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SeDA: Bridging the Gap between Efficient Syntactic and Precise Semantic Search of Similar Passages in Large Text Corpora

Summary: SeDA introduces semantic document alignment for similar-passage search: semantic set-similarity over k-width windows, closing the gap between fast syntactic candidate generation and precise semantic matching. A candidate generator plus bound cascade exploits window overlap to prune >99% of expensive comparisons, yielding SBERT-quality F1 with near-syntactic runtimes. (summarized by gpt-5.4-mini on Apr 12 2026)

Paper ID
14281
Venue
VLDB
Year
2026
Pagerank
4.1945683e-05
Overall Rank
10,245 | 28.73%
DOI
10.14778/3797919.3797938

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