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Pail is proposed, a 𝑘 NN search algo-rithm for sets that supports a wide range of similarity functions and implements the positional filter directly into a novel index structure to effectively prune candidates.
This paper formalizes a generalizable generate-filter framework and introduces LeDQeR, an LLM-based DQ rule generation approach that is able to produce effective and compact rule sets for various datasets and error types.
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