Author Assigned Keyphrases

Author-assigned keyphrases, representing the core concepts of a document, are increasingly studied for their ability to improve text summarization and information retrieval. Current research focuses on enhancing keyphrase generation and extraction methods, often employing large language models (LLMs) within frameworks like one2set and leveraging techniques such as contrastive learning and self-attention mechanisms to improve accuracy and address challenges like absent keyphrase prediction and calibration errors. This work is significant because effective keyphrase identification facilitates improved document understanding, efficient information retrieval, and more accurate summarization across diverse applications, including forensic analysis and scientific literature organization.