Better vector search with graphs and spectral indexing
16 hours ago
- #spectral-methods
- #dimensionality-reduction
- #graph-structure
- The release rethinks how `arrowspace` builds and queries graph structures from high-dimensional embeddings.
- Laplacian computation now condenses data using clustering and density-aware sampling.
- Dimensionality is projected proportionally to the problem size (centroids) to maintain query consistency.
- Graph sparsification is achieved via a fast spectral method to preserve structure while reducing costs.