VoteGCL

VoteGCL, developed by researchers, is a framework that uses few-shot LLM prompting and majority voting to generate high-confidence synthetic data for graph recommendation systems.

Two-hop subgraph: this entity, every entity it directly relates to, and every entity those neighbors relate to. Drag a node, scroll to zoom, click to inspect — or click any neighbor and re-center the atlas there.