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cv usk
@cv_usk
AI / Software Research Notes AI Agent, LLMOps, MLOps, Software Architecture ๆŠ•็จฟใฏๅ€‹ไบบใฎๆ„่ฆ‹ใงใ™ใ€‚
๊ฐ€์ž… May 2026
279 ํŒ”๋กœ์ž‰ ์ค‘    410 ํŒฌ
TL;DR: Pinecone released VQ-bench, a benchmark that treats today's zoo of vector quantization methods as combinations of a small set of shared primitives, making it possible to compare them fairly under the same conditions. Title: VQ-bench: a Composable Vector Quantization Framework URL: Points ๐Ÿงฉ Defines composable primitives like Center, Normalize, PCA, and RandomRotate that any quantizer can be built from ๐Ÿ”— Existing methods like E-RaBitQ reduce to just 4 chained primitives: Center, Normalize, Random Rotation, Angular Cast ๐Ÿ“Š Benchmarks 14 quantizers on 5 VIBE datasets using Reconstruction MSE, Recall@10, and encode time ๐Ÿฅ‡ PQ and OPQ consistently achieve the lowest Reconstruction MSE โšก EDEN encodes far faster than PQ, OPQ, and E-RaBitQ while keeping recall competitive ๐Ÿ› ๏ธ Adding a new quantizer often takes just a few lines of code, and a new primitive automatically composes with every existing one Putting fragmented quantization methods on the same evaluation footing should make it much easier to pick the right one for your use case. #VectorSearch# #VectorDB#
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