Lexical simplification has attracted much attention in many languages, which is the process of replacing complex words a given sentence with simpler alternatives equivalent meaning. Although richness vocabulary Chinese makes text very difficult to read for children and non-native speakers, there no research work lexical (CLS) task. To circumvent difficulties acquiring annotations, we manually c...

Models of large forest scenes are of a geometric complexity that surpasses even the capabilities of current high end graphics hardware. We propose an extreme simplification method which allows us to render such scenes in realtime. Our work is an extension of the image based-simplification method of Billboard Clouds. We automatically generate tree model representations of 15-50 textured polygons...

We present a new Lexical Simplification approach that exploits Neural Networks to learn substitutions from the Newsela corpus a large set of professionally produced simplifications. We extract candidate substitutions by combining the Newsela corpus with a retrofitted context-aware word embeddings model and rank them using a new neural regression model that learns rankings from annotated data. T...

In this paper we present the results of a study directed towards developing a lexical simplification module of an automatic simplification system for Spanish, intended for readers with cognitive disabilities. We here observe the word length and frequency distribution of two sets of texts that make up our parallel corpus, and we focus on cases of information expansion (through the insertion of d...