Sentence Processing

Sentence processing research investigates how humans understand and process sentences, aiming to model this complex cognitive ability computationally. Current research focuses on improving language models, such as Transformers and Recurrent Neural Networks, to better reflect human reading times and account for factors like memory limitations and cross-lingual influences, often using metrics derived from large language models to quantify meaning composition. These advancements contribute to a deeper understanding of human language comprehension and have implications for natural language processing applications, including code generation and improved chatbot interactions.