RACORN-1 adds adaptive search fallback to ACORN-1 to fix recall collapse at low selectivity in filtered vector search, achieving 9-26x speedups over HNSW with recovered recall on 1M-40M datasets.
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SIFT precomputes selective attention indices via local and cross-attention invariance to speed RAG prefill 1.71x while keeping accuracy within 1% of full recompute, storing only bit vectors 24,000x smaller than KV tensors.
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RACORN-1: Adaptive Recall-Preserving Speedup for Low-Selectivity Filtered Vector Search
RACORN-1 adds adaptive search fallback to ACORN-1 to fix recall collapse at low selectivity in filtered vector search, achieving 9-26x speedups over HNSW with recovered recall on 1M-40M datasets.
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SIFT: Selective-Index For Fast Compute of RAG Prefill by Exploiting Attention Invariance
SIFT precomputes selective attention indices via local and cross-attention invariance to speed RAG prefill 1.71x while keeping accuracy within 1% of full recompute, storing only bit vectors 24,000x smaller than KV tensors.