Lexical Simplification

Lexical simplification (LS) focuses on automatically replacing complex words in text with simpler synonyms while preserving meaning, thereby improving text accessibility for diverse audiences. Current research emphasizes developing multilingual LS systems using transformer-based models, including fine-tuned versions of BERT and T5, and leveraging large language models (LLMs) like GPT-3 for both supervised and unsupervised approaches. This field is significant because it enhances text comprehension for individuals with low literacy, language learning difficulties, or reading disabilities, and the development of robust, multilingual LS systems is driving progress in natural language processing and computational linguistics.