Google Releases RSLM: Training-Free Vector Quantization for ANN Search
_reachsumit · x · 2026-09-01
Google introduces RSLM (Rotated Scaled Lloyd-Max), a family of training-free vector quantization codecs compressing embeddings to 1-4 bits per dimension for Approximate Nearest Neighbor (ANN) search. By encoding residual vectors and correcting L2 norms, RSLM reduces memory costs while matching the recall of trained quantizers across multiple benchmarks.
More from Research
- Core principles of Denoising Diffusion Models and Score Matching explained — ariG23498 · 2026-09-01
- ContextLeak: Malicious tools can exfiltrate 92% of Agent context — rohanpaul_ai · 2026-09-01
- MIT Study: AI Agents Coordinate Silently via Shared Environment — mikeflache · 2026-09-01
- Elastic Triangle Splatting improves kernel design for reconstruction — zhenjun_zhao · 2026-09-01
- Audit reveals overconfidence in feed-forward 3D reconstruction models — zhenjun_zhao · 2026-09-01
- ReconSplat achieves generalizable 3D reconstruction via diffusion priors — zhenjun_zhao · 2026-09-01