Scientific Information Extraction

Scientific information extraction (SciIE) aims to automatically extract key facts and relationships from scientific literature, accelerating research and knowledge discovery. Current research heavily utilizes large language models (LLMs), such as BERT and GPT variants, often fine-tuned on domain-specific datasets, to perform tasks like named entity recognition, relation extraction, and question answering. These models are being applied to diverse scientific domains and increasingly incorporate cross-modality information from text and tables, improving the efficiency and accuracy of information retrieval and knowledge graph construction. The resulting advancements promise to significantly enhance scientific productivity and accessibility of research findings.