SemHash-LLM is a multi-granularity semantic hashing framework that fuses character, token, and document signals via gated fusion and cascaded filtering to achieve high-quality deduplication with under 1% neural verification cost.
Coil: Revisit exact lexical match in information retrieval with contextualized inverted list,
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SemHash-LLM: A Multi-Granularity Semantic Hashing Framework for Document Deduplication
SemHash-LLM is a multi-granularity semantic hashing framework that fuses character, token, and document signals via gated fusion and cascaded filtering to achieve high-quality deduplication with under 1% neural verification cost.