UC Berkeley’s LEANN vector index stores a pruned graph and recomputes embeddings at query time. It matches HNSW accuracy at 90% recall using 4 GB instead of 188 GB, at the cost of seconds-level search. The post Meet LEA…
开放权重的发布会对闭源定价形成压力、扩大可及性,改变整个生态「自建 vs 采购」的权衡。
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