5 papers
UOL@IDEM at BEA 2026 Shared Task 1: Neural Fusion and Feature-Rich Modeling for L1-Aware Vocabulary Difficulty Prediction
Nouran Khallaf, Serge Sharoff
This paper describes UOL@IDEM's closed-track submission to the BEA 2026 shared task on L1-aware vocabulary difficulty prediction. We model the task as regression and train separate…
Align and Shine: Building High-Quality Sentence-Aligned Corpora for Multilingual Text Simplification
Kenji Hilasaca, Nouran Khallaf, Serge Sharoff
Text simplification plays a crucial role in improving the accessibility and comprehensibility of written information for diverse audiences, including language learners and readers…
A Multilingual Human Annotated Corpus of Original and Easy-to-Read Texts to Support Access to Democratic Participatory Processes
Stefan Bott, Verena Riegler, Horacio Saggion +2
Being able to understand information is a key factor for a self-determined life and society. It is also very important for participating in democratic processes. The study of autom…
How Much Noise Can BERT Handle? Insights from Multilingual Sentence Difficulty Detection
Nouran Khallaf, Serge Sharoff
Noisy training data can significantly degrade the performance of language-model-based classifiers, particularly in non-topical classification tasks. In this study we designed a met…
To Predict or Not to Predict? Towards reliable uncertainty estimation in the presence of noise
Nouran Khallaf, Serge Sharoff
This study examines the role of uncertainty estimation (UE) methods in multilingual text classification under noisy and non-topical conditions. Using a complex-vs-simple sentence c…