Relatedly's design of scaffolding literature exploration by extracting and re-ranking related work sections across papers has informed a range of subsequent systems for augmented scholarly reading and sensemaking, been adopted as a reference point for reading interfaces that highlight salient content and reduce redundancy, contributed its belief propagation algorithm for citation-graph-based paper recommendation, served as a motivating example for structured output formats consumable by downstream reading tools, and been situated within the Semantic Reader Project as a key prototype for literature synthesis — collectively influencing work on literature review tool design, AI-assisted research gap discovery, and cross-document information maintenance.