30 citations · 44 across the 7 of their papers we have counts for
7 papers
MultiLS: A Multi-task Lexical Simplification Framework
Kai North, Tharindu Ranasinghe, Matthew Shardlow +1
Lexical Simplification (LS) automatically replaces difficult to read words for easier alternatives while preserving a sentence's original meaning. LS is a precursor to Text Simplif…
Overview of the BioLaySumm 2023 Shared Task on Lay Summarization of Biomedical Research Articles
Tomas Goldsack, Zheheng Luo, Qianqian Xie +4
This paper presents the results of the shared task on Lay Summarisation of Biomedical Research Articles (BioLaySumm), hosted at the BioNLP Workshop at ACL 2023. The goal of this sh…
BLESS: Benchmarking Large Language Models on Sentence Simplification
Tannon Kew, Alison Chi, Laura Vásquez-Rodríguez +4
We present BLESS, a comprehensive performance benchmark of the most recent state-of-the-art large language models (LLMs) on the task of text simplification (TS). We examine how wel…
Deep Learning Approaches to Lexical Simplification: A Survey
Kai North, Tharindu Ranasinghe, Matthew Shardlow +1
Lexical Simplification (LS) is the task of replacing complex for simpler words in a sentence whilst preserving the sentence's original meaning. LS is the lexical component of Text…
Natural language processing on customer note data
Andrew Hilditch, David Webb, Jozef Baca +3
Automatic analysis of customer data for businesses is an area that is of interest to companies. Business to business data is studied rarely in academia due to the sensitive nature…
Lexical Complexity Prediction: An Overview
Kai North, Marcos Zampieri, Matthew Shardlow
The occurrence of unknown words in texts significantly hinders reading comprehension. To improve accessibility for specific target populations, computational modelling has been app…