30 citations · 61 across the 12 of their papers we have counts for
12 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…
Health Text Simplification: An Annotated Corpus for Digestive Cancer Education and Novel Strategies for Reinforcement Learning
Md Mushfiqur Rahman, Mohammad Sabik Irbaz, Kai North +3
Objective: The reading level of health educational materials significantly influences the understandability and accessibility of the information, particularly for minoritized popul…
Offensive Language Identification in Transliterated and Code-Mixed Bangla
Md Nishat Raihan, Umma Hani Tanmoy, Anika Binte Islam +4
Identifying offensive content in social media is vital for creating safe online communities. Several recent studies have addressed this problem by creating datasets for various lan…
Findings of the VarDial Evaluation Campaign 2023
Noëmi Aepli, Çağrı Çöltekin, Rob Van Der Goot +7
This report presents the results of the shared tasks organized as part of the VarDial Evaluation Campaign 2023. The campaign is part of the tenth workshop on Natural Language Proce…
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…
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…
Language Variety Identification with True Labels
Marcos Zampieri, Kai North, Tommi Jauhiainen +4
Language identification is an important first step in many IR and NLP applications. Most publicly available language identification datasets, however, are compiled under the assump…
Findings of the TSAR-2022 Shared Task on Multilingual Lexical Simplification
Horacio Saggion, Sanja Štajner, Daniel Ferrés +4
We report findings of the TSAR-2022 shared task on multilingual lexical simplification, organized as part of the Workshop on Text Simplification, Accessibility, and Readability TSA…
Overview of the HASOC Subtrack at FIRE 2022: Offensive Language Identification in Marathi
Tharindu Ranasinghe, Kai North, Damith Premasiri +1
The widespread of offensive content online has become a reason for great concern in recent years, motivating researchers to develop robust systems capable of identifying such conte…
Lexical Simplification Benchmarks for English, Portuguese, and Spanish
Sanja Stajner, Daniel Ferres, Matthew Shardlow +3
Even in highly-developed countries, as many as 15-30\% of the population can only understand texts written using a basic vocabulary. Their understanding of everyday texts is limite…
ALEXSIS-PT: A New Resource for Portuguese Lexical Simplification
Kai North, Marcos Zampieri, Tharindu Ranasinghe
Lexical simplification (LS) is the task of automatically replacing complex words for easier ones making texts more accessible to various target populations (e.g. individuals with l…
LCP-RIT at SemEval-2021 Task 1: Exploring Linguistic Features for Lexical Complexity Prediction
Abhinandan Desai, Kai North, Marcos Zampieri +1
This paper describes team LCP-RIT's submission to the SemEval-2021 Task 1: Lexical Complexity Prediction (LCP). The task organizers provided participants with an augmented version…