Integrate BBC with graph-quantization ANN methods

Develop an integration of the bucket-based result collector (BBC) with graph–quantization approximate nearest neighbor methods that combine quantization and graphs, such as SymphonyQG and NGT-QG, to extend BBC beyond pure quantization-based IVF indexes.

Background

The paper introduces BBC, a bucket-based result collector designed to accelerate quantization-based approximate nearest neighbor (ANN) methods for large-k queries. While BBC is integrated and evaluated with IVF+PQ and IVF+RaBitQ, the authors note that there also exist ANN approaches that integrate quantization with graph structures.

However, the authors report practical limitations in existing graph–quantization systems: SymphonyQG and NGT-QG exhibit out-of-memory issues during indexing on their setup due to high memory consumption, and LVQ is closed-source. Given these constraints, the authors explicitly leave integrating BBC with such graph–quantization methods as future work.

References

Therefore, we leave the integration of BBC with these methods for future work.

BBC: Improving Large-k Approximate Nearest Neighbor Search with a Bucket-based Result Collector  (2604.01960 - Yin et al., 2 Apr 2026) in Related Work (Section 6), final paragraph