Automating Categorization of Scientific Texts with In-Context Learning and Prompt-Chaining in Large Language Models

ArXi:2604.23430v1 Announce Type: cross The relentless expansion of scientific literature presents significant challenges for navigation and knowledge discovery. Within Research Information Retrieval, established tasks such as text summarization and classification remain crucial for enabling researchers and practitioners to effectively navigate this vast landscape, so that efforts have increasingly been focused on developing advanced research information systems.