability, and medical knowledge on comprehending medical texts. material & method: 63 medical students in the second year of their study were randomly selected from the english language classes. they answered 100 multiple-choice questions on grammar and vocabulary to establish the level of language ...

Contrastive learning models have achieved great success in unsupervised visual representation learning, which maximize the similarities between feature representations of different views same image, while minimize images. In text summarization, output summary is a shorter form input document and they similar meanings. this paper, we propose contrastive model for supervised abstractive where vie...

Previous researches on Text-level discourse parsing mainly made use of constituency structure to parse the whole document into one discourse tree. In this paper, we present the limitations of constituency based discourse parsing and first propose to use dependency structure to directly represent the relations between elementary discourse units (EDUs). The state-of-the-art dependency parsing tec...

Text prediction is an application of language models to mobile devices. Currently, the state of the art models use neural networks. Unfortunately, mobile devices are constrainted in both computing power and space and are thus unable to run most (if not all) neural networks. Recently, however, character-level architectures have appeared that have outperformed previous architectures for machine t...