[R] VLouvain: Louvain Community Detection Directly on Vectors, No Graph Construction

You have embeddings for your objects. You want to build a similarity graph and find communities, whether for GraphRAG, a recommender system, or just finding structure in your data. So you compute pairwise similarities, build the graph, run Louvain. Except now you have O(n^2) edges and everything crashes above ~15K nodes. VLouvain reformulates Louvain to work directly on the embedding matrix. Degrees and modularity gains are computed from community-level vector sums, no edges involved. You maintain O(n*d) state instead of O(n^2.