{"id":97881,"date":"2026-09-25T08:09:17","date_gmt":"2026-09-25T05:09:17","guid":{"rendered":"https:\/\/twodots.gr\/?p=97881"},"modified":"2026-09-25T08:09:19","modified_gmt":"2026-09-25T05:09:19","slug":"causal-rag-reranking-sosti-apantisi","status":"publish","type":"post","link":"https:\/\/twodots.gr\/bg\/causal-rag-reranking-sosti-apantisi\/","title":{"rendered":"Causal RAG: \u03cc\u03c4\u03b1\u03bd \u03b7 \u03bf\u03bc\u03bf\u03b9\u03cc\u03c4\u03b7\u03c4\u03b1 \u03bb\u03ad\u03be\u03b5\u03c9\u03bd \u03b4\u03b5\u03bd \u03b2\u03c1\u03af\u03c3\u03ba\u03b5\u03b9 \u03c4\u03b7 \u03c3\u03c9\u03c3\u03c4\u03ae \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7"},"content":{"rendered":"<div class=\"td-article-lede\">\n<p><strong>\u0391\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7 \u03c0\u03c1\u03ce\u03c4\u03b1:<\/strong> \u03c4\u03bf causal RAG reranking \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b2\u03bf\u03b7\u03b8\u03ae\u03c3\u03b5\u03b9 \u03cc\u03c4\u03b1\u03bd \u03ad\u03bd\u03b1 \u03b5\u03c4\u03b1\u03b9\u03c1\u03b9\u03ba\u03cc \u03c3\u03cd\u03c3\u03c4\u03b7\u03bc\u03b1 \u03b1\u03bd\u03b1\u03b6\u03ae\u03c4\u03b7\u03c3\u03b7\u03c2 \u03b1\u03bd\u03b5\u03b2\u03ac\u03b6\u03b5\u03b9 \u03ad\u03b3\u03b3\u03c1\u03b1\u03c6\u03b1 \u03c0\u03bf\u03c5 \u03b5\u03c0\u03b1\u03bd\u03b1\u03bb\u03b1\u03bc\u03b2\u03ac\u03bd\u03bf\u03c5\u03bd \u03c4\u03b9\u03c2 \u03bb\u03ad\u03be\u03b5\u03b9\u03c2 \u03c4\u03b7\u03c2 \u03b5\u03c1\u03ce\u03c4\u03b7\u03c3\u03b7\u03c2 \u03b1\u03bb\u03bb\u03ac \u03b4\u03b5\u03bd \u03c0\u03b5\u03c1\u03b9\u03ad\u03c7\u03bf\u03c5\u03bd \u03c4\u03b7\u03bd \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7. \u0397 \u03bc\u03ad\u03b8\u03bf\u03b4\u03bf\u03c2 \u03b1\u03c6\u03b1\u03b9\u03c1\u03b5\u03af \u03b1\u03c0\u03cc \u03ba\u03ac\u03b8\u03b5 \u03c5\u03c0\u03bf\u03c8\u03ae\u03c6\u03b9\u03bf \u03c4\u03bf \u03ba\u03bf\u03b9\u03bd\u03cc \u03bb\u03b5\u03be\u03b9\u03bb\u03cc\u03b3\u03b9\u03bf \u03bc\u03b5 \u03c4\u03bf query \u03ba\u03b1\u03b9 \u03b5\u03be\u03b5\u03c4\u03ac\u03b6\u03b5\u03b9 \u03b1\u03bd \u03bf\u03b9 \u03cc\u03c1\u03bf\u03b9 \u03c0\u03bf\u03c5 \u03b1\u03c0\u03bf\u03bc\u03ad\u03bd\u03bf\u03c5\u03bd \u03c3\u03c5\u03bd\u03b4\u03ad\u03bf\u03bd\u03c4\u03b1\u03b9 \u03bc\u03b5 \u03c4\u03bf \u03b6\u03b7\u03c4\u03bf\u03cd\u03bc\u03b5\u03bd\u03bf evidence.<\/p>\n<p>\u0394\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03ba\u03b1\u03b8\u03bf\u03bb\u03b9\u03ba\u03ae \u03b1\u03bd\u03b1\u03b2\u03ac\u03b8\u03bc\u03b9\u03c3\u03b7 \u03c4\u03bf\u03c5 retrieval. \u03a3\u03c4\u03b7 \u03bc\u03b5\u03bb\u03ad\u03c4\u03b7 \u03b1\u03c0\u03ad\u03b4\u03c9\u03c3\u03b5 \u03c3\u03b5 keyword-stuffing \u03c0\u03b5\u03c1\u03b9\u03b2\u03ac\u03bb\u03bb\u03bf\u03bd, \u03b1\u03bb\u03bb\u03ac \u03c5\u03c0\u03bf\u03c7\u03ce\u03c1\u03b7\u03c3\u03b5 \u03ad\u03bd\u03c4\u03bf\u03bd\u03b1 \u03c3\u03b5 \u03c4\u03c1\u03af\u03b1 \u03b3\u03b5\u03bd\u03b9\u03ba\u03ac BEIR benchmarks. \u0393\u03b9\u03b1 \u03bc\u03b9\u03b1 \u03b5\u03c0\u03b9\u03c7\u03b5\u03af\u03c1\u03b7\u03c3\u03b7, \u03c4\u03bf \u03ce\u03c1\u03b9\u03bc\u03bf \u03c3\u03c5\u03bc\u03c0\u03ad\u03c1\u03b1\u03c3\u03bc\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03bf: \u03b5\u03bd\u03b5\u03c1\u03b3\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7 \u03bc\u03cc\u03bd\u03bf \u03bc\u03b5\u03c4\u03ac \u03b1\u03c0\u03cc labeled probes \u03c3\u03c4\u03bf \u03b4\u03b9\u03ba\u03cc \u03c4\u03b7\u03c2 corpus, \u03c3\u03cd\u03b3\u03ba\u03c1\u03b9\u03c3\u03b7 \u03bc\u03b5 \u03c4\u03bf baseline \u03ba\u03b1\u03b9 \u03b1\u03c3\u03c6\u03b1\u03bb\u03ad\u03c2 fallback \u03cc\u03c4\u03b1\u03bd \u03c4\u03bf \u03cc\u03c6\u03b5\u03bb\u03bf\u03c2 \u03b4\u03b5\u03bd \u03b1\u03c0\u03bf\u03b4\u03b5\u03b9\u03ba\u03bd\u03cd\u03b5\u03c4\u03b1\u03b9.<\/p>\n<\/div>\n<div class=\"td-article-toc\">\n<div class=\"td-toc-title\">\u0421\u044a\u0434\u044a\u0440\u0436\u0430\u043d\u0438\u0435<\/div>\n<ul>\n<li><a href=\"#giati-similarity-lathos-eggrafo\">\u0393\u03b9\u03b1\u03c4\u03af \u03c4\u03bf similarity \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b5\u03c0\u03b9\u03bb\u03ad\u03be\u03b5\u03b9 \u03bb\u03ac\u03b8\u03bf\u03c2 \u03ad\u03b3\u03b3\u03c1\u03b1\u03c6\u03bf<\/a><\/li>\n<li><a href=\"#ti-einai-causal-rag-reranking\">\u03a4\u03b9 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ac \u03c4\u03bf causal RAG reranking<\/a><\/li>\n<li><a href=\"#attention-score-choris-training\">\u03a0\u03ce\u03c2 \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03b5\u03af \u03c4\u03bf attention-style score \u03c7\u03c9\u03c1\u03af\u03c2 \u03bd\u03ad\u03bf training<\/a><\/li>\n<li><a href=\"#semantic-absorption\">\u0393\u03b9\u03b1\u03c4\u03af \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 semantic absorption<\/a><\/li>\n<li><a href=\"#knowledge-base-471-eggrafa\">\u03a4\u03b9 \u03ad\u03b4\u03b5\u03b9\u03be\u03b5 \u03b7 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ae \u03b2\u03ac\u03c3\u03b7 \u03b3\u03bd\u03ce\u03c3\u03b7\u03c2 \u03c4\u03c9\u03bd 471 \u03b5\u03b3\u03b3\u03c1\u03ac\u03c6\u03c9\u03bd<\/a><\/li>\n<li><a href=\"#diagnostic-keyword-stuffing\">\u03a4\u03bf diagnostic test \u03b3\u03b9\u03b1 keyword stuffing<\/a><\/li>\n<li><a href=\"#beir-arnitika-apotelesmata\">\u03a4\u03b1 \u03b1\u03c1\u03bd\u03b7\u03c4\u03b9\u03ba\u03ac \u03b1\u03c0\u03bf\u03c4\u03b5\u03bb\u03ad\u03c3\u03bc\u03b1\u03c4\u03b1 \u03c3\u03c4\u03b1 BEIR benchmarks \u03b1\u03bb\u03bb\u03ac\u03b6\u03bf\u03c5\u03bd \u03c4\u03bf \u03c3\u03c5\u03bc\u03c0\u03ad\u03c1\u03b1\u03c3\u03bc\u03b1<\/a><\/li>\n<li><a href=\"#calibration-gate\">\u03a4\u03bf calibration gate \u03c0\u03c1\u03b9\u03bd \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae<\/a><\/li>\n<li><a href=\"#kostos-idiotikotita-exartiseis\">\u039a\u03cc\u03c3\u03c4\u03bf\u03c2, \u03b9\u03b4\u03b9\u03c9\u03c4\u03b9\u03ba\u03cc\u03c4\u03b7\u03c4\u03b1 \u03ba\u03b1\u03b9 \u03c4\u03b5\u03c7\u03bd\u03b9\u03ba\u03ad\u03c2 \u03b5\u03be\u03b1\u03c1\u03c4\u03ae\u03c3\u03b5\u03b9\u03c2<\/a><\/li>\n<li><a href=\"#epicheirimatiki-axia\">\u03a4\u03b9 \u03c3\u03b7\u03bc\u03b1\u03af\u03bd\u03b5\u03b9 \u03b3\u03b9\u03b1 \u03ad\u03bd\u03b1 \u03b5\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03b7\u03c3\u03b9\u03b1\u03ba\u03cc RAG<\/a><\/li>\n<li><a href=\"#epta-vimata-pilot\">\u0395\u03c0\u03c4\u03ac \u03b2\u03ae\u03bc\u03b1\u03c4\u03b1 \u03b3\u03b9\u03b1 \u03b1\u03c3\u03c6\u03b1\u03bb\u03ad\u03c2 pilot<\/a><\/li>\n<li><a href=\"#periorismoi-symperasma\">\u03a0\u03b5\u03c1\u03b9\u03bf\u03c1\u03b9\u03c3\u03bc\u03bf\u03af \u03ba\u03b1\u03b9 \u03c0\u03c1\u03b1\u03ba\u03c4\u03b9\u03ba\u03cc \u03c3\u03c5\u03bc\u03c0\u03ad\u03c1\u03b1\u03c3\u03bc\u03b1<\/a><\/li>\n<\/ul>\n<\/div>\n<h2 id=\"giati-similarity-lathos-eggrafo\">\u0393\u03b9\u03b1\u03c4\u03af \u03c4\u03bf similarity \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b5\u03c0\u03b9\u03bb\u03ad\u03be\u03b5\u03b9 \u03bb\u03ac\u03b8\u03bf\u03c2 \u03ad\u03b3\u03b3\u03c1\u03b1\u03c6\u03bf<\/h2>\n<p>\u0388\u03bd\u03b1 \u03c4\u03c5\u03c0\u03b9\u03ba\u03cc RAG \u03c3\u03cd\u03c3\u03c4\u03b7\u03bc\u03b1 \u03bc\u03b5\u03c4\u03b1\u03c4\u03c1\u03ad\u03c0\u03b5\u03b9 \u03c4\u03b7\u03bd \u03b5\u03c1\u03ce\u03c4\u03b7\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03c4\u03b1 \u03ad\u03b3\u03b3\u03c1\u03b1\u03c6\u03b1 \u03c3\u03b5 embeddings, \u03c5\u03c0\u03bf\u03bb\u03bf\u03b3\u03af\u03b6\u03b5\u03b9 cosine similarity \u03ba\u03b1\u03b9 \u03ba\u03c1\u03b1\u03c4\u03ac \u03c4\u03b1 \u03ba\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03b1 \u03c5\u03c0\u03bf\u03c8\u03ae\u03c6\u03b9\u03b1. \u039c\u03c0\u03bf\u03c1\u03b5\u03af \u03ad\u03c0\u03b5\u03b9\u03c4\u03b1 \u03bd\u03b1 \u03c0\u03c1\u03bf\u03c3\u03b8\u03ad\u03c3\u03b5\u03b9 cross-encoder reranker. \u0397 \u03bb\u03bf\u03b3\u03b9\u03ba\u03ae \u03b5\u03af\u03bd\u03b1\u03b9 \u03b5\u03cd\u03bb\u03bf\u03b3\u03b7: \u03ad\u03bd\u03b1 \u03c3\u03c7\u03b5\u03c4\u03b9\u03ba\u03cc \u03ad\u03b3\u03b3\u03c1\u03b1\u03c6\u03bf \u03b8\u03b1 \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03b2\u03c1\u03af\u03c3\u03ba\u03b5\u03c4\u03b1\u03b9 \u03ba\u03bf\u03bd\u03c4\u03ac \u03c3\u03b7\u03bc\u03b1\u03c3\u03b9\u03bf\u03bb\u03bf\u03b3\u03b9\u03ba\u03ac \u03c3\u03c4\u03b7\u03bd \u03b5\u03c1\u03ce\u03c4\u03b7\u03c3\u03b7. \u038c\u03bc\u03c9\u03c2 \u03b7 \u03bf\u03bc\u03bf\u03b9\u03cc\u03c4\u03b7\u03c4\u03b1 \u03bc\u03b5\u03c4\u03c1\u03ac \u03b1\u03bd \u03b4\u03cd\u03bf \u03ba\u03b5\u03af\u03bc\u03b5\u03bd\u03b1 \u03bc\u03b9\u03bb\u03bf\u03cd\u03bd \u03b3\u03b9\u03b1 \u03c0\u03b1\u03c1\u03cc\u03bc\u03bf\u03b9\u03bf \u03b8\u03ad\u03bc\u03b1, \u03cc\u03c7\u03b9 \u03b1\u03bd \u03c4\u03bf \u03ad\u03bd\u03b1 \u03c0\u03b5\u03c1\u03b9\u03ad\u03c7\u03b5\u03b9 \u03c4\u03b1 \u03c3\u03c4\u03bf\u03b9\u03c7\u03b5\u03af\u03b1 \u03c0\u03bf\u03c5 \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03bf\u03bd\u03c4\u03b1\u03b9 \u03b3\u03b9\u03b1 \u03c4\u03b7 \u03c3\u03c9\u03c3\u03c4\u03ae \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7.<\/p>\n<p>\u0397 \u03b5\u03c1\u03b3\u03b1\u03c3\u03af\u03b1 <em>From Association to Causation<\/em> \u03be\u03b5\u03ba\u03b9\u03bd\u03ac \u03b1\u03c0\u03cc \u03ad\u03bd\u03b1 \u03b5\u03c4\u03b1\u03b9\u03c1\u03b9\u03ba\u03cc \u03c0\u03b1\u03c1\u03ac\u03b4\u03b5\u03b9\u03b3\u03bc\u03b1 \u03b3\u03b9\u03b1 \u03c4\u03b7\u03bd \u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7 \u03b1\u03c3\u03c6\u03ac\u03bb\u03b5\u03b9\u03b1\u03c2 \u03b4\u03b9\u03b1\u03c3\u03c5\u03bd\u03bf\u03c1\u03b9\u03b1\u03ba\u03ae\u03c2 \u03bc\u03b5\u03c4\u03b1\u03c6\u03bf\u03c1\u03ac\u03c2 \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd. \u0388\u03b3\u03b3\u03c1\u03b1\u03c6\u03b1 \u03b3\u03b9\u03b1 automotive data \u03b1\u03bd\u03ad\u03b2\u03b7\u03ba\u03b1\u03bd \u03c8\u03b7\u03bb\u03ac \u03b5\u03c0\u03b5\u03b9\u03b4\u03ae \u03b5\u03c0\u03b1\u03bd\u03b1\u03bb\u03ac\u03bc\u03b2\u03b1\u03bd\u03b1\u03bd \u03c3\u03c5\u03c7\u03bd\u03ac \u03cc\u03c1\u03bf\u03c5\u03c2 \u03cc\u03c0\u03c9\u03c2 \u00abdata\u00bb, \u00abcross-border\u00bb, \u00absecurity\u00bb \u03ba\u03b1\u03b9 \u00abassessment\u00bb. \u0397 \u03bf\u03b4\u03b7\u03b3\u03af\u03b1 \u03c0\u03bf\u03c5 \u03c0\u03b5\u03c1\u03b9\u03b5\u03af\u03c7\u03b5 \u03c4\u03b7 \u03b6\u03b7\u03c4\u03bf\u03cd\u03bc\u03b5\u03bd\u03b7 \u03b4\u03b9\u03b1\u03b4\u03b9\u03ba\u03b1\u03c3\u03af\u03b1 \u03ad\u03bc\u03b5\u03b9\u03bd\u03b5 \u03c3\u03c4\u03b7\u03bd \u03ad\u03ba\u03c4\u03b7 \u03b8\u03ad\u03c3\u03b7, \u03b5\u03c0\u03b5\u03b9\u03b4\u03ae \u03b5\u03be\u03b7\u03b3\u03bf\u03cd\u03c3\u03b5 \u03c4\u03b1 \u03b2\u03ae\u03bc\u03b1\u03c4\u03b1 \u03bc\u03b5 \u03c0\u03b9\u03bf \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03b9\u03ba\u03cc \u03ba\u03b1\u03b9 \u03b5\u03be\u03b5\u03b9\u03b4\u03b9\u03ba\u03b5\u03c5\u03bc\u03ad\u03bd\u03bf \u03bb\u03b5\u03be\u03b9\u03bb\u03cc\u03b3\u03b9\u03bf.<\/p>\n<p>\u0393\u03b9\u03b1 \u03bc\u03b9\u03b1 \u03b5\u03c0\u03b9\u03c7\u03b5\u03af\u03c1\u03b7\u03c3\u03b7, \u03b1\u03c5\u03c4\u03cc \u03b5\u03af\u03bd\u03b1\u03b9 \u03c0\u03c1\u03cc\u03b2\u03bb\u03b7\u03bc\u03b1 \u03c0\u03c1\u03bf\u03ca\u03cc\u03bd\u03c4\u03bf\u03c2 \u03ba\u03b1\u03b9 \u03cc\u03c7\u03b9 \u03bc\u03cc\u03bd\u03bf ranking metric. \u0391\u03bd \u03c4\u03bf \u03bb\u03ac\u03b8\u03bf\u03c2 evidence \u03bc\u03c0\u03b5\u03b9 \u03c3\u03c4\u03bf prompt, \u03b1\u03ba\u03cc\u03bc\u03b7 \u03ba\u03b1\u03b9 \u03ad\u03bd\u03b1 \u03b9\u03c3\u03c7\u03c5\u03c1\u03cc LLM \u03c0\u03b5\u03c1\u03b9\u03bf\u03c1\u03af\u03b6\u03b5\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc \u03b1\u03bd\u03b5\u03c0\u03b1\u03c1\u03ba\u03ad\u03c2 context. \u0397 \u03b1\u03be\u03b9\u03cc\u03c0\u03b9\u03c3\u03c4\u03b7 \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7 \u03be\u03b5\u03ba\u03b9\u03bd\u03ac \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03b1\u03bd\u03ac\u03ba\u03c4\u03b7\u03c3\u03b7, \u03cc\u03c0\u03c9\u03c2 \u03c6\u03b1\u03af\u03bd\u03b5\u03c4\u03b1\u03b9 \u03ba\u03b1\u03b9 \u03c3\u03c4\u03b7\u03bd \u03c0\u03c1\u03b1\u03ba\u03c4\u03b9\u03ba\u03ae \u03b1\u03c1\u03c7\u03b9\u03c4\u03b5\u03ba\u03c4\u03bf\u03bd\u03b9\u03ba\u03ae \u03b5\u03bd\u03cc\u03c2 <a href=\"https:\/\/twodots.gr\/private-chatbot-rag-knowledge-base-business\/\">private chatbot \u03bc\u03b5 RAG \u03c0\u03ac\u03bd\u03c9 \u03c3\u03c4\u03b7\u03bd \u03b5\u03c4\u03b1\u03b9\u03c1\u03b9\u03ba\u03ae \u03b3\u03bd\u03ce\u03c3\u03b7<\/a>.<\/p>\n<h2 id=\"ti-einai-causal-rag-reranking\">\u03a4\u03b9 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ac \u03c4\u03bf causal RAG reranking<\/h2>\n<p>\u0397 \u03c0\u03c1\u03cc\u03c4\u03b1\u03c3\u03b7 \u03b4\u03b5\u03bd \u03ba\u03b1\u03c4\u03b1\u03c3\u03ba\u03b5\u03c5\u03ac\u03b6\u03b5\u03b9 \u03b3\u03c1\u03ac\u03c6\u03bf \u03b1\u03b9\u03c4\u03af\u03c9\u03bd \u03bc\u03ad\u03c3\u03b1 \u03c3\u03c4\u03b1 \u03ad\u03b3\u03b3\u03c1\u03b1\u03c6\u03b1 \u03ba\u03b1\u03b9 \u03b4\u03b5\u03bd \u03b6\u03b7\u03c4\u03ac \u03b1\u03c0\u03cc LLM \u03bd\u03b1 \u03b1\u03ba\u03bf\u03bb\u03bf\u03c5\u03b8\u03ae\u03c3\u03b5\u03b9 causal paths. \u039c\u03bf\u03bd\u03c4\u03b5\u03bb\u03bf\u03c0\u03bf\u03b9\u03b5\u03af \u03c4\u03b7 \u03b4\u03b9\u03b1\u03b4\u03b9\u03ba\u03b1\u03c3\u03af\u03b1 retrieval. \u0393\u03b9\u03b1 \u03ba\u03ac\u03b8\u03b5 \u03b1\u03bd\u03b1\u03ba\u03c4\u03b7\u03bc\u03ad\u03bd\u03bf \u03ad\u03b3\u03b3\u03c1\u03b1\u03c6\u03bf, \u03c4\u03bf \u03bb\u03b1\u03bd\u03b8\u03ac\u03bd\u03bf\u03bd \u03c3\u03cd\u03bd\u03bf\u03bb\u03bf <strong>A<\/strong> \u03c0\u03b5\u03c1\u03b9\u03bb\u03b1\u03bc\u03b2\u03ac\u03bd\u03b5\u03b9 \u03c4\u03bf\u03c5\u03c2 \u03cc\u03c1\u03bf\u03c5\u03c2 \u03c0\u03bf\u03c5 \u03bc\u03bf\u03b9\u03c1\u03ac\u03b6\u03bf\u03bd\u03c4\u03b1\u03b9 \u03b7 \u03b5\u03c1\u03ce\u03c4\u03b7\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03c4\u03bf \u03ad\u03b3\u03b3\u03c1\u03b1\u03c6\u03bf, \u03b5\u03af\u03c4\u03b5 \u03bc\u03b5 \u03b1\u03ba\u03c1\u03b9\u03b2\u03ae \u03b1\u03bd\u03c4\u03b9\u03c3\u03c4\u03bf\u03af\u03c7\u03b9\u03c3\u03b7 \u03b5\u03af\u03c4\u03b5 \u03bc\u03b5 \u03c3\u03b7\u03bc\u03b1\u03c3\u03b9\u03bf\u03bb\u03bf\u03b3\u03b9\u03ba\u03ae \u03b5\u03b3\u03b3\u03cd\u03c4\u03b7\u03c4\u03b1. \u03a4\u03bf <strong>B<\/strong> \u03c0\u03b5\u03c1\u03b9\u03bb\u03b1\u03bc\u03b2\u03ac\u03bd\u03b5\u03b9 \u03c4\u03bf \u03c5\u03c0\u03bf\u03bb\u03b5\u03b9\u03c0\u03cc\u03bc\u03b5\u03bd\u03bf, \u03c3\u03c4\u03b1\u03b8\u03bc\u03b9\u03c3\u03bc\u03ad\u03bd\u03bf \u03bb\u03b5\u03be\u03b9\u03bb\u03cc\u03b3\u03b9\u03bf \u03c4\u03bf\u03c5 \u03b5\u03b3\u03b3\u03c1\u03ac\u03c6\u03bf\u03c5.<\/p>\n<p>\u03a3\u03c4\u03bf \u03b3\u03c1\u03ac\u03c6\u03b7\u03bc\u03b1 \u03c4\u03c9\u03bd \u03c3\u03c5\u03b3\u03b3\u03c1\u03b1\u03c6\u03ad\u03c9\u03bd, \u03c4\u03bf A \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03b5\u03af \u03c9\u03c2 \u03ba\u03bf\u03b9\u03bd\u03ae \u03b1\u03b9\u03c4\u03af\u03b1 \u03c4\u03b7\u03c2 \u03b5\u03c1\u03ce\u03c4\u03b7\u03c3\u03b7\u03c2 \u03ba\u03b1\u03b9 \u03c4\u03bf\u03c5 \u03b5\u03b3\u03b3\u03c1\u03ac\u03c6\u03bf\u03c5, \u03b5\u03bd\u03ce \u03c4\u03bf B \u03c3\u03c5\u03bd\u03b4\u03ad\u03b5\u03b9 \u03c4\u03bf \u03ad\u03b3\u03b3\u03c1\u03b1\u03c6\u03bf \u03bc\u03b5 \u03c4\u03b7\u03bd \u03b9\u03b4\u03b1\u03bd\u03b9\u03ba\u03ae \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7. \u03a4\u03bf \u03b1\u03bd\u03b1\u03ba\u03c4\u03b7\u03bc\u03ad\u03bd\u03bf \u03ad\u03b3\u03b3\u03c1\u03b1\u03c6\u03bf \u03b5\u03af\u03bd\u03b1\u03b9 collider \u03c3\u03c4\u03b7 \u03b4\u03bf\u03bc\u03ae A \u2192 d \u2190 B. \u0397 \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ae \u03c4\u03bf\u03c5 \u03c9\u03c2 \u03c5\u03c0\u03bf\u03c8\u03b7\u03c6\u03af\u03bf\u03c5 \u00ab\u03b1\u03bd\u03bf\u03af\u03b3\u03b5\u03b9\u00bb \u03bc\u03b9\u03b1 \u03c3\u03c5\u03c3\u03c7\u03ad\u03c4\u03b9\u03c3\u03b7 \u03b1\u03bd\u03ac\u03bc\u03b5\u03c3\u03b1 \u03c3\u03c4\u03b7\u03bd \u03b5\u03c1\u03ce\u03c4\u03b7\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03c4\u03bf B, \u03c4\u03b7\u03bd \u03bf\u03c0\u03bf\u03af\u03b1 \u03b7 \u03bc\u03ad\u03b8\u03bf\u03b4\u03bf\u03c2 \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03b5\u03af \u03c9\u03c2 \u03ba\u03af\u03bd\u03b7\u03c4\u03c1\u03bf \u03b3\u03b9\u03b1 \u03bd\u03ad\u03bf score.<\/p>\n<p>\u0397 \u03bf\u03bd\u03bf\u03bc\u03b1\u03c3\u03af\u03b1 \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03c0\u03c1\u03bf\u03c3\u03bf\u03c7\u03ae. \u039f\u03b9 \u03c3\u03c5\u03b3\u03b3\u03c1\u03b1\u03c6\u03b5\u03af\u03c2 \u03b4\u03b7\u03bb\u03ce\u03bd\u03bf\u03c5\u03bd \u03c1\u03b7\u03c4\u03ac \u03cc\u03c4\u03b9 \u03b4\u03b5\u03bd \u03b5\u03ba\u03c4\u03b9\u03bc\u03bf\u03cd\u03bd causal effect \u03ba\u03b1\u03b9 \u03cc\u03c4\u03b9 \u03c4\u03bf score \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03c4\u03b1\u03c5\u03c4\u03bf\u03c0\u03bf\u03b9\u03b7\u03bc\u03ad\u03bd\u03bf causal estimand. \u039f \u03b3\u03c1\u03ac\u03c6\u03bf\u03c2 \u03c0\u03b1\u03c1\u03ad\u03c7\u03b5\u03b9 \u03b4\u03bf\u03bc\u03b9\u03ba\u03ae \u03ba\u03b1\u03b9 motivational \u03b4\u03b9\u03ba\u03b1\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7\u00b7 \u03c4\u03bf \u03b1\u03bd \u03b7 \u03b9\u03b4\u03ad\u03b1 \u03b4\u03bf\u03c5\u03bb\u03b5\u03cd\u03b5\u03b9 \u03ba\u03c1\u03af\u03bd\u03b5\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc \u03c4\u03b1 \u03c0\u03b5\u03b9\u03c1\u03ac\u03bc\u03b1\u03c4\u03b1.<\/p>\n<aside class=\"td-article-note\"><strong>\u038c\u03c1\u03b9\u03bf \u03c4\u03bf\u03c5 \u03cc\u03c1\u03bf\u03c5 \u00abcausal\u00bb:<\/strong> \u03b7 \u03c4\u03b5\u03c7\u03bd\u03b9\u03ba\u03ae \u03b5\u03af\u03bd\u03b1\u03b9 causally motivated heuristic \u03b3\u03b9\u03b1 \u03c4\u03bf terminal retrieval. \u0394\u03b5\u03bd \u03b1\u03c0\u03bf\u03b4\u03b5\u03b9\u03ba\u03bd\u03cd\u03b5\u03b9 \u03cc\u03c4\u03b9 \u03ad\u03bd\u03b1 \u03ad\u03b3\u03b3\u03c1\u03b1\u03c6\u03bf \u03c0\u03c1\u03bf\u03ba\u03b1\u03bb\u03b5\u03af \u03bc\u03b9\u03b1 \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03b4\u03b5\u03bd \u03b1\u03bd\u03c4\u03b9\u03ba\u03b1\u03b8\u03b9\u03c3\u03c4\u03ac relevance labels, offline evaluation \u03ae domain review.<\/aside>\n<div class=\"td-comparison td-comparison-cards td-comparison-cards--horizontal\">\n<div class=\"td-comparison-grid td-comparison-grid--three\">\n<div class=\"td-platform-card\">\n<p class=\"td-comparison-title\">Similarity baseline<\/p>\n<p>\u0391\u03bd\u03c4\u03b1\u03bc\u03b5\u03af\u03b2\u03b5\u03b9 \u03c4\u03b7 \u03c3\u03c5\u03bd\u03bf\u03bb\u03b9\u03ba\u03ae \u03c3\u03b7\u03bc\u03b1\u03c3\u03b9\u03bf\u03bb\u03bf\u03b3\u03b9\u03ba\u03ae \u03b5\u03b3\u03b3\u03cd\u03c4\u03b7\u03c4\u03b1 \u03ba\u03b1\u03b9 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03c0\u03b1\u03c1\u03b1\u03c3\u03c5\u03c1\u03b8\u03b5\u03af \u03cc\u03c4\u03b1\u03bd \u03ac\u03c3\u03c7\u03b5\u03c4\u03b1 \u03ad\u03b3\u03b3\u03c1\u03b1\u03c6\u03b1 \u03b5\u03c0\u03b1\u03bd\u03b1\u03bb\u03b1\u03bc\u03b2\u03ac\u03bd\u03bf\u03c5\u03bd \u03c4\u03bf query vocabulary.<\/p>\n<div class=\"td-badge-row\"><span class=\"td-badge\">\u0393\u03c1\u03ae\u03b3\u03bf\u03c1\u03bf<\/span><span class=\"td-badge\">\u0399\u03c3\u03c7\u03c5\u03c1\u03cc baseline<\/span><\/div>\n<\/div>\n<div class=\"td-platform-card\">\n<p class=\"td-comparison-title\">Cross-encoder<\/p>\n<p>\u0392\u03b1\u03b8\u03bc\u03bf\u03bb\u03bf\u03b3\u03b5\u03af query \u03ba\u03b1\u03b9 \u03ad\u03b3\u03b3\u03c1\u03b1\u03c6\u03bf \u03bc\u03b1\u03b6\u03af. \u03a3\u03c4\u03bf \u03bc\u03b9\u03ba\u03c1\u03cc diagnostic corpus \u03b2\u03b5\u03bb\u03c4\u03af\u03c9\u03c3\u03b5 \u03bb\u03af\u03b3\u03bf \u03c4\u03bf target rank, \u03b1\u03bb\u03bb\u03ac \u03b4\u03b5\u03bd \u03ad\u03bb\u03c5\u03c3\u03b5 \u03c4\u03bf keyword-stuffing failure.<\/p>\n<div class=\"td-badge-row\"><span class=\"td-badge\">Supervised<\/span><span class=\"td-badge\">2,63 mean rank<\/span><\/div>\n<\/div>\n<div class=\"td-platform-card td-platform-card--navy\">\n<p class=\"td-comparison-title\">Causal \u03ae hybrid<\/p>\n<p>\u0392\u03b1\u03b8\u03bc\u03bf\u03bb\u03bf\u03b3\u03b5\u03af \u03c4\u03bf residual vocabulary B \u03ba\u03b1\u03b9 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03c3\u03c5\u03bd\u03b4\u03c5\u03b1\u03c3\u03c4\u03b5\u03af \u03bc\u03b5 similarity, \u03b1\u03bb\u03bb\u03ac \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03b5\u03bd\u03b5\u03c1\u03b3\u03bf\u03c0\u03bf\u03b9\u03b5\u03af\u03c4\u03b1\u03b9 \u03bc\u03cc\u03bd\u03bf \u03c3\u03b5 corpus \u03cc\u03c0\u03bf\u03c5 \u03c4\u03bf \u03cc\u03c6\u03b5\u03bb\u03bf\u03c2 \u03bc\u03b5\u03c4\u03c1\u03b9\u03ad\u03c4\u03b1\u03b9.<\/p>\n<div class=\"td-badge-row\"><span class=\"td-badge\">Training-free<\/span><span class=\"td-badge\">Calibration first<\/span><\/div>\n<\/div>\n<\/div>\n<\/div>\n<h2 id=\"attention-score-choris-training\">\u03a0\u03ce\u03c2 \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03b5\u03af \u03c4\u03bf attention-style score \u03c7\u03c9\u03c1\u03af\u03c2 \u03bd\u03ad\u03bf training<\/h2>\n<p>\u0397 \u03b4\u03b9\u03b1\u03b4\u03b9\u03ba\u03b1\u03c3\u03af\u03b1 \u03b5\u03c6\u03b1\u03c1\u03bc\u03cc\u03b6\u03b5\u03c4\u03b1\u03b9 \u03c0\u03ac\u03bd\u03c9 \u03c3\u03c4\u03bf \u03ae\u03b4\u03b7 \u03bc\u03b9\u03ba\u03c1\u03cc candidate set \u03c4\u03bf\u03c5 retriever. \u0388\u03bd\u03b1\u03c2 keyword extractor \u03c0\u03b1\u03c1\u03ac\u03b3\u03b5\u03b9 \u03c3\u03c4\u03b1\u03b8\u03bc\u03b9\u03c3\u03bc\u03ad\u03bd\u03bf\u03c5\u03c2 \u03cc\u03c1\u03bf\u03c5\u03c2 \u03b3\u03b9\u03b1 \u03c4\u03bf query \u03ba\u03b1\u03b9 \u03ba\u03ac\u03b8\u03b5 \u03c5\u03c0\u03bf\u03c8\u03ae\u03c6\u03b9\u03bf \u03ad\u03b3\u03b3\u03c1\u03b1\u03c6\u03bf. \u038c\u03c3\u03bf\u03b9 \u03cc\u03c1\u03bf\u03b9 \u03c4\u03bf\u03c5 \u03b5\u03b3\u03b3\u03c1\u03ac\u03c6\u03bf\u03c5 \u03c4\u03b1\u03b9\u03c1\u03b9\u03ac\u03b6\u03bf\u03c5\u03bd \u03b1\u03ba\u03c1\u03b9\u03b2\u03ce\u03c2 \u03ae \u03c3\u03b7\u03bc\u03b1\u03c3\u03b9\u03bf\u03bb\u03bf\u03b3\u03b9\u03ba\u03ac \u03bc\u03b5 \u03c4\u03bf query vocabulary \u03c0\u03b5\u03c1\u03bd\u03bf\u03cd\u03bd \u03c3\u03c4\u03bf A. \u03a3\u03c4\u03b1 \u03c0\u03b5\u03b9\u03c1\u03ac\u03bc\u03b1\u03c4\u03b1 \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03ae\u03b8\u03b7\u03ba\u03b5 threshold \u03c3\u03b7\u03bc\u03b1\u03c3\u03b9\u03bf\u03bb\u03bf\u03b3\u03b9\u03ba\u03ae\u03c2 \u03b1\u03c0\u03bf\u03c1\u03c1\u03cc\u03c6\u03b7\u03c3\u03b7\u03c2 0,6.<\/p>\n<p>\u0393\u03b9\u03b1 \u03c4\u03bf\u03c5\u03c2 \u03cc\u03c1\u03bf\u03c5\u03c2 \u03c0\u03bf\u03c5 \u03b1\u03c0\u03bf\u03bc\u03ad\u03bd\u03bf\u03c5\u03bd \u03c3\u03c4\u03bf B \u03c5\u03c0\u03bf\u03bb\u03bf\u03b3\u03af\u03b6\u03b5\u03c4\u03b1\u03b9 weighted centroid embedding. \u03a4\u03bf causal-attention score \u03b5\u03af\u03bd\u03b1\u03b9 \u03b7 cosine similarity \u03b1\u03bd\u03ac\u03bc\u03b5\u03c3\u03b1 \u03c3\u03c4\u03bf embedding \u03c4\u03b7\u03c2 \u03b5\u03c1\u03ce\u03c4\u03b7\u03c3\u03b7\u03c2 \u03ba\u03b1\u03b9 \u03b1\u03c5\u03c4\u03cc \u03c4\u03bf centroid. \u0388\u03bd\u03b1 \u03ad\u03b3\u03b3\u03c1\u03b1\u03c6\u03bf \u03c0\u03bf\u03c5 \u03b1\u03c0\u03bb\u03ce\u03c2 \u03b5\u03c0\u03b1\u03bd\u03b1\u03bb\u03b1\u03bc\u03b2\u03ac\u03bd\u03b5\u03b9 \u03c4\u03b9\u03c2 \u03bb\u03ad\u03be\u03b5\u03b9\u03c2 \u03c4\u03b7\u03c2 \u03b5\u03c1\u03ce\u03c4\u03b7\u03c3\u03b7\u03c2 \u03ad\u03c7\u03b5\u03b9 \u03bc\u03b9\u03ba\u03c1\u03cc \u03ae \u03c6\u03c4\u03c9\u03c7\u03cc B \u03ba\u03b1\u03b9 \u03c4\u03b5\u03af\u03bd\u03b5\u03b9 \u03bd\u03b1 \u03c5\u03c0\u03bf\u03b2\u03b1\u03b8\u03bc\u03b9\u03c3\u03c4\u03b5\u03af. \u0388\u03bd\u03b1 \u03ad\u03b3\u03b3\u03c1\u03b1\u03c6\u03bf \u03c4\u03bf\u03c5 \u03bf\u03c0\u03bf\u03af\u03bf\u03c5 \u03c4\u03bf residual vocabulary \u03c0\u03b5\u03c1\u03b9\u03b3\u03c1\u03ac\u03c6\u03b5\u03b9 \u03c4\u03b7 \u03b4\u03b9\u03b1\u03b4\u03b9\u03ba\u03b1\u03c3\u03af\u03b1 \u03ae \u03c4\u03bf answer-bearing \u03c3\u03c4\u03bf\u03b9\u03c7\u03b5\u03af\u03bf \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b1\u03bd\u03ad\u03b2\u03b5\u03b9.<\/p>\n<p>\u0397 \u03bc\u03ad\u03b8\u03bf\u03b4\u03bf\u03c2 \u03b4\u03b5\u03bd \u03b1\u03c0\u03b1\u03b9\u03c4\u03b5\u03af fine-tuning \u03ba\u03b1\u03b9, \u03c3\u03cd\u03bc\u03c6\u03c9\u03bd\u03b1 \u03bc\u03b5 \u03c4\u03b7\u03bd \u03c0\u03c1\u03bf\u03c4\u03b5\u03b9\u03bd\u03cc\u03bc\u03b5\u03bd\u03b7 \u03c1\u03bf\u03ae, \u03b4\u03b5\u03bd \u03c0\u03c1\u03bf\u03c3\u03b8\u03ad\u03c4\u03b5\u03b9 LLM call \u03c4\u03b7\u03bd \u03ce\u03c1\u03b1 \u03c4\u03b7\u03c2 \u03b5\u03c1\u03ce\u03c4\u03b7\u03c3\u03b7\u03c2. \u03a0\u03c1\u03bf\u03c3\u03b8\u03ad\u03c4\u03b5\u03b9 keyword extraction \u03ba\u03b1\u03b9 embeddings \u03b3\u03b9\u03b1 \u03b4\u03b5\u03ba\u03ac\u03b4\u03b5\u03c2 residual terms \u03c3\u03b5 candidate set \u03bc\u03bf\u03bd\u03bf\u03c8\u03ae\u03c6\u03b9\u03bf\u03c5 \u03ae \u03c7\u03b1\u03bc\u03b7\u03bb\u03bf\u03cd \u03b4\u03b9\u03c8\u03ae\u03c6\u03b9\u03bf\u03c5 \u03bc\u03b5\u03b3\u03ad\u03b8\u03bf\u03c5\u03c2. \u0391\u03c5\u03c4\u03cc \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03bc\u03b9\u03ba\u03c1\u03cc \u03c3\u03b5 \u03c3\u03c7\u03ad\u03c3\u03b7 \u03bc\u03b5 \u03c4\u03bf \u03b1\u03c1\u03c7\u03b9\u03ba\u03cc retrieval, \u03b1\u03bb\u03bb\u03ac \u03b4\u03b5\u03bd \u03b1\u03c0\u03bf\u03c4\u03b5\u03bb\u03b5\u03af \u03ba\u03b1\u03b8\u03bf\u03bb\u03b9\u03ba\u03ae \u03c5\u03c0\u03cc\u03c3\u03c7\u03b5\u03c3\u03b7 latency \u03b3\u03b9\u03b1 \u03ba\u03ac\u03b8\u03b5 \u03c5\u03c0\u03bf\u03b4\u03bf\u03bc\u03ae.<\/p>\n<h2 id=\"semantic-absorption\">\u0393\u03b9\u03b1\u03c4\u03af \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 semantic absorption<\/h2>\n<p>\u0397 exact-match \u03b5\u03ba\u03b4\u03bf\u03c7\u03ae \u03b1\u03c6\u03b1\u03b9\u03c1\u03bf\u03cd\u03c3\u03b5 \u03b1\u03c0\u03cc \u03c4\u03bf B \u03bc\u03cc\u03bd\u03bf \u03c4\u03bf\u03c5\u03c2 \u03cc\u03c1\u03bf\u03c5\u03c2 \u03c0\u03bf\u03c5 \u03c4\u03b1\u03af\u03c1\u03b9\u03b1\u03b6\u03b1\u03bd \u03b1\u03c5\u03c4\u03bf\u03cd\u03c3\u03b9\u03bf\u03b9 \u03bc\u03b5 \u03c4\u03bf query. \u03a4\u03bf \u03c0\u03c1\u03cc\u03b2\u03bb\u03b7\u03bc\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03cc\u03c4\u03b9 \u03ad\u03bd\u03b1 distractor \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03b5\u03af \u03c3\u03c5\u03bd\u03ce\u03bd\u03c5\u03bc\u03b1 \u03ae \u03b3\u03b5\u03b9\u03c4\u03bf\u03bd\u03b9\u03ba\u03ae \u03bf\u03c1\u03bf\u03bb\u03bf\u03b3\u03af\u03b1 \u03ba\u03b1\u03b9 \u03bd\u03b1 \u03ba\u03c1\u03b1\u03c4\u03ac \u03c3\u03c4\u03bf B \u03b1\u03c1\u03ba\u03b5\u03c4\u03cc \u03b5\u03c0\u03b9\u03c6\u03b1\u03bd\u03b5\u03b9\u03b1\u03ba\u03cc \u03c3\u03ae\u03bc\u03b1 \u03ce\u03c3\u03c4\u03b5 \u03bd\u03b1 \u03b2\u03b1\u03b8\u03bc\u03bf\u03bb\u03bf\u03b3\u03b7\u03b8\u03b5\u03af \u03c8\u03b7\u03bb\u03ac. \u0397 semantic absorption \u03bc\u03b5\u03c4\u03b1\u03c6\u03ad\u03c1\u03b5\u03b9 \u03c3\u03c4\u03bf A \u03ba\u03b1\u03b9 \u03c4\u03bf\u03c5\u03c2 \u03cc\u03c1\u03bf\u03c5\u03c2 \u03c0\u03bf\u03c5 \u03b5\u03af\u03bd\u03b1\u03b9 \u03ba\u03bf\u03bd\u03c4\u03ac \u03c3\u03c4\u03b1 query terms \u03c3\u03c4\u03bf embedding space.<\/p>\n<p>\u03a3\u03c4\u03bf \u03b5\u03bb\u03b5\u03b3\u03c7\u03cc\u03bc\u03b5\u03bd\u03bf corpus, \u03b7 exact-match \u03c0\u03b1\u03c1\u03b1\u03bb\u03bb\u03b1\u03b3\u03ae \u03b5\u03af\u03c7\u03b5 \u03b1\u03c3\u03c5\u03bd\u03b5\u03c0\u03ae \u03c3\u03c5\u03bc\u03c0\u03b5\u03c1\u03b9\u03c6\u03bf\u03c1\u03ac. \u0397 semantic \u03c0\u03b1\u03c1\u03b1\u03bb\u03bb\u03b1\u03b3\u03ae \u03ad\u03c6\u03b5\u03c1\u03b5 \u03c4\u03bf answer-bearing \u03ad\u03b3\u03b3\u03c1\u03b1\u03c6\u03bf \u03c3\u03c4\u03b7\u03bd \u03c0\u03c1\u03ce\u03c4\u03b7 \u03ae \u03b4\u03b5\u03cd\u03c4\u03b5\u03c1\u03b7 \u03b8\u03ad\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03c3\u03c4\u03b1 \u03bf\u03ba\u03c4\u03ce \u03b8\u03ad\u03bc\u03b1\u03c4\u03b1. \u0397 \u03bc\u03ad\u03c3\u03b7 \u03b8\u03ad\u03c3\u03b7 \u03b2\u03b5\u03bb\u03c4\u03b9\u03ce\u03b8\u03b7\u03ba\u03b5 \u03b1\u03c0\u03cc 2,88 \u03c3\u03c4\u03bf similarity baseline \u03c3\u03b5 1,25, \u03b5\u03bd\u03ce \u03b7 \u03bc\u03ad\u03c3\u03b7 \u03b8\u03ad\u03c3\u03b7 \u03c4\u03c9\u03bd \u03b4\u03cd\u03bf keyword-stuffed distractors \u03b1\u03bd\u03ac \u03b8\u03ad\u03bc\u03b1 \u03bc\u03b5\u03c4\u03b1\u03ba\u03b9\u03bd\u03ae\u03b8\u03b7\u03ba\u03b5 \u03b1\u03c0\u03cc 2,00 \u03c3\u03b5 4,50.<\/p>\n<p>\u03a4\u03bf hybrid score, \u03bc\u03b5 \u03af\u03c3\u03bf \u03b2\u03ac\u03c1\u03bf\u03c2 \u03c3\u03b5 \u03ba\u03b1\u03bd\u03bf\u03bd\u03b9\u03ba\u03bf\u03c0\u03bf\u03b9\u03b7\u03bc\u03ad\u03bd\u03bf similarity \u03ba\u03b1\u03b9 causal-attention score, \u03ad\u03c6\u03c4\u03b1\u03c3\u03b5 \u03bc\u03ad\u03c3\u03b7 \u03b8\u03ad\u03c3\u03b7 1,38 \u03ba\u03b1\u03b9 \u03c3\u03c4\u03b1 \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03b1 runs \u03b4\u03b5\u03bd \u03ad\u03b2\u03b1\u03bb\u03b5 \u03c4\u03bf target \u03c7\u03b1\u03bc\u03b7\u03bb\u03cc\u03c4\u03b5\u03c1\u03b1 \u03b1\u03c0\u03cc \u03c4\u03bf baseline. \u0391\u03c5\u03c4\u03cc \u03b5\u03af\u03bd\u03b1\u03b9 \u03b5\u03c0\u03b9\u03c7\u03b5\u03af\u03c1\u03b7\u03bc\u03b1 \u03b3\u03b9\u03b1 \u03c0\u03c1\u03bf\u03c3\u03b5\u03ba\u03c4\u03b9\u03ba\u03ae \u03c3\u03c5\u03bd\u03ad\u03bd\u03c9\u03c3\u03b7 \u03c3\u03b7\u03bc\u03ac\u03c4\u03c9\u03bd, \u03cc\u03c0\u03c9\u03c2 \u03c3\u03c5\u03bc\u03b2\u03b1\u03af\u03bd\u03b5\u03b9 \u03ba\u03b1\u03b9 \u03c3\u03c4\u03bf <a href=\"https:\/\/twodots.gr\/hybrid-ai-search-papers-with-code\/\">hybrid AI search \u03c0\u03bf\u03c5 \u03c3\u03c5\u03bd\u03b4\u03c5\u03ac\u03b6\u03b5\u03b9 \u03bb\u03ad\u03be\u03b5\u03b9\u03c2, embeddings \u03ba\u03b1\u03b9 fallbacks<\/a>, \u03cc\u03c7\u03b9 \u03b1\u03c0\u03cc\u03b4\u03b5\u03b9\u03be\u03b7 \u03cc\u03c4\u03b9 \u03ad\u03bd\u03b1 fixed 50\/50 \u03b2\u03ac\u03c1\u03bf\u03c2 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b2\u03ad\u03bb\u03c4\u03b9\u03c3\u03c4\u03bf \u03c0\u03b1\u03bd\u03c4\u03bf\u03cd.<\/p>\n<h2 id=\"knowledge-base-471-eggrafa\">\u03a4\u03b9 \u03ad\u03b4\u03b5\u03b9\u03be\u03b5 \u03b7 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ae \u03b2\u03ac\u03c3\u03b7 \u03b3\u03bd\u03ce\u03c3\u03b7\u03c2 \u03c4\u03c9\u03bd 471 \u03b5\u03b3\u03b3\u03c1\u03ac\u03c6\u03c9\u03bd<\/h2>\n<p>\u03a4\u03bf deployment case study \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b5 471 \u03c4\u03bf\u03c0\u03b9\u03ba\u03ac \u03b1\u03c1\u03c7\u03b5\u03af\u03b1 \u03c3\u03c5\u03bd\u03bf\u03bb\u03b9\u03ba\u03bf\u03cd \u03bc\u03b5\u03b3\u03ad\u03b8\u03bf\u03c5\u03c2 2,95 GB: \u03bd\u03cc\u03bc\u03bf\u03c5\u03c2, \u03ba\u03b1\u03bd\u03bf\u03bd\u03b9\u03c3\u03bc\u03bf\u03cd\u03c2, \u03b5\u03c3\u03c9\u03c4\u03b5\u03c1\u03b9\u03ba\u03ad\u03c2 \u03b1\u03bd\u03b1\u03c6\u03bf\u03c1\u03ad\u03c2, \u03b5\u03c0\u03b1\u03b3\u03b3\u03b5\u03bb\u03bc\u03b1\u03c4\u03b9\u03ba\u03ac \u03b2\u03b9\u03b2\u03bb\u03af\u03b1 \u03ba\u03b1\u03b9 papers \u03c3\u03b5 Word \u03ba\u03b1\u03b9 PDF. \u03a4\u03b1 \u03b1\u03c1\u03c7\u03b5\u03af\u03b1 \u03ba\u03b1\u03b8\u03b1\u03c1\u03af\u03c3\u03c4\u03b7\u03ba\u03b1\u03bd, \u03c7\u03c9\u03c1\u03af\u03c3\u03c4\u03b7\u03ba\u03b1\u03bd \u03c3\u03b5 chunks 4.096 \u03c7\u03b1\u03c1\u03b1\u03ba\u03c4\u03ae\u03c1\u03c9\u03bd \u03bc\u03b5 overlap 512 \u03ba\u03b1\u03b9 \u03b5\u03bd\u03c3\u03c9\u03bc\u03b1\u03c4\u03ce\u03b8\u03b7\u03ba\u03b1\u03bd \u03bc\u03b5 BGE-M3 \u03c3\u03b5 vectors 1.024 \u03b4\u03b9\u03b1\u03c3\u03c4\u03ac\u03c3\u03b5\u03c9\u03bd.<\/p>\n<p>\u03a3\u03c4\u03b7\u03bd \u03b5\u03c1\u03ce\u03c4\u03b7\u03c3\u03b7 \u03b3\u03b9\u03b1 \u03c4\u03b7\u03bd \u03b1\u03c3\u03c6\u03ac\u03bb\u03b5\u03b9\u03b1 \u03b4\u03b9\u03b1\u03c3\u03c5\u03bd\u03bf\u03c1\u03b9\u03b1\u03ba\u03ae\u03c2 \u03bc\u03b5\u03c4\u03b1\u03c6\u03bf\u03c1\u03ac\u03c2, \u03b7 \u03ba\u03b1\u03c4\u03ac\u03bb\u03bb\u03b7\u03bb\u03b7 \u03bf\u03b4\u03b7\u03b3\u03af\u03b1 \u03b1\u03bd\u03ad\u03b2\u03b7\u03ba\u03b5 \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03ad\u03ba\u03c4\u03b7 \u03b8\u03ad\u03c3\u03b7 \u03c3\u03c4\u03bf top 3. \u03a4\u03bf \u03b1\u03c0\u03bf\u03c4\u03ad\u03bb\u03b5\u03c3\u03bc\u03b1 \u03b1\u03c0\u03bf\u03b4\u03b5\u03b9\u03ba\u03bd\u03cd\u03b5\u03b9 \u03cc\u03c4\u03b9 \u03bf \u03bc\u03b7\u03c7\u03b1\u03bd\u03b9\u03c3\u03bc\u03cc\u03c2 \u03b4\u03b9\u03cc\u03c1\u03b8\u03c9\u03c3\u03b5 \u03ad\u03bd\u03b1 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03cc failure \u03bc\u03ad\u03c3\u03b1 \u03c3\u03b5 \u03b1\u03c5\u03c4\u03cc \u03c4\u03bf \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03bf corpus. \u0394\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03c3\u03c4\u03b1\u03c4\u03b9\u03c3\u03c4\u03b9\u03ba\u03ae \u03b1\u03c0\u03cc\u03b4\u03b5\u03b9\u03be\u03b7 \u03b3\u03b5\u03bd\u03b9\u03ba\u03ae\u03c2 \u03c5\u03c0\u03b5\u03c1\u03bf\u03c7\u03ae\u03c2: \u03c0\u03c1\u03cc\u03ba\u03b5\u03b9\u03c4\u03b1\u03b9 \u03b3\u03b9\u03b1 \u03b5\u03c0\u03b9\u03bb\u03b5\u03b3\u03bc\u03ad\u03bd\u03bf case study, \u03b5\u03bd\u03ce \u03b7 \u03b5\u03bb\u03b5\u03b3\u03c7\u03cc\u03bc\u03b5\u03bd\u03b7 \u03c0\u03bf\u03c3\u03bf\u03c4\u03b9\u03ba\u03ae \u03b4\u03b9\u03b5\u03c1\u03b5\u03cd\u03bd\u03b7\u03c3\u03b7 \u03c0\u03c1\u03bf\u03ad\u03c1\u03c7\u03b5\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc \u03c4\u03b1 \u03b5\u03c0\u03cc\u03bc\u03b5\u03bd\u03b1 \u03c0\u03b5\u03b9\u03c1\u03ac\u03bc\u03b1\u03c4\u03b1.<\/p>\n<p>\u03a4\u03bf \u03c3\u03b5\u03bd\u03ac\u03c1\u03b9\u03bf \u03b5\u03af\u03bd\u03b1\u03b9 \u03b1\u03bd\u03b1\u03b3\u03bd\u03c9\u03c1\u03af\u03c3\u03b9\u03bc\u03bf \u03c3\u03b5 knowledge managers. \u039a\u03b1\u03b8\u03ce\u03c2 \u03c3\u03c5\u03c3\u03c3\u03c9\u03c1\u03b5\u03cd\u03bf\u03bd\u03c4\u03b1\u03b9 versions, policy notes, \u03c0\u03b1\u03c1\u03bf\u03c5\u03c3\u03b9\u03ac\u03c3\u03b5\u03b9\u03c2 \u03ba\u03b1\u03b9 \u03c0\u03b1\u03c1\u03cc\u03bc\u03bf\u03b9\u03b1 manuals, \u03b7 \u03b8\u03b5\u03bc\u03b1\u03c4\u03b9\u03ba\u03ae \u03b3\u03b5\u03b9\u03c4\u03bd\u03af\u03b1\u03c3\u03b7 \u03b1\u03c5\u03be\u03ac\u03bd\u03b5\u03c4\u03b1\u03b9. \u0397 retrieval \u03b1\u03c1\u03c7\u03b9\u03c4\u03b5\u03ba\u03c4\u03bf\u03bd\u03b9\u03ba\u03ae \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03c4\u03cc\u03c4\u03b5 \u03bd\u03b1 \u03b4\u03b9\u03b1\u03ba\u03c1\u03af\u03bd\u03b5\u03b9 \u03c4\u03bf \u00ab\u03bc\u03b9\u03bb\u03ac \u03b3\u03b9\u03b1 \u03c4\u03bf \u03af\u03b4\u03b9\u03bf \u03b8\u03ad\u03bc\u03b1\u00bb \u03b1\u03c0\u03cc \u03c4\u03bf \u00ab\u03c0\u03b5\u03c1\u03b9\u03ad\u03c7\u03b5\u03b9 \u03c4\u03b7 \u03b4\u03b9\u03b1\u03b4\u03b9\u03ba\u03b1\u03c3\u03af\u03b1 \u03c0\u03bf\u03c5 \u03b6\u03b7\u03c4\u03ae\u03b8\u03b7\u03ba\u03b5\u00bb. \u03a4\u03b5\u03c7\u03bd\u03b9\u03ba\u03ad\u03c2 \u03c3\u03c5\u03bc\u03c0\u03af\u03b5\u03c3\u03b7\u03c2, \u03cc\u03c0\u03c9\u03c2 \u03c4\u03b1 <a href=\"https:\/\/twodots.gr\/semantic-compression-trees-rag-context\/\">Semantic Compression Trees \u03b3\u03b9\u03b1 \u03bb\u03b9\u03b3\u03cc\u03c4\u03b5\u03c1\u03bf RAG context<\/a>, \u03bb\u03cd\u03bd\u03bf\u03c5\u03bd \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03cc \u03bc\u03ad\u03c1\u03bf\u03c2 \u03c4\u03bf\u03c5 \u03c0\u03c1\u03bf\u03b2\u03bb\u03ae\u03bc\u03b1\u03c4\u03bf\u03c2 \u03ba\u03b1\u03b9 \u03b4\u03b5\u03bd \u03c5\u03c0\u03bf\u03ba\u03b1\u03b8\u03b9\u03c3\u03c4\u03bf\u03cd\u03bd \u03c4\u03b7\u03bd \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ae \u03c3\u03c9\u03c3\u03c4\u03bf\u03cd evidence.<\/p>\n<h2 id=\"diagnostic-keyword-stuffing\">\u03a4\u03bf diagnostic test \u03b3\u03b9\u03b1 keyword stuffing<\/h2>\n<p>\u0393\u03b9\u03b1 \u03b3\u03bd\u03c9\u03c3\u03c4\u03cc ground truth, \u03bf\u03b9 \u03b5\u03c1\u03b5\u03c5\u03bd\u03b7\u03c4\u03ad\u03c2 \u03ba\u03b1\u03c4\u03b1\u03c3\u03ba\u03b5\u03cd\u03b1\u03c3\u03b1\u03bd \u03bc\u03b9\u03ba\u03c1\u03cc \u03c3\u03c5\u03bd\u03b8\u03b5\u03c4\u03b9\u03ba\u03cc corpus \u03bf\u03ba\u03c4\u03ce \u03b8\u03b5\u03bc\u03ac\u03c4\u03c9\u03bd, \u03c0\u03ad\u03bd\u03c4\u03b5 \u03c3\u03c4\u03b1 \u03ba\u03b9\u03bd\u03b5\u03b6\u03b9\u03ba\u03ac \u03ba\u03b1\u03b9 \u03c4\u03c1\u03af\u03b1 \u03c3\u03c4\u03b1 \u03b1\u03b3\u03b3\u03bb\u03b9\u03ba\u03ac. \u039a\u03ac\u03b8\u03b5 \u03b8\u03ad\u03bc\u03b1 \u03b5\u03af\u03c7\u03b5 \u03ad\u03bd\u03b1 answer-bearing target, near-relevant \u03ba\u03b5\u03af\u03bc\u03b5\u03bd\u03b1, \u03b4\u03cd\u03bf \u03c3\u03ba\u03cc\u03c0\u03b9\u03bc\u03b1 keyword-stuffed distractors \u03ba\u03b1\u03b9 \u03ac\u03c3\u03c7\u03b5\u03c4\u03b1 \u03ad\u03b3\u03b3\u03c1\u03b1\u03c6\u03b1. \u03a4\u03b1 \u03b8\u03ad\u03bc\u03b1\u03c4\u03b1 \u03ba\u03ac\u03bb\u03c5\u03c0\u03c4\u03b1\u03bd data-transfer security, \u03b8\u03b5\u03c1\u03b1\u03c0\u03b5\u03af\u03b5\u03c2 \u03c0\u03b1\u03c1\u03b1\u03b4\u03bf\u03c3\u03b9\u03b1\u03ba\u03ae\u03c2 \u03ba\u03b9\u03bd\u03b5\u03b6\u03b9\u03ba\u03ae\u03c2 \u03b9\u03b1\u03c4\u03c1\u03b9\u03ba\u03ae\u03c2, Wason selection task, \u03ba\u03b1\u03b8\u03b1\u03c1\u03b9\u03c3\u03bc\u03cc LLM pretraining data, privacy impact assessment, ColBERT \u03ba\u03b1\u03b9 SPLADE.<\/p>\n<p>\u039f BGE-reranker-v2-m3 cross-encoder \u03b2\u03b5\u03bb\u03c4\u03af\u03c9\u03c3\u03b5 \u03c4\u03b7 \u03bc\u03ad\u03c3\u03b7 \u03b8\u03ad\u03c3\u03b7 \u03c4\u03bf\u03c5 target \u03bc\u03cc\u03bd\u03bf \u03b1\u03c0\u03cc 2,88 \u03c3\u03b5 2,63 \u03ba\u03b1\u03b9 \u03ac\u03c6\u03b7\u03c3\u03b5 \u03c4\u03bf\u03c5\u03c2 distractors \u03ba\u03bf\u03bd\u03c4\u03ac \u03c3\u03c4\u03b7\u03bd \u03ba\u03bf\u03c1\u03c5\u03c6\u03ae. \u0397 semantic causal \u03c0\u03b1\u03c1\u03b1\u03bb\u03bb\u03b1\u03b3\u03ae \u03ad\u03c6\u03c4\u03b1\u03c3\u03b5 1,25. \u03a4\u03bf \u03b1\u03c0\u03bf\u03c4\u03ad\u03bb\u03b5\u03c3\u03bc\u03b1 \u03b4\u03b5\u03af\u03c7\u03bd\u03b5\u03b9 \u03cc\u03c4\u03b9 \u03b7 \u03c4\u03b5\u03c7\u03bd\u03b9\u03ba\u03ae \u03b5\u03c0\u03b9\u03bb\u03cd\u03b5\u03b9 \u03c4\u03bf\u03bd failure mode \u03b3\u03b9\u03b1 \u03c4\u03bf\u03bd \u03bf\u03c0\u03bf\u03af\u03bf \u03c3\u03c7\u03b5\u03b4\u03b9\u03ac\u03c3\u03c4\u03b7\u03ba\u03b5, \u03cc\u03c7\u03b9 \u03cc\u03c4\u03b9 \u03c5\u03c0\u03b5\u03c1\u03ad\u03c7\u03b5\u03b9 \u03c3\u03b5 \u03ba\u03ac\u03b8\u03b5 retrieval workload.<\/p>\n<div class=\"td-chart td-chart--metrics\">\n<div class=\"td-chart-head\">\n<p class=\"td-chart-kicker\">\u03a4\u03b5\u03ba\u03bc\u03b7\u03c1\u03b9\u03c9\u03bc\u03ad\u03bd\u03b7 \u03b5\u03b9\u03ba\u03cc\u03bd\u03b1<\/p>\n<p class=\"td-chart-title\">\u03a4\u03ad\u03c3\u03c3\u03b5\u03c1\u03b9\u03c2 \u03b1\u03c1\u03b9\u03b8\u03bc\u03bf\u03af \u03c0\u03bf\u03c5 \u03bf\u03c1\u03af\u03b6\u03bf\u03c5\u03bd \u03c4\u03bf \u03b5\u03cd\u03c1\u03bf\u03c2 \u03c4\u03b7\u03c2 \u03bc\u03b5\u03b8\u03cc\u03b4\u03bf\u03c5<\/p>\n<p class=\"td-chart-intro\">\u039f\u03b9 \u03c4\u03b9\u03bc\u03ad\u03c2 \u03c0\u03c1\u03bf\u03ad\u03c1\u03c7\u03bf\u03bd\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03ac \u03c0\u03b5\u03b9\u03c1\u03ac\u03bc\u03b1\u03c4\u03b1 \u03c4\u03b7\u03c2 \u03af\u03b4\u03b9\u03b1\u03c2 \u03bc\u03b5\u03bb\u03ad\u03c4\u03b7\u03c2 \u03ba\u03b1\u03b9 \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03b4\u03b9\u03b1\u03b2\u03ac\u03b6\u03bf\u03bd\u03c4\u03b1\u03b9 \u03bc\u03b1\u03b6\u03af \u03bc\u03b5 \u03c4\u03bf \u03b1\u03bd\u03c4\u03af\u03c3\u03c4\u03bf\u03b9\u03c7\u03bf corpus.<\/p>\n<\/div>\n<div class=\"td-metric-grid\">\n<div class=\"td-metric-card\"><span class=\"td-metric-value\">471<\/span><span class=\"td-metric-label\">\u03ad\u03b3\u03b3\u03c1\u03b1\u03c6\u03b1 \u03c3\u03c4\u03bf enterprise case study<\/span><\/div>\n<div class=\"td-metric-card\"><span class=\"td-metric-value\">2,88 \u2192 1,25<\/span><span class=\"td-metric-label\">mean target rank \u03c3\u03c4\u03bf diagnostic corpus<\/span><\/div>\n<div class=\"td-metric-card\"><span class=\"td-metric-value\">2,00 \u2192 4,50<\/span><span class=\"td-metric-label\">mean distractor rank, \u03c7\u03b1\u03bc\u03b7\u03bb\u03cc\u03c4\u03b5\u03c1\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03ba\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03b1 \u03b3\u03b9\u03b1 \u03c4\u03bf target<\/span><\/div>\n<div class=\"td-metric-card\"><span class=\"td-metric-value\">30<\/span><span class=\"td-metric-label\">probes \u03b3\u03b9\u03b1 \u226595% \u03c3\u03c9\u03c3\u03c4\u03ae \u03b1\u03c0\u03b5\u03bd\u03b5\u03c1\u03b3\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7 \u03c3\u03c4\u03b1 BEIR tests<\/span><\/div>\n<\/div>\n<p class=\"td-chart-source\">\u03a0\u03b7\u03b3\u03ae: arXiv 2608.21702 v1, \u03c0\u03af\u03bd\u03b1\u03ba\u03b5\u03c2 2\u20134.<\/p>\n<\/div>\n<h2 id=\"beir-arnitika-apotelesmata\">\u03a4\u03b1 \u03b1\u03c1\u03bd\u03b7\u03c4\u03b9\u03ba\u03ac \u03b1\u03c0\u03bf\u03c4\u03b5\u03bb\u03ad\u03c3\u03bc\u03b1\u03c4\u03b1 \u03c3\u03c4\u03b1 BEIR benchmarks \u03b1\u03bb\u03bb\u03ac\u03b6\u03bf\u03c5\u03bd \u03c4\u03bf \u03c3\u03c5\u03bc\u03c0\u03ad\u03c1\u03b1\u03c3\u03bc\u03b1<\/h2>\n<p>\u03a3\u03c4\u03b1 SciFact, NFCorpus \u03ba\u03b1\u03b9 ArguAna \u03c4\u03bf\u03c5 BEIR, \u03c4\u03bf causal score \u03c5\u03c0\u03bf\u03b1\u03c0\u03ad\u03b4\u03c9\u03c3\u03b5 \u03ba\u03b1\u03b8\u03b1\u03c1\u03ac. \u03a3\u03c4\u03bf SciFact, \u03c4\u03bf baseline \u03b5\u03af\u03c7\u03b5 nDCG@10 0,642, \u03bf cross-encoder 0,716 \u03ba\u03b1\u03b9 \u03c4\u03bf causal score 0,157. \u03a3\u03c4\u03bf NFCorpus \u03bf\u03b9 \u03b1\u03bd\u03c4\u03af\u03c3\u03c4\u03bf\u03b9\u03c7\u03b5\u03c2 \u03c4\u03b9\u03bc\u03ad\u03c2 \u03ae\u03c4\u03b1\u03bd 0,317, 0,337 \u03ba\u03b1\u03b9 0,136. \u03a3\u03c4\u03bf ArguAna \u03ae\u03c4\u03b1\u03bd 0,398, 0,470 \u03ba\u03b1\u03b9 0,213.<\/p>\n<p>\u0397 \u03b5\u03be\u03ae\u03b3\u03b7\u03c3\u03b7 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b5\u03cd\u03bb\u03bf\u03b3\u03b7: \u03c3\u03b5 factoid-style corpora, \u03c4\u03bf \u03c3\u03c9\u03c3\u03c4\u03cc \u03ad\u03b3\u03b3\u03c1\u03b1\u03c6\u03bf \u03c3\u03c5\u03c7\u03bd\u03ac \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03b5\u03af \u03b1\u03ba\u03c1\u03b9\u03b2\u03ce\u03c2 \u03c4\u03bf content vocabulary \u03c4\u03b7\u03c2 \u03b5\u03c1\u03ce\u03c4\u03b7\u03c3\u03b7\u03c2. \u0391\u03bd \u03b1\u03c5\u03c4\u03cc \u03c4\u03bf \u03bb\u03b5\u03be\u03b9\u03bb\u03cc\u03b3\u03b9\u03bf \u03b1\u03c0\u03bf\u03c1\u03c1\u03bf\u03c6\u03b7\u03b8\u03b5\u03af \u03c3\u03c4\u03bf A, \u03c4\u03bf B \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03bc\u03b5\u03af\u03bd\u03b5\u03b9 \u03bc\u03b5 \u03cc\u03c1\u03bf\u03c5\u03c2 \u03b4\u03b9\u03b1\u03ba\u03c1\u03b9\u03c4\u03bf\u03cd\u03c2 \u03b1\u03bb\u03bb\u03ac \u03cc\u03c7\u03b9 answer-bearing. \u03a4\u03bf score \u03c4\u03cc\u03c4\u03b5 \u03b1\u03bd\u03c4\u03b1\u03bc\u03b5\u03af\u03b2\u03b5\u03b9 \u03ba\u03b5\u03af\u03bc\u03b5\u03bd\u03b1 \u03c0\u03bf\u03c5 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b8\u03b5\u03bc\u03b1\u03c4\u03b9\u03ba\u03ac \u03b3\u03b5\u03b9\u03c4\u03bf\u03bd\u03b9\u03ba\u03ac \u03c7\u03c9\u03c1\u03af\u03c2 \u03bd\u03b1 \u03b1\u03c0\u03bf\u03c4\u03b5\u03bb\u03bf\u03cd\u03bd \u03c4\u03b7\u03bd \u03ba\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03b7 \u03b1\u03c0\u03cc\u03b4\u03b5\u03b9\u03be\u03b7.<\/p>\n<p>\u039f cross-encoder \u03ba\u03b1\u03b9 \u03c4\u03bf causal score \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03b1\u03c0\u03bb\u03bf\u03af \u03b1\u03bd\u03c4\u03b1\u03b3\u03c9\u03bd\u03b9\u03c3\u03c4\u03ad\u03c2. \u039f \u03c0\u03c1\u03ce\u03c4\u03bf\u03c2 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b9\u03c3\u03c7\u03c5\u03c1\u03cc\u03c2 \u03cc\u03c4\u03b1\u03bd \u03b7 soft semantic relevance \u03b5\u03af\u03bd\u03b1\u03b9 \u03b1\u03be\u03b9\u03cc\u03c0\u03b9\u03c3\u03c4\u03bf \u03c3\u03ae\u03bc\u03b1. \u03a4\u03bf \u03b4\u03b5\u03cd\u03c4\u03b5\u03c1\u03bf \u03c3\u03c4\u03bf\u03c7\u03b5\u03cd\u03b5\u03b9 \u03c0\u03b5\u03c1\u03b9\u03b2\u03ac\u03bb\u03bb\u03bf\u03bd\u03c4\u03b1 \u03cc\u03c0\u03bf\u03c5 \u03b1\u03c5\u03c4\u03cc \u03c4\u03bf \u03c3\u03ae\u03bc\u03b1 \u03bc\u03bf\u03bb\u03cd\u03bd\u03b5\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc repetition \u03ba\u03b1\u03b9 topic-near distractors. \u0397 \u03c3\u03c9\u03c3\u03c4\u03ae \u03b5\u03c1\u03ce\u03c4\u03b7\u03c3\u03b7 \u03b5\u03af\u03bd\u03b1\u03b9 \u00ab\u03c3\u03b5 \u03c0\u03bf\u03b9\u03bf corpus regime \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03b5\u03af \u03bf \u03ba\u03b1\u03b8\u03ad\u03bd\u03b1\u03c2;\u00bb, \u03cc\u03c7\u03b9 \u00ab\u03c0\u03bf\u03b9\u03bf\u03c2 reranker \u03ba\u03b5\u03c1\u03b4\u03af\u03b6\u03b5\u03b9 \u03b3\u03b5\u03bd\u03b9\u03ba\u03ac;\u00bb.<\/p>\n<aside class=\"td-article-note\"><strong>\u0397 \u03b1\u03c1\u03bd\u03b7\u03c4\u03b9\u03ba\u03ae \u03b1\u03c0\u03cc\u03b4\u03b5\u03b9\u03be\u03b7 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b2\u03b1\u03c3\u03b9\u03ba\u03cc \u03b5\u03cd\u03c1\u03b7\u03bc\u03b1:<\/strong> \u03c4\u03bf causal score \u03b4\u03b5\u03bd \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03b5\u03bd\u03b5\u03c1\u03b3\u03bf\u03c0\u03bf\u03b9\u03b5\u03af\u03c4\u03b1\u03b9 \u03b5\u03c0\u03b5\u03b9\u03b4\u03ae \u03b1\u03ba\u03bf\u03cd\u03b3\u03b5\u03c4\u03b1\u03b9 \u03c0\u03b9\u03bf \u03b5\u03be\u03b5\u03bb\u03b9\u03b3\u03bc\u03ad\u03bd\u03bf. \u03a3\u03c4\u03b1 \u03c4\u03c1\u03af\u03b1 \u03b4\u03b7\u03bc\u03cc\u03c3\u03b9\u03b1 benchmarks \u03ad\u03c7\u03b1\u03c3\u03b5 \u03b1\u03c0\u03cc \u03c4\u03bf similarity baseline, \u03b5\u03bd\u03ce \u03bf cross-encoder \u03ae\u03c4\u03b1\u03bd \u03bf \u03ba\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03bf\u03c2 \u03ba\u03b1\u03b9 \u03c3\u03c4\u03b1 \u03c4\u03c1\u03af\u03b1.<\/aside>\n<h2 id=\"calibration-gate\">\u03a4\u03bf calibration gate \u03c0\u03c1\u03b9\u03bd \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae<\/h2>\n<p>\u039f\u03b9 \u03c3\u03c5\u03b3\u03b3\u03c1\u03b1\u03c6\u03b5\u03af\u03c2 \u03b4\u03bf\u03ba\u03af\u03bc\u03b1\u03c3\u03b1\u03bd \u03c4\u03c1\u03b5\u03b9\u03c2 \u03c6\u03b8\u03b7\u03bd\u03bf\u03cd\u03c2 per-query \u03b4\u03b5\u03af\u03ba\u03c4\u03b5\u03c2 \u03c0\u03ac\u03bd\u03c9 \u03c3\u03c4\u03b1 top-10 candidates: keyword overlap, \u03c0\u03bf\u03c3\u03bf\u03c3\u03c4\u03cc \u03b2\u03ac\u03c1\u03bf\u03c5\u03c2 \u03c0\u03bf\u03c5 \u03b1\u03c0\u03bf\u03c1\u03c1\u03bf\u03c6\u03ac\u03c4\u03b1\u03b9 \u03c3\u03c4\u03bf A \u03ba\u03b1\u03b9 normalized gap \u03b1\u03bd\u03ac\u03bc\u03b5\u03c3\u03b1 \u03c3\u03c4\u03b1 \u03b4\u03cd\u03bf \u03c5\u03c8\u03b7\u03bb\u03cc\u03c4\u03b5\u03c1\u03b1 similarity scores. \u039a\u03b1\u03bd\u03ad\u03bd\u03b1\u03c2 \u03b4\u03b5\u03bd \u03be\u03b5\u03c7\u03ce\u03c1\u03b9\u03c3\u03b5 \u03b1\u03be\u03b9\u03cc\u03c0\u03b9\u03c3\u03c4\u03b1 \u03c4\u03bf keyword-stuffing \u03b1\u03c0\u03cc \u03c4\u03bf factoid regime. \u0397 \u03c3\u03c7\u03ad\u03c3\u03b7 \u03b1\u03bd\u03ac\u03bc\u03b5\u03c3\u03b1 \u03c3\u03c4\u03bf keyword-driven ranking \u03ba\u03b1\u03b9 \u03c4\u03b7\u03bd \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ae relevance \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03bf\u03c1\u03b1\u03c4\u03ae \u03c7\u03c9\u03c1\u03af\u03c2 labels.<\/p>\n<p>\u0397 \u03c0\u03c1\u03b1\u03ba\u03c4\u03b9\u03ba\u03ae \u03c0\u03c1\u03cc\u03c4\u03b1\u03c3\u03b7 \u03b5\u03af\u03bd\u03b1\u03b9 corpus-level offline calibration. \u0397 \u03bf\u03bc\u03ac\u03b4\u03b1 \u03b4\u03b5\u03b9\u03b3\u03bc\u03b1\u03c4\u03bf\u03bb\u03b7\u03c0\u03c4\u03b5\u03af queries, \u03c3\u03b7\u03bc\u03b5\u03b9\u03ce\u03bd\u03b5\u03b9 \u03c4\u03bf \u03c3\u03c9\u03c3\u03c4\u03cc evidence \u03bc\u03b5 \u03b1\u03bd\u03b8\u03c1\u03ce\u03c0\u03b9\u03bd\u03b7 \u03ae \u03b5\u03bb\u03b5\u03b3\u03c7\u03cc\u03bc\u03b5\u03bd\u03b7 LLM \u03ba\u03c1\u03af\u03c3\u03b7, \u03c3\u03c5\u03b3\u03ba\u03c1\u03af\u03bd\u03b5\u03b9 baseline \u03ba\u03b1\u03b9 \u03bd\u03ad\u03bf ranking \u03ba\u03b1\u03b9 \u03b5\u03bd\u03b5\u03c1\u03b3\u03bf\u03c0\u03bf\u03b9\u03b5\u03af \u03c4\u03bf reranker \u03bc\u03cc\u03bd\u03bf \u03b1\u03bd \u03b7 \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03ac \u03b5\u03af\u03bd\u03b1\u03b9 \u03b8\u03b5\u03c4\u03b9\u03ba\u03ae. \u039c\u03b5 2.000 bootstrap draws, 30 probes \u03ad\u03b4\u03c9\u03c3\u03b1\u03bd \u03c4\u03bf\u03c5\u03bb\u03ac\u03c7\u03b9\u03c3\u03c4\u03bf\u03bd 95% \u03b1\u03be\u03b9\u03bf\u03c0\u03b9\u03c3\u03c4\u03af\u03b1 \u03b3\u03b9\u03b1 \u03c4\u03b7 \u03c3\u03c9\u03c3\u03c4\u03ae \u03b1\u03c0\u03cc\u03c6\u03b1\u03c3\u03b7 \u03b1\u03c0\u03b5\u03bd\u03b5\u03c1\u03b3\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7\u03c2 \u03c3\u03c4\u03b1 \u03c4\u03c1\u03af\u03b1 BEIR datasets. \u03a3\u03c4\u03bf \u03bc\u03b9\u03ba\u03c1\u03cc diagnostic corpus, \u03c4\u03ad\u03c3\u03c3\u03b5\u03c1\u03b1 probes \u03ad\u03b4\u03c9\u03c3\u03b1\u03bd 100% \u03b1\u03be\u03b9\u03bf\u03c0\u03b9\u03c3\u03c4\u03af\u03b1 \u03b5\u03bd\u03b5\u03c1\u03b3\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7\u03c2.<\/p>\n<p>\u039f\u03b9 \u03b1\u03c1\u03b9\u03b8\u03bc\u03bf\u03af \u03b1\u03c6\u03bf\u03c1\u03bf\u03cd\u03bd \u03b1\u03c5\u03c4\u03ac \u03c4\u03b1 \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03b1. \u0394\u03b5\u03bd \u03b5\u03b3\u03b3\u03c5\u03ce\u03bd\u03c4\u03b1\u03b9 \u03cc\u03c4\u03b9 30 probes \u03b1\u03c1\u03ba\u03bf\u03cd\u03bd \u03c3\u03b5 \u03ba\u03ac\u03b8\u03b5 \u03bf\u03c1\u03b3\u03b1\u03bd\u03b9\u03c3\u03bc\u03cc. \u03a4\u03bf sample \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03b5\u03ba\u03c0\u03c1\u03bf\u03c3\u03c9\u03c0\u03b5\u03af \u03c4\u03bf corpus \u03ba\u03b1\u03b9 \u03c4\u03b1 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ac intents, \u03b5\u03bd\u03ce \u03bc\u03b9\u03b1 \u03b2\u03ac\u03c3\u03b7 \u03b3\u03bd\u03ce\u03c3\u03b7\u03c2 \u03c0\u03bf\u03c5 \u03b1\u03bb\u03bb\u03ac\u03b6\u03b5\u03b9 \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03c0\u03b5\u03c1\u03b9\u03bf\u03b4\u03b9\u03ba\u03cc recalibration. \u0397 \u03b1\u03c1\u03c7\u03b9\u03c4\u03b5\u03ba\u03c4\u03bf\u03bd\u03b9\u03ba\u03ae \u03b1\u03be\u03af\u03b1 \u03b2\u03c1\u03af\u03c3\u03ba\u03b5\u03c4\u03b1\u03b9 \u03c3\u03c4\u03bf release gate \u03ba\u03b1\u03b9 \u03c3\u03c4\u03bf fallback, \u03cc\u03c7\u03b9 \u03c3\u03b5 \u03ad\u03bd\u03b1 one-off benchmark.<\/p>\n<div class=\"td-decision-band\">\n<p class=\"td-decision-kicker\">\u039a\u03b1\u03bd\u03cc\u03bd\u03b1\u03c2 \u03b5\u03bd\u03b5\u03c1\u03b3\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7\u03c2<\/p>\n<p class=\"td-decision-title\">\u03a7\u03c9\u03c1\u03af\u03c2 labeled probes, \u03ba\u03c1\u03b1\u03c4\u03ae\u03c3\u03c4\u03b5 \u03c4\u03bf baseline<\/p>\n<p>\u03a4\u03bf causal RAG reranking \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03c0\u03b5\u03c1\u03ac\u03c3\u03b5\u03b9 offline \u03c3\u03cd\u03b3\u03ba\u03c1\u03b9\u03c3\u03b7 \u03c3\u03c4\u03bf \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03cc corpus, \u03b1\u03bd\u03ac \u03c3\u03c5\u03bb\u03bb\u03bf\u03b3\u03ae \u03ae use case. \u0391\u03bd \u03c4\u03bf confidence interval \u03b4\u03b5\u03bd \u03b4\u03b5\u03af\u03c7\u03bd\u03b5\u03b9 \u03ba\u03b1\u03b8\u03b1\u03c1\u03cc \u03cc\u03c6\u03b5\u03bb\u03bf\u03c2, \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03c4\u03b5 similarity \u03ae hybrid fallback \u03ba\u03b1\u03b9 \u03c3\u03c5\u03bd\u03b5\u03c7\u03af\u03c3\u03c4\u03b5 \u03c4\u03b7 \u03bc\u03ad\u03c4\u03c1\u03b7\u03c3\u03b7.<\/p>\n<\/div>\n<h2 id=\"kostos-idiotikotita-exartiseis\">\u039a\u03cc\u03c3\u03c4\u03bf\u03c2, \u03b9\u03b4\u03b9\u03c9\u03c4\u03b9\u03ba\u03cc\u03c4\u03b7\u03c4\u03b1 \u03ba\u03b1\u03b9 \u03c4\u03b5\u03c7\u03bd\u03b9\u03ba\u03ad\u03c2 \u03b5\u03be\u03b1\u03c1\u03c4\u03ae\u03c3\u03b5\u03b9\u03c2<\/h2>\n<p>\u0397 reference \u03c5\u03bb\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7 \u03be\u03b1\u03bd\u03b1\u03c7\u03c4\u03af\u03c3\u03c4\u03b7\u03ba\u03b5 \u03c4\u03bf\u03c0\u03b9\u03ba\u03ac \u03bc\u03b5 Qwen3-4B \u03c9\u03c2 generator \u03ba\u03b1\u03b9 translation module \u03ba\u03b1\u03b9 BGE-M3 \u03b3\u03b9\u03b1 embeddings. \u03a0\u03b5\u03c1\u03b9\u03bb\u03b1\u03bc\u03b2\u03ac\u03bd\u03b5\u03b9 parsing Word\/PDF, cleaning, chunking, thresholded retrieval, \u03bc\u03b5\u03c4\u03ac\u03c6\u03c1\u03b1\u03c3\u03b7 chunks \u03ba\u03b1\u03b9 prompt generation. \u039f \u03ba\u03ce\u03b4\u03b9\u03ba\u03b1\u03c2 \u03c4\u03bf\u03c5 testbed \u03ba\u03b1\u03b9 \u03c4\u03c9\u03bd \u03c0\u03b5\u03b9\u03c1\u03b1\u03bc\u03ac\u03c4\u03c9\u03bd \u03b4\u03b9\u03b1\u03c4\u03af\u03b8\u03b5\u03c4\u03b1\u03b9 \u03b4\u03b7\u03bc\u03cc\u03c3\u03b9\u03b1 \u03b1\u03c0\u03cc \u03c4\u03bf\u03c5\u03c2 \u03c3\u03c5\u03b3\u03b3\u03c1\u03b1\u03c6\u03b5\u03af\u03c2.<\/p>\n<p>\u0397 \u03c4\u03bf\u03c0\u03b9\u03ba\u03ae \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03af\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c7\u03c1\u03ae\u03c3\u03b9\u03bc\u03b7 \u03b3\u03b9\u03b1 \u03bf\u03c1\u03b3\u03b1\u03bd\u03b9\u03c3\u03bc\u03bf\u03cd\u03c2 \u03c0\u03bf\u03c5 \u03b4\u03b5\u03bd \u03bc\u03c0\u03bf\u03c1\u03bf\u03cd\u03bd \u03bd\u03b1 \u03c3\u03c4\u03b5\u03af\u03bb\u03bf\u03c5\u03bd \u03bd\u03bf\u03bc\u03b9\u03ba\u03ac, \u03ba\u03b1\u03bd\u03bf\u03bd\u03b9\u03c3\u03c4\u03b9\u03ba\u03ac \u03ae \u03b5\u03c3\u03c9\u03c4\u03b5\u03c1\u03b9\u03ba\u03ac \u03ad\u03b3\u03b3\u03c1\u03b1\u03c6\u03b1 \u03c3\u03b5 \u03b5\u03be\u03c9\u03c4\u03b5\u03c1\u03b9\u03ba\u03ad\u03c2 \u03c5\u03c0\u03b7\u03c1\u03b5\u03c3\u03af\u03b5\u03c2. \u0394\u03b5\u03bd \u03c3\u03b7\u03bc\u03b1\u03af\u03bd\u03b5\u03b9 plug-and-play. \u0397 \u03c0\u03bf\u03b9\u03cc\u03c4\u03b7\u03c4\u03b1 \u03b5\u03be\u03b1\u03c1\u03c4\u03ac\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc keyword extractor, \u03b2\u03ac\u03c1\u03b7, absorption threshold, embedding model, chunking, candidate window \u03ba\u03b1\u03b9 \u03c4\u03c1\u03cc\u03c0\u03bf \u03c3\u03c5\u03bd\u03b4\u03c5\u03b1\u03c3\u03bc\u03bf\u03cd \u03c4\u03c9\u03bd scores. \u0397 \u03b5\u03c1\u03b3\u03b1\u03c3\u03af\u03b1 \u03b1\u03bd\u03b1\u03b3\u03bd\u03c9\u03c1\u03af\u03b6\u03b5\u03b9 \u03cc\u03c4\u03b9 \u03b1\u03c0\u03b1\u03b9\u03c4\u03b5\u03af\u03c4\u03b1\u03b9 \u03c0\u03bb\u03b7\u03c1\u03ad\u03c3\u03c4\u03b5\u03c1\u03bf ablation \u03b1\u03c5\u03c4\u03ce\u03bd \u03c4\u03c9\u03bd \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ce\u03bd.<\/p>\n<p>\u03a4\u03bf retrieval pipeline \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03b5\u03c0\u03af\u03c3\u03b7\u03c2 \u03b9\u03c7\u03bd\u03b7\u03bb\u03b1\u03c3\u03b9\u03bc\u03cc\u03c4\u03b7\u03c4\u03b1. \u0397 \u03bb\u03bf\u03b3\u03b9\u03ba\u03ae \u03c4\u03bf\u03c5 <a href=\"https:\/\/twodots.gr\/schemarouter-ai-agents-field-aware-rag\/\">field-aware RAG \u03ba\u03b1\u03b9 \u03c4\u03bf\u03c5 \u03b5\u03bb\u03b5\u03b3\u03c7\u03cc\u03bc\u03b5\u03bd\u03bf\u03c5 schema routing<\/a> \u03b4\u03b5\u03af\u03c7\u03bd\u03b5\u03b9 \u03b3\u03b9\u03b1\u03c4\u03af \u03c4\u03b1 permissions \u03ba\u03b1\u03b9 \u03c4\u03bf scope \u03c4\u03b7\u03c2 \u03b1\u03bd\u03ac\u03ba\u03c4\u03b7\u03c3\u03b7\u03c2 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b5\u03be\u03af\u03c3\u03bf\u03c5 \u03c3\u03b7\u03bc\u03b1\u03bd\u03c4\u03b9\u03ba\u03ac \u03bc\u03b5 \u03c4\u03bf ranking. \u0391\u03bd \u03bf agent \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b1\u03bd\u03b1\u03b6\u03b7\u03c4\u03ae\u03c3\u03b5\u03b9 \u03bb\u03ac\u03b8\u03bf\u03c2 \u03c3\u03c5\u03bb\u03bb\u03bf\u03b3\u03ae \u03ae \u03bd\u03b1 \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03b5\u03b9 \u03bc\u03b7 \u03b5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03bf \u03ad\u03b3\u03b3\u03c1\u03b1\u03c6\u03bf, \u03ba\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03bf reranking \u03b4\u03b5\u03bd \u03b4\u03b9\u03bf\u03c1\u03b8\u03ce\u03bd\u03b5\u03b9 \u03c4\u03bf governance gap.<\/p>\n<h2 id=\"epicheirimatiki-axia\">\u03a4\u03b9 \u03c3\u03b7\u03bc\u03b1\u03af\u03bd\u03b5\u03b9 \u03b3\u03b9\u03b1 \u03ad\u03bd\u03b1 \u03b5\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03b7\u03c3\u03b9\u03b1\u03ba\u03cc RAG<\/h2>\n<p>\u0393\u03b9\u03b1 customer support, e-commerce operations, compliance \u03ba\u03b1\u03b9 internal search, \u03b7 \u03bf\u03bc\u03ac\u03b4\u03b1 \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03bc\u03b5\u03c4\u03c1\u03ac \u03b1\u03bd \u03c4\u03bf \u03c3\u03c9\u03c3\u03c4\u03cc chunk \u03c6\u03c4\u03ac\u03bd\u03b5\u03b9 \u03c3\u03c4\u03bf prompt. Answer quality \u03c7\u03c9\u03c1\u03af\u03c2 retrieval trace \u03ba\u03c1\u03cd\u03b2\u03b5\u03b9 \u03c4\u03bf failure: \u03bc\u03b9\u03b1 \u03ba\u03b1\u03bb\u03ae \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03c0\u03c1\u03bf\u03ad\u03c1\u03c7\u03b5\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc prior knowledge \u03c4\u03bf\u03c5 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf\u03c5, \u03b5\u03bd\u03ce \u03bc\u03b9\u03b1 \u03bb\u03b1\u03bd\u03b8\u03b1\u03c3\u03bc\u03ad\u03bd\u03b7 \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03bf\u03c6\u03b5\u03af\u03bb\u03b5\u03c4\u03b1\u03b9 \u03c3\u03b5 \u03bb\u03ac\u03b8\u03bf\u03c2 evidence \u03ba\u03b1\u03b9 \u03cc\u03c7\u03b9 \u03c3\u03c4\u03bf\u03bd generator.<\/p>\n<p>\u0397 observability \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03ba\u03b1\u03c4\u03b1\u03b3\u03c1\u03ac\u03c6\u03b5\u03b9 query, \u03b1\u03c1\u03c7\u03b9\u03ba\u03cc rank, \u03bd\u03ad\u03bf rank, \u03bc\u03ad\u03b3\u03b5\u03b8\u03bf\u03c2 A\/B, source IDs, evidence \u03c0\u03bf\u03c5 \u03bc\u03c0\u03ae\u03ba\u03b5 \u03c3\u03c4\u03bf prompt \u03ba\u03b1\u03b9 outcome \u03b1\u03c0\u03cc reviewer \u03ae downstream task. \u0397 \u03af\u03b4\u03b9\u03b1 \u03b1\u03c1\u03c7\u03ae provenance \u03c0\u03bf\u03c5 \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03b7 <a href=\"https:\/\/twodots.gr\/echo-mnimi-ai-agent-apodeixeis-provenance\/\">\u03bc\u03bd\u03ae\u03bc\u03b7 \u03b5\u03bd\u03cc\u03c2 AI agent \u03bc\u03b5 \u03b1\u03c0\u03bf\u03b4\u03b5\u03af\u03be\u03b5\u03b9\u03c2<\/a> \u03b9\u03c3\u03c7\u03cd\u03b5\u03b9 \u03ba\u03b1\u03b9 \u03b5\u03b4\u03ce: \u03c7\u03c9\u03c1\u03af\u03c2 \u03c3\u03cd\u03bd\u03b4\u03b5\u03c3\u03b7 \u03b1\u03bd\u03ac\u03bc\u03b5\u03c3\u03b1 \u03c3\u03b5 claim \u03ba\u03b1\u03b9 \u03c0\u03b7\u03b3\u03ae, \u03b7 \u03bf\u03bc\u03ac\u03b4\u03b1 \u03b4\u03b5\u03bd \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03be\u03b5\u03c7\u03c9\u03c1\u03af\u03c3\u03b5\u03b9 \u03b2\u03b5\u03bb\u03c4\u03af\u03c9\u03c3\u03b7 \u03b1\u03c0\u03cc \u03c4\u03c5\u03c7\u03b1\u03af\u03b1 \u03b5\u03c0\u03b9\u03c4\u03c5\u03c7\u03af\u03b1.<\/p>\n<p>\u03a4\u03bf operating model \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 owner, cadence \u03b5\u03c0\u03b1\u03bd\u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7\u03c2 \u03ba\u03b1\u03b9 stop condition. \u039f\u03b9 \u03c0\u03c1\u03b1\u03ba\u03c4\u03b9\u03ba\u03ad\u03c2 \u03c4\u03c9\u03bd <a href=\"https:\/\/twodots.gr\/enterprise-ai-harnesses-diakyvernisi-architektoniki\/\">enterprise AI harnesses<\/a> \u03ba\u03b1\u03b9 \u03c4\u03c9\u03bd <a href=\"https:\/\/twodots.gr\/airep-apodeiktiko-apofaseon-ai-runtime\/\">\u03b5\u03bb\u03b5\u03b3\u03ba\u03c4\u03b9\u03ba\u03ce\u03bd \u03b1\u03c0\u03bf\u03b4\u03b5\u03af\u03be\u03b5\u03c9\u03bd \u03c3\u03b5 AI runtimes<\/a> \u03b5\u03af\u03bd\u03b1\u03b9 \u03c3\u03c5\u03bd\u03b1\u03c6\u03b5\u03af\u03c2: \u03c4\u03bf ranking change \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03c0\u03b1\u03c1\u03ac\u03b3\u03b5\u03b9 \u03c4\u03b5\u03ba\u03bc\u03b7\u03c1\u03b9\u03c9\u03bc\u03ad\u03bd\u03bf artifact, \u03cc\u03c7\u03b9 \u03bd\u03b1 \u03c0\u03b1\u03c1\u03b1\u03bc\u03ad\u03bd\u03b5\u03b9 \u03b1\u03cc\u03c1\u03b1\u03c4\u03b7 \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ae \u03bc\u03ad\u03c3\u03b1 \u03c3\u03b5 \u03bc\u03b9\u03b1 \u03b1\u03bb\u03c5\u03c3\u03af\u03b4\u03b1.<\/p>\n<h2 id=\"epta-vimata-pilot\">\u0395\u03c0\u03c4\u03ac \u03b2\u03ae\u03bc\u03b1\u03c4\u03b1 \u03b3\u03b9\u03b1 \u03b1\u03c3\u03c6\u03b1\u03bb\u03ad\u03c2 pilot<\/h2>\n<p>\u0388\u03bd\u03b1 pilot \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03bc\u03b9\u03ba\u03c1\u03cc, \u03b1\u03bb\u03bb\u03ac \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03b4\u03bf\u03ba\u03b9\u03bc\u03ac\u03b6\u03b5\u03b9 \u03c4\u03bf \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03cc corpus \u03ba\u03b1\u03b9 \u03c4\u03b1 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ac intents. \u03a4\u03bf \u03b6\u03b7\u03c4\u03bf\u03cd\u03bc\u03b5\u03bd\u03bf \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03bd\u03b1 \u03b1\u03bd\u03b1\u03c0\u03b1\u03c1\u03b1\u03c7\u03b8\u03b5\u03af \u03bf\u03bb\u03cc\u03ba\u03bb\u03b7\u03c1\u03b7 \u03b7 \u03bc\u03b5\u03bb\u03ad\u03c4\u03b7\u00b7 \u03b5\u03af\u03bd\u03b1\u03b9 \u03bd\u03b1 \u03b1\u03c0\u03bf\u03b4\u03b5\u03b9\u03c7\u03b8\u03b5\u03af \u03b1\u03bd \u03c5\u03c0\u03ac\u03c1\u03c7\u03b5\u03b9 \u03cc\u03bd\u03c4\u03c9\u03c2 keyword-stuffing regime \u03ba\u03b1\u03b9 \u03b1\u03bd \u03b7 \u03b1\u03bb\u03bb\u03b1\u03b3\u03ae \u03b2\u03b5\u03bb\u03c4\u03b9\u03ce\u03bd\u03b5\u03b9 \u03c4\u03b7\u03bd evidence retrieval \u03c7\u03c9\u03c1\u03af\u03c2 \u03bd\u03b1 \u03b2\u03bb\u03ac\u03c0\u03c4\u03b5\u03b9 \u03c4\u03b9\u03c2 \u03c5\u03c0\u03cc\u03bb\u03bf\u03b9\u03c0\u03b5\u03c2 \u03b5\u03c1\u03c9\u03c4\u03ae\u03c3\u03b5\u03b9\u03c2.<\/p>\n<div class=\"td-step-list\">\n<p class=\"td-step-list-title\">\u0391\u03c0\u03cc \u03c4\u03bf retrieval failure \u03c3\u03b5 \u03b5\u03bb\u03b5\u03b3\u03c7\u03cc\u03bc\u03b5\u03bd\u03b7 \u03b1\u03c0\u03cc\u03c6\u03b1\u03c3\u03b7<\/p>\n<ol>\n<li><span class=\"td-step-kicker\">\u0421\u0442\u044a\u043f\u043a\u0430 1<\/span><strong>\u039f\u03c1\u03af\u03c3\u03c4\u03b5 \u03c4\u03bf failure mode<\/strong>\n<p>\u03a3\u03c5\u03bb\u03bb\u03ad\u03be\u03c4\u03b5 queries \u03cc\u03c0\u03bf\u03c5 topic-near \u03ae keyword-heavy \u03ad\u03b3\u03b3\u03c1\u03b1\u03c6\u03b1 \u03b5\u03ba\u03c4\u03bf\u03c0\u03af\u03b6\u03bf\u03c5\u03bd \u03c4\u03bf answer-bearing evidence \u03b1\u03c0\u03cc \u03c4\u03bf prompt.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">\u0421\u0442\u044a\u043f\u043a\u0430 2<\/span><strong>\u03a7\u03c4\u03af\u03c3\u03c4\u03b5 \u03b1\u03bd\u03c4\u03b9\u03c0\u03c1\u03bf\u03c3\u03c9\u03c0\u03b5\u03c5\u03c4\u03b9\u03ba\u03cc probe set<\/strong>\n<p>\u0394\u03b5\u03b9\u03b3\u03bc\u03b1\u03c4\u03bf\u03bb\u03b7\u03c0\u03c4\u03ae\u03c3\u03c4\u03b5 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ac intents \u03b1\u03bd\u03ac \u03c3\u03c5\u03bb\u03bb\u03bf\u03b3\u03ae, \u03b3\u03bb\u03ce\u03c3\u03c3\u03b1 \u03ba\u03b1\u03b9 \u03c1\u03cc\u03bb\u03bf \u03c7\u03c1\u03ae\u03c3\u03c4\u03b7, \u03cc\u03c7\u03b9 \u03bc\u03cc\u03bd\u03bf \u03b5\u03cd\u03ba\u03bf\u03bb\u03b5\u03c2 \u03b5\u03c1\u03c9\u03c4\u03ae\u03c3\u03b5\u03b9\u03c2 \u03b5\u03c0\u03af\u03b4\u03b5\u03b9\u03be\u03b7\u03c2.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">\u0421\u0442\u044a\u043f\u043a\u0430 3<\/span><strong>\u039a\u03b1\u03c4\u03b1\u03b3\u03c1\u03ac\u03c8\u03c4\u03b5 relevance labels<\/strong>\n<p>\u0396\u03b7\u03c4\u03ae\u03c3\u03c4\u03b5 \u03b1\u03c0\u03cc domain reviewers \u03bd\u03b1 \u03c3\u03b7\u03bc\u03b5\u03b9\u03ce\u03c3\u03bf\u03c5\u03bd \u03c0\u03bf\u03b9\u03bf \u03ad\u03b3\u03b3\u03c1\u03b1\u03c6\u03bf \u03ae chunk \u03c0\u03b5\u03c1\u03b9\u03ad\u03c7\u03b5\u03b9 \u03c4\u03bf \u03c3\u03c4\u03bf\u03b9\u03c7\u03b5\u03af\u03bf \u03c0\u03bf\u03c5 \u03b1\u03c0\u03b1\u03b9\u03c4\u03b5\u03af \u03b7 \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">\u0421\u0442\u044a\u043f\u043a\u0430 4<\/span><strong>\u039c\u03b5\u03c4\u03c1\u03ae\u03c3\u03c4\u03b5 \u03c4\u03ad\u03c3\u03c3\u03b5\u03c1\u03b9\u03c2 \u03b4\u03b9\u03b1\u03b4\u03c1\u03bf\u03bc\u03ad\u03c2<\/strong>\n<p>\u03a3\u03c5\u03b3\u03ba\u03c1\u03af\u03bd\u03b5\u03c4\u03b5 similarity baseline, \u03c5\u03c0\u03ac\u03c1\u03c7\u03bf\u03bd cross-encoder, causal score \u03ba\u03b1\u03b9 hybrid \u03bc\u03b5 MRR \u03ae nDCG \u03ba\u03b1\u03b9 \u03bc\u03b5 evidence-in-prompt success.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">\u0421\u0442\u044a\u043f\u043a\u0430 5<\/span><strong>\u0392\u03ac\u03bb\u03c4\u03b5 corpus-level gate<\/strong>\n<p>\u0395\u03bd\u03b5\u03c1\u03b3\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03c4\u03b5 \u03c4\u03b7 \u03bd\u03ad\u03b1 \u03ba\u03b1\u03c4\u03ac\u03c4\u03b1\u03be\u03b7 \u03bc\u03cc\u03bd\u03bf \u03cc\u03c4\u03b1\u03bd \u03b7 \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03ac \u03b5\u03af\u03bd\u03b1\u03b9 \u03b8\u03b5\u03c4\u03b9\u03ba\u03ae \u03ba\u03b1\u03b9 \u03c4\u03bf uncertainty \u03c0\u03b1\u03c1\u03b1\u03bc\u03ad\u03bd\u03b5\u03b9 \u03bc\u03ad\u03c3\u03b1 \u03c3\u03c4\u03bf \u03b1\u03c0\u03bf\u03b4\u03b5\u03ba\u03c4\u03cc \u03cc\u03c1\u03b9\u03bf.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">\u0421\u0442\u044a\u043f\u043a\u0430 6<\/span><strong>\u039a\u03c1\u03b1\u03c4\u03ae\u03c3\u03c4\u03b5 fallback \u03ba\u03b1\u03b9 traces<\/strong>\n<p>\u0391\u03c0\u03bf\u03b8\u03b7\u03ba\u03b5\u03cd\u03c3\u03c4\u03b5 ranks, A\/B diagnostics \u03ba\u03b1\u03b9 source IDs \u03ba\u03b1\u03b9 \u03b5\u03c0\u03b9\u03c3\u03c4\u03c1\u03ad\u03c8\u03c4\u03b5 \u03c3\u03c4\u03bf baseline \u03cc\u03c4\u03b1\u03bd \u03c4\u03bf B \u03b5\u03af\u03bd\u03b1\u03b9 \u03ba\u03b5\u03bd\u03cc, \u03b1\u03c3\u03c4\u03b1\u03b8\u03ad\u03c2 \u03ae \u03b5\u03ba\u03c4\u03cc\u03c2 calibrated scope.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">\u0421\u0442\u044a\u043f\u043a\u0430 7<\/span><strong>\u0395\u03c0\u03b1\u03bd\u03b1\u03be\u03b9\u03bf\u03bb\u03bf\u03b3\u03ae\u03c3\u03c4\u03b5 \u03cc\u03c4\u03b1\u03bd \u03b1\u03bb\u03bb\u03ac\u03b6\u03b5\u03b9 \u03c4\u03bf corpus<\/strong>\n<p>\u039d\u03ad\u03b1 \u03ad\u03b3\u03b3\u03c1\u03b1\u03c6\u03b1, \u03bd\u03ad\u03b5\u03c2 \u03b5\u03ba\u03b4\u03cc\u03c3\u03b5\u03b9\u03c2 \u03ba\u03b1\u03b9 \u03bd\u03ad\u03b1 intents \u03bc\u03c0\u03bf\u03c1\u03bf\u03cd\u03bd \u03bd\u03b1 \u03bc\u03b5\u03c4\u03b1\u03ba\u03b9\u03bd\u03ae\u03c3\u03bf\u03c5\u03bd \u03c4\u03bf regime\u00b7 \u03c0\u03c1\u03bf\u03b3\u03c1\u03b1\u03bc\u03bc\u03b1\u03c4\u03af\u03c3\u03c4\u03b5 \u03c0\u03b5\u03c1\u03b9\u03bf\u03b4\u03b9\u03ba\u03ac probes \u03ba\u03b1\u03b9 rollback criteria.<\/p>\n<\/li>\n<\/ol>\n<\/div>\n<p>\u03a4\u03bf NIST AI RMF \u03c4\u03bf\u03c0\u03bf\u03b8\u03b5\u03c4\u03b5\u03af \u03c4\u03b7 \u03bc\u03ad\u03c4\u03c1\u03b7\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03c4\u03b7 \u03b4\u03b9\u03b1\u03c7\u03b5\u03af\u03c1\u03b9\u03c3\u03b7 \u03bc\u03ad\u03c3\u03b1 \u03c3\u03b5 \u03c3\u03c5\u03bd\u03b5\u03c7\u03ae \u03ba\u03cd\u03ba\u03bb\u03bf Govern, Map, Measure \u03ba\u03b1\u03b9 Manage. \u0393\u03b9\u03b1 \u03ad\u03bd\u03b1 RAG \u03c3\u03cd\u03c3\u03c4\u03b7\u03bc\u03b1 \u03b1\u03c5\u03c4\u03cc \u03c3\u03b7\u03bc\u03b1\u03af\u03bd\u03b5\u03b9 documented scope, testing \u03c0\u03c1\u03b9\u03bd \u03b1\u03c0\u03cc deployment, monitoring \u03c3\u03c4\u03b7\u03bd \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae \u03ba\u03b1\u03b9 \u03c3\u03b1\u03c6\u03ae \u03b1\u03c0\u03cc\u03c6\u03b1\u03c3\u03b7 \u03b3\u03b9\u03b1 \u03c4\u03bf \u03c0\u03cc\u03c4\u03b5 \u03b7 \u03c4\u03b5\u03c7\u03bd\u03b9\u03ba\u03ae \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03b1\u03c0\u03b5\u03bd\u03b5\u03c1\u03b3\u03bf\u03c0\u03bf\u03b9\u03b7\u03b8\u03b5\u03af.<\/p>\n<h2 id=\"periorismoi-symperasma\">\u03a0\u03b5\u03c1\u03b9\u03bf\u03c1\u03b9\u03c3\u03bc\u03bf\u03af \u03ba\u03b1\u03b9 \u03c0\u03c1\u03b1\u03ba\u03c4\u03b9\u03ba\u03cc \u03c3\u03c5\u03bc\u03c0\u03ad\u03c1\u03b1\u03c3\u03bc\u03b1<\/h2>\n<p>\u0397 \u03b5\u03c1\u03b3\u03b1\u03c3\u03af\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 preprint 16 \u03c3\u03b5\u03bb\u03af\u03b4\u03c9\u03bd, \u03ad\u03ba\u03b4\u03bf\u03c3\u03b7 v1 \u03c4\u03b7\u03c2 22\u03b1\u03c2 \u0391\u03c5\u03b3\u03bf\u03cd\u03c3\u03c4\u03bf\u03c5 2026. \u03a4\u03bf enterprise corpus \u03b5\u03af\u03bd\u03b1\u03b9 \u03b9\u03b4\u03b9\u03c9\u03c4\u03b9\u03ba\u03cc \u03ba\u03b1\u03b9 \u03c4\u03bf \u03ba\u03cd\u03c1\u03b9\u03bf \u03b8\u03b5\u03c4\u03b9\u03ba\u03cc \u03c0\u03bf\u03c3\u03bf\u03c4\u03b9\u03ba\u03cc \u03c0\u03b5\u03af\u03c1\u03b1\u03bc\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03bc\u03b9\u03ba\u03c1\u03cc \u03ba\u03b1\u03b9 \u03c3\u03c5\u03bd\u03b8\u03b5\u03c4\u03b9\u03ba\u03cc. \u03a4\u03bf calibration result \u03b2\u03b1\u03c3\u03af\u03b6\u03b5\u03c4\u03b1\u03b9 \u03c3\u03b5 bootstrap \u03c0\u03ac\u03bd\u03c9 \u03c3\u03c4\u03b1 \u03b4\u03b9\u03b1\u03b8\u03ad\u03c3\u03b9\u03bc\u03b1 scores, \u03cc\u03c7\u03b9 \u03c3\u03b5 \u03c0\u03bf\u03bb\u03c5\u03ac\u03c1\u03b9\u03b8\u03bc\u03b5\u03c2 \u03b1\u03bd\u03b5\u03be\u03ac\u03c1\u03c4\u03b7\u03c4\u03b5\u03c2 \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03b9\u03ba\u03ad\u03c2 \u03b5\u03b3\u03ba\u03b1\u03c4\u03b1\u03c3\u03c4\u03ac\u03c3\u03b5\u03b9\u03c2.<\/p>\n<p>\u0397 \u03bc\u03ad\u03b8\u03bf\u03b4\u03bf\u03c2 \u03b5\u03be\u03b1\u03c1\u03c4\u03ac\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03c0\u03bf\u03b9\u03cc\u03c4\u03b7\u03c4\u03b1 \u03c4\u03bf\u03c5 keyword extraction \u03ba\u03b1\u03b9 \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03c5\u03c0\u03cc\u03b8\u03b5\u03c3\u03b7 \u03cc\u03c4\u03b9 \u03c4\u03bf residual vocabulary B \u03c6\u03ad\u03c1\u03b5\u03b9 \u03c4\u03bf answer-bearing \u03c3\u03ae\u03bc\u03b1. \u03a3\u03b5 factoid corpora \u03b1\u03c5\u03c4\u03ae \u03b7 \u03c5\u03c0\u03cc\u03b8\u03b5\u03c3\u03b7 \u03b1\u03c0\u03ad\u03c4\u03c5\u03c7\u03b5. \u0397 \u03c3\u03c5\u03bd\u03ad\u03bd\u03c9\u03c3\u03b7 \u03bc\u03b5 similarity, \u03c4\u03b1 thresholds \u03ba\u03b1\u03b9 \u03c4\u03bf routing \u03b1\u03bd\u03ac collection \u03c0\u03b1\u03c1\u03b1\u03bc\u03ad\u03bd\u03bf\u03c5\u03bd \u03b1\u03bd\u03bf\u03b9\u03ba\u03c4\u03ad\u03c2 \u03c3\u03c7\u03b5\u03b4\u03b9\u03b1\u03c3\u03c4\u03b9\u03ba\u03ad\u03c2 \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ad\u03c2 \u03c0\u03bf\u03c5 \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03bf\u03bd\u03c4\u03b1\u03b9 domain-specific validation.<\/p>\n<p>\u03a4\u03bf \u03ce\u03c1\u03b9\u03bc\u03bf \u03c3\u03c5\u03bc\u03c0\u03ad\u03c1\u03b1\u03c3\u03bc\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c7\u03c1\u03ae\u03c3\u03b9\u03bc\u03bf \u03b1\u03ba\u03c1\u03b9\u03b2\u03ce\u03c2 \u03b5\u03c0\u03b5\u03b9\u03b4\u03ae \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03b5\u03bd\u03c4\u03c5\u03c0\u03c9\u03c3\u03b9\u03b1\u03ba\u03ac \u03b1\u03c0\u03cc\u03bb\u03c5\u03c4\u03bf. \u03a4\u03bf causal RAG reranking \u03b1\u03be\u03af\u03b6\u03b5\u03b9 \u03b4\u03bf\u03ba\u03b9\u03bc\u03ae \u03cc\u03c4\u03b1\u03bd \u03b7 \u03b5\u03c4\u03b1\u03b9\u03c1\u03b9\u03ba\u03ae \u03b3\u03bd\u03ce\u03c3\u03b7 \u03ad\u03c7\u03b5\u03b9 \u03c0\u03bf\u03bb\u03bb\u03ac \u03c0\u03b1\u03c1\u03cc\u03bc\u03bf\u03b9\u03b1 documents \u03ba\u03b1\u03b9 \u03b5\u03bc\u03c6\u03b1\u03bd\u03af\u03b6\u03b5\u03b9 false positives \u03b3\u03b5\u03bc\u03ac\u03c4\u03b1 query terms. \u0391\u03be\u03af\u03b6\u03b5\u03b9 \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03b9\u03ba\u03ae \u03b5\u03bd\u03b5\u03c1\u03b3\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7 \u03bc\u03cc\u03bd\u03bf \u03cc\u03c4\u03b1\u03bd labeled probes \u03b1\u03c0\u03bf\u03b4\u03b5\u03b9\u03ba\u03bd\u03cd\u03bf\u03c5\u03bd \u03cc\u03c6\u03b5\u03bb\u03bf\u03c2 \u03c3\u03c4\u03bf \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03bf corpus. \u0397 \u03ba\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03b7 retrieval \u03ba\u03b1\u03b9\u03bd\u03bf\u03c4\u03bf\u03bc\u03af\u03b1 \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03b1\u03c5\u03c4\u03ae \u03c0\u03bf\u03c5 \u03b1\u03bb\u03bb\u03ac\u03b6\u03b5\u03b9 \u03ba\u03ac\u03b8\u03b5 ranking\u00b7 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b1\u03c5\u03c4\u03ae \u03c0\u03bf\u03c5 \u03be\u03ad\u03c1\u03b5\u03b9 \u03c0\u03cc\u03c4\u03b5 \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03ba\u03c1\u03b1\u03c4\u03ae\u03c3\u03b5\u03b9 \u03c4\u03bf baseline.<\/p>\n<section class=\"td-service-cta\">\n<div class=\"td-service-cta-content\">\n<p class=\"td-service-cta-kicker\">RAG \u03bc\u03b5 \u03bc\u03b5\u03c4\u03c1\u03ae\u03c3\u03b9\u03bc\u03b7 \u03c0\u03bf\u03b9\u03cc\u03c4\u03b7\u03c4\u03b1 evidence<\/p>\n<p class=\"td-service-cta-title\">\u03a3\u03c7\u03b5\u03b4\u03b9\u03ac\u03c3\u03c4\u03b5 AI \u03b1\u03bd\u03b1\u03b6\u03ae\u03c4\u03b7\u03c3\u03b7 \u03c0\u03bf\u03c5 \u03be\u03ad\u03c1\u03b5\u03b9 \u03c0\u03cc\u03c4\u03b5 \u03bd\u03b1 \u03ba\u03c1\u03b1\u03c4\u03ac \u03c4\u03bf baseline<\/p>\n<p>\u0397 TWO DOTS \u03c3\u03c5\u03bd\u03b4\u03ad\u03b5\u03b9 \u03b5\u03c4\u03b1\u03b9\u03c1\u03b9\u03ba\u03ad\u03c2 \u03b2\u03ac\u03c3\u03b5\u03b9\u03c2 \u03b3\u03bd\u03ce\u03c3\u03b7\u03c2, AI assistants \u03ba\u03b1\u03b9 \u03b1\u03c5\u03c4\u03bf\u03bc\u03b1\u03c4\u03b9\u03c3\u03bc\u03bf\u03cd\u03c2 \u03bc\u03b5 retrieval evaluation, permissions, monitoring, \u03b1\u03c3\u03c6\u03b1\u03bb\u03ae fallbacks \u03ba\u03b1\u03b9 \u03b1\u03bd\u03b8\u03c1\u03ce\u03c0\u03b9\u03bd\u03b7 \u03b5\u03c0\u03bf\u03c0\u03c4\u03b5\u03af\u03b1.<\/p>\n<div class=\"td-service-cta-actions\"><a class=\"td-service-cta-button\" href=\"https:\/\/twodots.gr\/aftomatismoi-epicheiriseon-ai\/\">\u0394\u03b5\u03af\u03c4\u03b5 \u03bb\u03cd\u03c3\u03b5\u03b9\u03c2 \u03b1\u03c5\u03c4\u03bf\u03bc\u03b1\u03c4\u03b9\u03c3\u03bc\u03ce\u03bd \u03ba\u03b1\u03b9 AI<\/a><\/div>\n<\/div>\n<\/section>\n<section id=\"sychnes-erotiseis\" class=\"td-faq-section\">\n<div class=\"td-faq\">\n<p class=\"td-faq-heading\">\u0427\u0435\u0441\u0442\u043e \u0437\u0430\u0434\u0430\u0432\u0430\u043d\u0438 \u0432\u044a\u043f\u0440\u043e\u0441\u0438<\/p>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u03a4\u03b9 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c4\u03bf causal RAG reranking \u03b1\u03c5\u03c4\u03ae\u03c2 \u03c4\u03b7\u03c2 \u03bc\u03b5\u03bb\u03ad\u03c4\u03b7\u03c2;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u0395\u03af\u03bd\u03b1\u03b9 training-free \u03b5\u03c0\u03b1\u03bd\u03b1\u03b2\u03b1\u03b8\u03bc\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7 \u03c4\u03bf\u03c5 \u03ae\u03b4\u03b7 \u03b1\u03bd\u03b1\u03ba\u03c4\u03b7\u03bc\u03ad\u03bd\u03bf\u03c5 candidate set \u03bc\u03b5 \u03b2\u03ac\u03c3\u03b7 \u03c4\u03bf residual vocabulary \u03b5\u03bd\u03cc\u03c2 \u03b5\u03b3\u03b3\u03c1\u03ac\u03c6\u03bf\u03c5, \u03b1\u03c6\u03bf\u03cd \u03b1\u03c6\u03b1\u03b9\u03c1\u03b5\u03b8\u03bf\u03cd\u03bd \u03bf\u03b9 \u03cc\u03c1\u03bf\u03b9 \u03c0\u03bf\u03c5 \u03b5\u03c0\u03b9\u03ba\u03b1\u03bb\u03cd\u03c0\u03c4\u03bf\u03bd\u03c4\u03b1\u03b9 \u03bc\u03b5 \u03c4\u03b7\u03bd \u03b5\u03c1\u03ce\u03c4\u03b7\u03c3\u03b7.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u0395\u03ba\u03c4\u03b9\u03bc\u03ac \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03cc causal effect;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u038c\u03c7\u03b9. \u039f\u03b9 \u03c3\u03c5\u03b3\u03b3\u03c1\u03b1\u03c6\u03b5\u03af\u03c2 \u03c0\u03b1\u03c1\u03bf\u03c5\u03c3\u03b9\u03ac\u03b6\u03bf\u03c5\u03bd \u03c4\u03bf\u03bd causal \u03b3\u03c1\u03ac\u03c6\u03bf \u03c9\u03c2 \u03b4\u03bf\u03bc\u03b9\u03ba\u03cc \u03ba\u03b1\u03b9 motivational \u03c0\u03bb\u03b1\u03af\u03c3\u03b9\u03bf. \u03a4\u03bf score \u03b5\u03af\u03bd\u03b1\u03b9 heuristic \u03ba\u03b1\u03b9 \u03cc\u03c7\u03b9 \u03c4\u03b1\u03c5\u03c4\u03bf\u03c0\u03bf\u03b9\u03b7\u03bc\u03ad\u03bd\u03bf causal estimand.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u03a0\u03cc\u03c4\u03b5 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b2\u03bf\u03b7\u03b8\u03ae\u03c3\u03b5\u03b9 \u03c0\u03b5\u03c1\u03b9\u03c3\u03c3\u03cc\u03c4\u03b5\u03c1\u03bf;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u038c\u03c4\u03b1\u03bd \u03ad\u03bd\u03b1 \u03b5\u03c4\u03b1\u03b9\u03c1\u03b9\u03ba\u03cc corpus \u03ad\u03c7\u03b5\u03b9 \u03c0\u03bf\u03bb\u03bb\u03ac topic-near \u03ae keyword-heavy \u03ad\u03b3\u03b3\u03c1\u03b1\u03c6\u03b1 \u03c0\u03bf\u03c5 \u03b1\u03bd\u03b5\u03b2\u03b1\u03af\u03bd\u03bf\u03c5\u03bd \u03c8\u03b7\u03bb\u03ac \u03c7\u03c9\u03c1\u03af\u03c2 \u03bd\u03b1 \u03c0\u03b5\u03c1\u03b9\u03ad\u03c7\u03bf\u03c5\u03bd \u03c4\u03bf answer-bearing evidence.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u03a3\u03b5 \u03c0\u03bf\u03b9\u03b1 \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03b1 \u03b1\u03c0\u03ad\u03c4\u03c5\u03c7\u03b5;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u03a5\u03c0\u03bf\u03b1\u03c0\u03ad\u03b4\u03c9\u03c3\u03b5 \u03b1\u03c0\u03ad\u03bd\u03b1\u03bd\u03c4\u03b9 \u03c3\u03c4\u03bf similarity baseline \u03c3\u03c4\u03b1 SciFact, NFCorpus \u03ba\u03b1\u03b9 ArguAna, \u03cc\u03c0\u03bf\u03c5 \u03b7 \u03ba\u03bf\u03b9\u03bd\u03ae \u03bf\u03c1\u03bf\u03bb\u03bf\u03b3\u03af\u03b1 query \u03ba\u03b1\u03b9 \u03c3\u03c9\u03c3\u03c4\u03bf\u03cd \u03b5\u03b3\u03b3\u03c1\u03ac\u03c6\u03bf\u03c5 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c7\u03c1\u03ae\u03c3\u03b9\u03bc\u03bf relevance signal.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u03a0\u03c1\u03bf\u03c3\u03b8\u03ad\u03c4\u03b5\u03b9 \u03bd\u03ad\u03bf LLM call \u03c3\u03c4\u03bf query time;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u038c\u03c7\u03b9 \u03c3\u03c4\u03b7\u03bd \u03c0\u03c1\u03bf\u03c4\u03b5\u03b9\u03bd\u03cc\u03bc\u03b5\u03bd\u03b7 \u03c1\u03bf\u03ae. \u03a0\u03c1\u03bf\u03c3\u03b8\u03ad\u03c4\u03b5\u03b9 keyword extraction \u03ba\u03b1\u03b9 embedding\/scoring \u03c4\u03c9\u03bd residual terms \u03c0\u03ac\u03bd\u03c9 \u03c3\u03c4\u03bf \u03ae\u03b4\u03b7 \u03bc\u03b9\u03ba\u03c1\u03cc candidate set.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u0393\u03b9\u03b1\u03c4\u03af \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 semantic absorption;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u0395\u03c0\u03b5\u03b9\u03b4\u03ae \u03b7 \u03b1\u03ba\u03c1\u03b9\u03b2\u03ae\u03c2 \u03b1\u03bd\u03c4\u03b9\u03c3\u03c4\u03bf\u03af\u03c7\u03b9\u03c3\u03b7 \u03b1\u03c6\u03ae\u03bd\u03b5\u03b9 \u03c3\u03c5\u03bd\u03ce\u03bd\u03c5\u03bc\u03b1 \u03ba\u03b1\u03b9 \u03b3\u03b5\u03b9\u03c4\u03bf\u03bd\u03b9\u03ba\u03bf\u03cd\u03c2 \u03cc\u03c1\u03bf\u03c5\u03c2 \u03c4\u03c9\u03bd distractors \u03bc\u03ad\u03c3\u03b1 \u03c3\u03c4\u03bf B. \u0397 \u03c3\u03b7\u03bc\u03b1\u03c3\u03b9\u03bf\u03bb\u03bf\u03b3\u03b9\u03ba\u03ae \u03b1\u03c0\u03bf\u03c1\u03c1\u03cc\u03c6\u03b7\u03c3\u03b7 \u03bc\u03b5\u03c4\u03b1\u03c6\u03ad\u03c1\u03b5\u03b9 \u03b1\u03c5\u03c4\u03bf\u03cd\u03c2 \u03c4\u03bf\u03c5\u03c2 \u03cc\u03c1\u03bf\u03c5\u03c2 \u03c3\u03c4\u03bf A.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u03a0\u03ce\u03c2 \u03b1\u03c0\u03bf\u03c6\u03b1\u03c3\u03af\u03b6\u03b5\u03b9 \u03bc\u03b9\u03b1 \u03bf\u03bc\u03ac\u03b4\u03b1 \u03b1\u03bd \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03c4\u03bf \u03b5\u03bd\u03b5\u03c1\u03b3\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03b5\u03b9;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u039c\u03b5 \u03b1\u03bd\u03c4\u03b9\u03c0\u03c1\u03bf\u03c3\u03c9\u03c0\u03b5\u03c5\u03c4\u03b9\u03ba\u03ac labeled probes, \u03c3\u03cd\u03b3\u03ba\u03c1\u03b9\u03c3\u03b7 baseline \u03ba\u03b1\u03b9 \u03bd\u03ad\u03bf\u03c5 ranking \u03ba\u03b1\u03b9 corpus-level gate \u03c0\u03bf\u03c5 \u03b5\u03bd\u03b5\u03c1\u03b3\u03bf\u03c0\u03bf\u03b9\u03b5\u03af \u03c4\u03b7 \u03bc\u03ad\u03b8\u03bf\u03b4\u03bf \u03bc\u03cc\u03bd\u03bf \u03cc\u03c4\u03b1\u03bd \u03c4\u03bf \u03bc\u03b5\u03c4\u03c1\u03b7\u03bc\u03ad\u03bd\u03bf \u03cc\u03c6\u03b5\u03bb\u03bf\u03c2 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b8\u03b5\u03c4\u03b9\u03ba\u03cc.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u03a0\u03bf\u03b9\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b7 \u03b1\u03c3\u03c6\u03b1\u03bb\u03ad\u03c3\u03c4\u03b5\u03c1\u03b7 \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ae \u03c3\u03b5 \u03ac\u03b3\u03bd\u03c9\u03c3\u03c4\u03bf corpus;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u039d\u03b1 \u03c0\u03b1\u03c1\u03b1\u03bc\u03b5\u03af\u03bd\u03b5\u03b9 \u03b5\u03bd\u03b5\u03c1\u03b3\u03cc \u03c4\u03bf similarity baseline \u03ae \u03ad\u03bd\u03b1 \u03bc\u03b5\u03c4\u03c1\u03b7\u03bc\u03ad\u03bd\u03bf hybrid fallback \u03bc\u03ad\u03c7\u03c1\u03b9 offline calibration \u03c3\u03c4\u03bf \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03cc corpus \u03bd\u03b1 \u03b1\u03c0\u03bf\u03b4\u03b5\u03af\u03be\u03b5\u03b9 \u03ba\u03b1\u03b8\u03b1\u03c1\u03cc \u03cc\u03c6\u03b5\u03bb\u03bf\u03c2.<\/p>\n<\/div>\n<\/details>\n<\/div>\n<\/section>\n<div class=\"td-source-list\">\n<p id=\"piges\" class=\"td-source-list-title\">\u0418\u0437\u0442\u043e\u0447\u043d\u0438\u0446\u0438<\/p>\n<ul>\n<li><a href=\"https:\/\/arxiv.org\/abs\/2608.21702\" target=\"_blank\" rel=\"noopener\">arXiv \u2014 From Association to Causation: Improving Retrieval Precision of RAG<\/a><\/li>\n<li><a href=\"https:\/\/github.com\/Silk-Road\/causal-rag-rerank\" target=\"_blank\" rel=\"noopener\">GitHub \u2014 \u0395\u03c0\u03af\u03c3\u03b7\u03bc\u03b7 \u03c5\u03bb\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7 causal-rag-rerank<\/a><\/li>\n<li><a href=\"https:\/\/arxiv.org\/abs\/2104.08663\" target=\"_blank\" rel=\"noopener\">arXiv \u2014 BEIR: A Heterogeneous Benchmark for Information Retrieval<\/a><\/li>\n<li><a href=\"https:\/\/arxiv.org\/abs\/2402.03216\" target=\"_blank\" rel=\"noopener\">arXiv \u2014 BGE M3-Embedding<\/a><\/li>\n<li><a href=\"https:\/\/airc.nist.gov\/airmf-resources\/airmf\/5-sec-core\/\" target=\"_blank\" rel=\"noopener\">NIST \u2014 AI Risk Management Framework Core<\/a><\/li>\n<\/ul>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>\u03a4\u03bf causal RAG reranking \u03be\u03b5\u03c7\u03c9\u03c1\u03af\u03b6\u03b5\u03b9 answer-bearing evidence \u03b1\u03c0\u03cc keyword-stuffed \u03ad\u03b3\u03b3\u03c1\u03b1\u03c6\u03b1, \u03b1\u03bb\u03bb\u03ac \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 calibration \u03b5\u03c0\u03b5\u03b9\u03b4\u03ae \u03b1\u03c0\u03bf\u03c4\u03c5\u03b3\u03c7\u03ac\u03bd\u03b5\u03b9 \u03c3\u03b5 factoid corpora.<\/p>","protected":false},"author":1,"featured_media":104939,"comment_status":"open","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_gspb_post_css":"","content-type":"","footnotes":""},"categories":[199],"tags":[18399,8768,9225,8233,20702],"class_list":["post-97881","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-techniti-noimosyni","tag-causal-ai","tag-enterprise-ai","tag-llm","tag-rag","tag-retrieval"],"blocksy_meta":{"styles_descriptor":{"styles":{"desktop":"","tablet":"","mobile":""},"google_fonts":[],"version":8}},"_links":{"self":[{"href":"https:\/\/twodots.gr\/bg\/wp-json\/wp\/v2\/posts\/97881","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/twodots.gr\/bg\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/twodots.gr\/bg\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/twodots.gr\/bg\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/twodots.gr\/bg\/wp-json\/wp\/v2\/comments?post=97881"}],"version-history":[{"count":1,"href":"https:\/\/twodots.gr\/bg\/wp-json\/wp\/v2\/posts\/97881\/revisions"}],"predecessor-version":[{"id":104940,"href":"https:\/\/twodots.gr\/bg\/wp-json\/wp\/v2\/posts\/97881\/revisions\/104940"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/twodots.gr\/bg\/wp-json\/wp\/v2\/media\/104939"}],"wp:attachment":[{"href":"https:\/\/twodots.gr\/bg\/wp-json\/wp\/v2\/media?parent=97881"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/twodots.gr\/bg\/wp-json\/wp\/v2\/categories?post=97881"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/twodots.gr\/bg\/wp-json\/wp\/v2\/tags?post=97881"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}