Questions.
Evidence. Progress.

Research at a glance

When Does Low-Bit Quantization Preserve the Decisions of Vector Search?

Places quantization error inside the ranking and graph-pruning decisions that vector search actually makes, relating reliability to comparison margins, correlated residuals, and execution traces.

Vector search · Decision stability

Research at a glance

Contextual Utility of Quantization Moves in Extreme Low-Bit LLMs

Studies the real utility of a discrete move in extreme low-bit LLMs by evaluating the move along its own path and combining decisions in an evolving model state.

LLM quantization · Post-training

Research at a glance

Covariance Structure and Coordinate Heterogeneity Govern Binary Quantization of Contrastive Embeddings

Explains low-bit ranking behavior through covariance structure and coordinate heterogeneity, including why an extra magnitude bit and random rotation help different representations in different ways.

Representation geometry · Binary quantization

Research at a glance

QuIVer: Rethinking ANN Graph Topology via Training-Free Binary Quantization

Builds, prunes, and navigates an ANN graph in a training-free two-bit space, reading full vectors only for final reranking and exposing the data regimes where compact topology works.

Approximate nearest neighbors · Graph indexes