Span Extraction

Span extraction, a core task in natural language processing, focuses on identifying and classifying relevant subsequences within text to extract structured information. Current research emphasizes unifying diverse information extraction tasks under a span-based framework, employing transformer-based models and novel attention mechanisms (like fuzzy span attention) to improve accuracy and efficiency, particularly in low-resource settings. This work is significant for advancing information extraction across various domains, including legal documents, medical records, and business reports, enabling improved knowledge representation and downstream applications like question answering and semantic search.