This article introduces a novel method for progressively visualizing the evolution of a knowledge domain's cocitation network, aiming to identify intellectually significant articles. The method involves dividing a time interval into equal-length slices, deriving cocitation networks from each slice, and merging these networks into a panoramic view. Visually salient nodes, such as landmark, hub, and pivot nodes, are identified in this panoramic view, which can be validated by leading scientists in the field. The method is applied to the study of superstring theory in theoretical physics, focusing on the search for articles that triggered two superstring revolutions. The analysis demonstrates that the method can effectively narrow down the search for intellectual turning points to visually salient nodes, simplifying cognitively demanding tasks. The entire process is implemented in CITESPACE, a computer system designed for knowledge domain visualization. The article also discusses the challenges and future directions of the method, emphasizing its potential to provide a practical tool for scientists to monitor and understand the evolution of their fields.This article introduces a novel method for progressively visualizing the evolution of a knowledge domain's cocitation network, aiming to identify intellectually significant articles. The method involves dividing a time interval into equal-length slices, deriving cocitation networks from each slice, and merging these networks into a panoramic view. Visually salient nodes, such as landmark, hub, and pivot nodes, are identified in this panoramic view, which can be validated by leading scientists in the field. The method is applied to the study of superstring theory in theoretical physics, focusing on the search for articles that triggered two superstring revolutions. The analysis demonstrates that the method can effectively narrow down the search for intellectual turning points to visually salient nodes, simplifying cognitively demanding tasks. The entire process is implemented in CITESPACE, a computer system designed for knowledge domain visualization. The article also discusses the challenges and future directions of the method, emphasizing its potential to provide a practical tool for scientists to monitor and understand the evolution of their fields.