新闻
MRVQ: One Resident Index for Dimension- and Rate-Elastic Vector Search
arXiv cs.AI · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- MRVQ is a vector quantization method that stores one index serving multiple embedding dimensions and compression rates simultaneously.
- 为何重要
- Matters for engineers building dense-retrieval services that must adapt to changing latency, quality, and memory constraints at runtime.
- 注意
- MRVQ trades memory efficiency for retrieval quality, losing 0.026-0.107 nDCG@10 compared to separately tuned indices on some benchmarks.
- retrieval
- embedding
- quantiz
- latency
- eval
这条新闻背后的模式
- Hierarchical Index Retrieval (RAPTOR)
- Eval-Driven Development (Agent CI)
- Constraint Satisfaction Planning
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