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the best performing on val\n\n By sometimes merging and sometimes evolving (and dev sets) they improve over all current methods https://twitter.com/LChoshen/status/1803410445635653960/photo/1\n\n In some sense, this can be seen as a better search in the region between the merged models, which we know is not equally good but all better than the edges\nhttps://x.com/LChoshen/status/1729488495515713672 https://twitter.com/LChoshen/status/1803410447246250483/photo/1\n\n" } } } rows { name { id: 0 value: "keywords" } } rows { quad { p_iri { prefix_id: 9 name_id: 0 } o_literal { lex: "TIES" } } } rows { quad { o_literal { lex: "evolver" } } } rows { quad { o_literal { lex: "genetic\\_algorithms" } } } rows { quad { o_literal { lex: "knowledge\\_fusion" } } } rows { quad { o_literal { lex: "model\\_merging" } } } rows { name { id: 0 value: "endorses" } } rows { quad { p_iri { prefix_id: 14 name_id: 0 } o_iri { prefix_id: 16 name_id: 17 } } } rows { name { id: 0 value: "summarizes" } } rows { 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