Naturalistic Word Order

Naturalistic word order research investigates how the arrangement of words in naturally occurring language impacts various cognitive and computational processes. Current studies focus on leveraging large language models like BERT and GPT-2, along with techniques like causal probing and attention-based span selection, to analyze how word order influences model performance on tasks ranging from emotion recognition to predicting eye-movement patterns during reading. This research is crucial for advancing our understanding of human language processing and improving the performance and interpretability of natural language processing systems, with implications for applications in autonomous vehicles, human-computer interaction, and other fields.