Lexical Complexity Prediction

Lexical complexity prediction (LCP) focuses on computationally determining the difficulty of words in text, aiming to improve text accessibility for diverse audiences. Recent research emphasizes developing robust LCP models using various techniques, including machine learning classifiers, deep neural networks like BERT, and leveraging large language models. This work is driven by the need for improved text simplification tools and resources across multiple languages, with a growing focus on addressing data scarcity and domain adaptation challenges to enhance model generalizability and accuracy. The resulting advancements have significant implications for fields like education, healthcare, and language learning, enabling the creation of more inclusive and understandable textual content.