{"id":97672,"date":"2026-09-17T15:07:24","date_gmt":"2026-09-17T12:07:24","guid":{"rendered":"https:\/\/twodots.gr\/?p=97672"},"modified":"2026-09-17T15:07:26","modified_gmt":"2026-09-17T12:07:26","slug":"model-collapse-ai-synthetic-data","status":"publish","type":"post","link":"https:\/\/twodots.gr\/bg\/model-collapse-ai-synthetic-data\/","title":{"rendered":"Model collapse: \u03cc\u03c4\u03b1\u03bd \u03b7 AI \u03b5\u03ba\u03c0\u03b1\u03b9\u03b4\u03b5\u03cd\u03b5\u03c4\u03b1\u03b9 \u03c3\u03c4\u03b7 \u03b4\u03b9\u03ba\u03ae \u03c4\u03b7\u03c2 \u03b7\u03c7\u03ce"},"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 model collapse \u03b5\u03bc\u03c6\u03b1\u03bd\u03af\u03b6\u03b5\u03c4\u03b1\u03b9 \u03cc\u03c4\u03b1\u03bd \u03ad\u03bd\u03b1 generative AI \u03c3\u03cd\u03c3\u03c4\u03b7\u03bc\u03b1 \u03b5\u03ba\u03c0\u03b1\u03b9\u03b4\u03b5\u03cd\u03b5\u03c4\u03b1\u03b9 \u03b1\u03bd\u03b1\u03b4\u03c1\u03bf\u03bc\u03b9\u03ba\u03ac \u03c3\u03b5 \u03b4\u03b9\u03ba\u03ac \u03c4\u03bf\u03c5 \u03ae \u03ac\u03bb\u03bb\u03b1 \u03c3\u03c5\u03bd\u03b8\u03b5\u03c4\u03b9\u03ba\u03ac outputs \u03ba\u03b1\u03b9, \u03b3\u03cd\u03c1\u03bf \u03bc\u03b5 \u03c4\u03bf\u03bd \u03b3\u03cd\u03c1\u03bf, \u03c7\u03ac\u03bd\u03b5\u03b9 \u03b5\u03c0\u03b1\u03c6\u03ae \u03bc\u03b5 \u03c4\u03b7\u03bd \u03b1\u03bd\u03b8\u03c1\u03ce\u03c0\u03b9\u03bd\u03b7 \u03ba\u03b1\u03c4\u03b1\u03bd\u03bf\u03bc\u03ae \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd. \u03a3\u03c5\u03bd\u03ae\u03b8\u03c9\u03c2 \u03b4\u03b5\u03bd \u03ba\u03b1\u03c4\u03b1\u03c1\u03c1\u03ad\u03bf\u03c5\u03bd \u03c0\u03c1\u03ce\u03c4\u03b1 \u03bf\u03b9 \u03c3\u03c5\u03c7\u03bd\u03ad\u03c2 \u03c0\u03b5\u03c1\u03b9\u03c0\u03c4\u03ce\u03c3\u03b5\u03b9\u03c2\u00b7 \u03c3\u03c5\u03c1\u03c1\u03b9\u03ba\u03bd\u03ce\u03bd\u03bf\u03bd\u03c4\u03b1\u03b9 \u03b7 \u03c0\u03bf\u03b9\u03ba\u03b9\u03bb\u03af\u03b1, \u03bf\u03b9 \u03c3\u03c0\u03ac\u03bd\u03b9\u03b5\u03c2 \u03ba\u03b1\u03c4\u03b7\u03b3\u03bf\u03c1\u03af\u03b5\u03c2 \u03ba\u03b1\u03b9 \u03c4\u03b1 \u03b4\u03cd\u03c3\u03ba\u03bf\u03bb\u03b1 \u03c0\u03b1\u03c1\u03b1\u03b4\u03b5\u03af\u03b3\u03bc\u03b1\u03c4\u03b1 \u03c0\u03bf\u03c5 \u03bf \u03bc\u03ad\u03c3\u03bf\u03c2 \u03b4\u03b5\u03af\u03ba\u03c4\u03b7\u03c2 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03ba\u03c1\u03cd\u03c8\u03b5\u03b9.<\/p>\n<p>\u0397 \u03c0\u03c1\u03b1\u03ba\u03c4\u03b9\u03ba\u03ae \u03ac\u03bc\u03c5\u03bd\u03b1 \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03b7 \u03c0\u03bb\u03ae\u03c1\u03b7\u03c2 \u03b1\u03c0\u03cc\u03c1\u03c1\u03b9\u03c8\u03b7 \u03c4\u03c9\u03bd \u03c3\u03c5\u03bd\u03b8\u03b5\u03c4\u03b9\u03ba\u03ce\u03bd \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd. \u0395\u03af\u03bd\u03b1\u03b9 \u03ad\u03bd\u03b1 \u03b5\u03bb\u03b5\u03b3\u03c7\u03cc\u03bc\u03b5\u03bd\u03bf \u03bc\u03af\u03b3\u03bc\u03b1 \u03bc\u03b5 \u03c3\u03c4\u03b1\u03b8\u03b5\u03c1\u03cc \u03b1\u03bd\u03b8\u03c1\u03ce\u03c0\u03b9\u03bd\u03bf \u03c0\u03c5\u03c1\u03ae\u03bd\u03b1, \u03c0\u03bb\u03ae\u03c1\u03b5\u03c2 provenance, \u03bc\u03b5\u03c4\u03c1\u03ae\u03c3\u03b5\u03b9\u03c2 \u03b1\u03bd\u03ac rare-case slice \u03ba\u03b1\u03b9 \u03b4\u03c5\u03bd\u03b1\u03c4\u03cc\u03c4\u03b7\u03c4\u03b1 rollback. \u03a4\u03b1 \u03c0\u03bf\u03c3\u03bf\u03c3\u03c4\u03ac \u03c0\u03bf\u03c5 \u03c0\u03c1\u03bf\u03c4\u03b5\u03af\u03bd\u03b5\u03b9 \u03b7 \u03b1\u03bd\u03b1\u03c3\u03ba\u03cc\u03c0\u03b7\u03c3\u03b7 \u03c4\u03c9\u03bd Xihao Xie \u03ba\u03b1\u03b9 Beichen Hu \u03b5\u03af\u03bd\u03b1\u03b9 \u03ba\u03b1\u03c4\u03b5\u03c5\u03b8\u03cd\u03bd\u03c3\u03b5\u03b9\u03c2 \u03c4\u03c9\u03bd \u03c3\u03c5\u03b3\u03b3\u03c1\u03b1\u03c6\u03ad\u03c9\u03bd, \u03cc\u03c7\u03b9 \u03ba\u03b1\u03b8\u03bf\u03bb\u03b9\u03ba\u03ac \u03cc\u03c1\u03b9\u03b1 \u03b1\u03c3\u03c6\u03ac\u03bb\u03b5\u03b9\u03b1\u03c2.<\/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=\"#aftokatanalosi-katanomi\">\u0397 \u03b1\u03c5\u03c4\u03bf\u03ba\u03b1\u03c4\u03b1\u03bd\u03ac\u03bb\u03c9\u03c3\u03b7 \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd \u03b1\u03bb\u03bb\u03ac\u03b6\u03b5\u03b9 \u03c4\u03b7\u03bd \u03ba\u03b1\u03c4\u03b1\u03bd\u03bf\u03bc\u03ae<\/a><\/li>\n<li><a href=\"#spanies-periptoseis\">\u03a0\u03c1\u03ce\u03c4\u03b1 \u03c7\u03ac\u03bd\u03bf\u03bd\u03c4\u03b1\u03b9 \u03bf\u03b9 \u03c3\u03c0\u03ac\u03bd\u03b9\u03b5\u03c2 \u03ba\u03b1\u03b9 \u03b4\u03cd\u03c3\u03ba\u03bf\u03bb\u03b5\u03c2 \u03c0\u03b5\u03c1\u03b9\u03c0\u03c4\u03ce\u03c3\u03b5\u03b9\u03c2<\/a><\/li>\n<li><a href=\"#diafores-collapse\">\u03a4\u03b9 \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 model collapse<\/a><\/li>\n<li><a href=\"#llm-decoding\">\u03a0\u03ce\u03c2 \u03c4\u03bf \u03c3\u03c5\u03bd\u03c4\u03b7\u03c1\u03b7\u03c4\u03b9\u03ba\u03cc decoding \u03ba\u03cc\u03b2\u03b5\u03b9 \u03c4\u03b7\u03bd \u03bf\u03c5\u03c1\u03ac<\/a><\/li>\n<li><a href=\"#multimodal-bias\">\u03a3\u03c4\u03b1 multimodal \u03c3\u03c5\u03c3\u03c4\u03ae\u03bc\u03b1\u03c4\u03b1 \u03c4\u03bf bias \u03c4\u03b1\u03be\u03b9\u03b4\u03b5\u03cd\u03b5\u03b9<\/a><\/li>\n<li><a href=\"#anthropos-pyrinas\">\u039f \u03b1\u03bd\u03b8\u03c1\u03ce\u03c0\u03b9\u03bd\u03bf\u03c2 \u03c0\u03c5\u03c1\u03ae\u03bd\u03b1\u03c2 \u03b5\u03af\u03bd\u03b1\u03b9 anchor<\/a><\/li>\n<li><a href=\"#provenance\">Provenance: \u03c0\u03bf\u03b9\u03bf\u03c2 \u03c0\u03b1\u03c1\u03ae\u03b3\u03b1\u03b3\u03b5 \u03ba\u03ac\u03b8\u03b5 sample<\/a><\/li>\n<li><a href=\"#metrikes-oura\">\u039c\u03b5\u03c4\u03c1\u03ae\u03c3\u03b5\u03b9\u03c2 \u03b3\u03b9\u03b1 \u03c4\u03b7\u03bd \u03bf\u03c5\u03c1\u03ac \u03ba\u03b1\u03b9 \u03cc\u03c7\u03b9 \u03bc\u03cc\u03bd\u03bf \u03c4\u03bf\u03bd \u03bc\u03ad\u03c3\u03bf \u03cc\u03c1\u03bf<\/a><\/li>\n<li><a href=\"#algorithmika-guardrails\">\u0391\u03bb\u03b3\u03bf\u03c1\u03b9\u03b8\u03bc\u03b9\u03ba\u03ac guardrails \u03bc\u03b5 \u03c3\u03b1\u03c6\u03ae \u03cc\u03c1\u03b9\u03b1<\/a><\/li>\n<li><a href=\"#pososta-survey\">\u0393\u03b9\u03b1\u03c4\u03af \u03c4\u03b1 \u03c0\u03bf\u03c3\u03bf\u03c3\u03c4\u03ac \u03c4\u03bf\u03c5 survey \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03ba\u03b1\u03bd\u03cc\u03bd\u03b1\u03c2<\/a><\/li>\n<li><a href=\"#omada-epta-vimata\">\u0388\u03bd\u03b1 \u03c0\u03c1\u03b1\u03ba\u03c4\u03b9\u03ba\u03cc \u03c3\u03c7\u03ad\u03b4\u03b9\u03bf \u03c3\u03b5 \u03b5\u03c0\u03c4\u03ac \u03b2\u03ae\u03bc\u03b1\u03c4\u03b1<\/a><\/li>\n<li><a href=\"#anoikta-erotimata-agora\">\u0391\u03bd\u03bf\u03b9\u03c7\u03c4\u03ac \u03b5\u03c1\u03c9\u03c4\u03ae\u03bc\u03b1\u03c4\u03b1 \u03c0\u03bf\u03c5 \u03b1\u03c6\u03bf\u03c1\u03bf\u03cd\u03bd \u03ae\u03b4\u03b7 \u03c4\u03b7\u03bd \u03b1\u03b3\u03bf\u03c1\u03ac<\/a><\/li>\n<\/ul>\n<\/div>\n<h2 id=\"aftokatanalosi-katanomi\">\u0397 \u03b1\u03c5\u03c4\u03bf\u03ba\u03b1\u03c4\u03b1\u03bd\u03ac\u03bb\u03c9\u03c3\u03b7 \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd \u03b1\u03bb\u03bb\u03ac\u03b6\u03b5\u03b9 \u03c4\u03b7\u03bd \u03ba\u03b1\u03c4\u03b1\u03bd\u03bf\u03bc\u03ae<\/h2>\n<p>\u0388\u03bd\u03b1 generative model \u03b5\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03b5\u03af \u03bd\u03b1 \u03c0\u03c1\u03bf\u03c3\u03b5\u03b3\u03b3\u03af\u03c3\u03b5\u03b9 \u03c4\u03b7\u03bd \u03ba\u03b1\u03c4\u03b1\u03bd\u03bf\u03bc\u03ae \u03c4\u03c9\u03bd \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd \u03c0\u03bf\u03c5 \u03c0\u03b1\u03c1\u03b1\u03c4\u03b7\u03c1\u03b5\u03af. \u038c\u03c4\u03b1\u03bd \u03c4\u03bf \u03b1\u03c1\u03c7\u03b9\u03ba\u03cc \u03c3\u03cd\u03bd\u03bf\u03bb\u03bf \u03b5\u03af\u03bd\u03b1\u03b9 \u03b1\u03bd\u03b8\u03c1\u03ce\u03c0\u03b9\u03bd\u03bf, \u03c0\u03b5\u03c1\u03b9\u03bb\u03b1\u03bc\u03b2\u03ac\u03bd\u03b5\u03b9 \u03c3\u03c5\u03c7\u03bd\u03ac \u03bc\u03bf\u03c4\u03af\u03b2\u03b1 \u03b1\u03bb\u03bb\u03ac \u03ba\u03b1\u03b9 \u03b1\u03c3\u03c5\u03bd\u03ae\u03b8\u03b9\u03c3\u03c4\u03b5\u03c2 \u03b4\u03b9\u03b1\u03c4\u03c5\u03c0\u03ce\u03c3\u03b5\u03b9\u03c2, \u03c3\u03c0\u03ac\u03bd\u03b9\u03b5\u03c2 \u03ba\u03b1\u03c4\u03b7\u03b3\u03bf\u03c1\u03af\u03b5\u03c2, \u03b1\u03ba\u03c1\u03b1\u03af\u03b5\u03c2 \u03c0\u03b5\u03c1\u03b9\u03c0\u03c4\u03ce\u03c3\u03b5\u03b9\u03c2 \u03ba\u03b1\u03b9 \u03b1\u03bd\u03c4\u03b9\u03c6\u03ac\u03c3\u03b5\u03b9\u03c2. \u0397 \u03c3\u03c5\u03bd\u03b8\u03b5\u03c4\u03b9\u03ba\u03ae \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae \u03b5\u03af\u03bd\u03b1\u03b9 \u03b4\u03b5\u03af\u03b3\u03bc\u03b1 \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03ae\u03b4\u03b7 \u03b1\u03c4\u03b5\u03bb\u03ae \u03c0\u03c1\u03bf\u03c3\u03ad\u03b3\u03b3\u03b9\u03c3\u03b7 \u03c4\u03bf\u03c5 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf\u03c5. \u039a\u03ac\u03b8\u03b5 \u03c6\u03af\u03bb\u03c4\u03c1\u03bf, \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ae \u03ae \u03c0\u03b5\u03c1\u03b9\u03bf\u03c1\u03b9\u03c3\u03bc\u03cc\u03c2 \u03b1\u03c0\u03bf\u03ba\u03c9\u03b4\u03b9\u03ba\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7\u03c2 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b1\u03c6\u03b1\u03b9\u03c1\u03ad\u03c3\u03b5\u03b9 \u03bc\u03ad\u03c1\u03bf\u03c2 \u03b1\u03c5\u03c4\u03ae\u03c2 \u03c4\u03b7\u03c2 \u03bf\u03c5\u03c1\u03ac\u03c2.<\/p>\n<p>\u03a3\u03c4\u03bf\u03bd \u03b5\u03c0\u03cc\u03bc\u03b5\u03bd\u03bf \u03b3\u03cd\u03c1\u03bf, \u03c4\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03b4\u03b5\u03bd \u03b2\u03bb\u03ad\u03c0\u03b5\u03b9 \u03b1\u03c0\u03bb\u03ce\u03c2 \u03c0\u03b5\u03c1\u03b9\u03c3\u03c3\u03cc\u03c4\u03b5\u03c1\u03bf \u03c5\u03bb\u03b9\u03ba\u03cc. \u0392\u03bb\u03ad\u03c0\u03b5\u03b9 \u03bc\u03b9\u03b1 \u03b5\u03bb\u03b1\u03c6\u03c1\u03ce\u03c2 \u03c3\u03c4\u03b5\u03bd\u03cc\u03c4\u03b5\u03c1\u03b7 \u03b5\u03ba\u03b4\u03bf\u03c7\u03ae \u03c4\u03bf\u03c5 \u03ba\u03cc\u03c3\u03bc\u03bf\u03c5. \u039f\u03b9 \u03c3\u03c5\u03c7\u03bd\u03ad\u03c2 \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ad\u03c2 \u03b1\u03c0\u03bf\u03ba\u03c4\u03bf\u03cd\u03bd \u03bc\u03b5\u03b3\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03bf \u03b2\u03ac\u03c1\u03bf\u03c2, \u03b5\u03bd\u03ce \u03bf\u03b9 \u03c7\u03b1\u03bc\u03b7\u03bb\u03ae\u03c2 \u03c0\u03b9\u03b8\u03b1\u03bd\u03cc\u03c4\u03b7\u03c4\u03b1\u03c2 \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ad\u03c2 \u03b5\u03bc\u03c6\u03b1\u03bd\u03af\u03b6\u03bf\u03bd\u03c4\u03b1\u03b9 \u03bb\u03b9\u03b3\u03cc\u03c4\u03b5\u03c1\u03bf. \u0391\u03bd \u03b1\u03c5\u03c4\u03cc \u03b5\u03c0\u03b1\u03bd\u03b1\u03bb\u03b7\u03c6\u03b8\u03b5\u03af, \u03b7 \u03b1\u03c0\u03ce\u03bb\u03b5\u03b9\u03b1 \u03b3\u03af\u03bd\u03b5\u03c4\u03b1\u03b9 \u03c3\u03c9\u03c1\u03b5\u03c5\u03c4\u03b9\u03ba\u03ae. \u0397 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\u03c0\u03c4\u03ce\u03c3\u03b7 \u03b5\u03bd\u03c4\u03c1\u03bf\u03c0\u03af\u03b1\u03c2, \u03bb\u03b9\u03b3\u03cc\u03c4\u03b5\u03c1\u03b1 distinct n-grams, \u03c0\u03b9\u03bf \u03c4\u03c5\u03c0\u03bf\u03c0\u03bf\u03b9\u03b7\u03bc\u03ad\u03bd\u03b5\u03c2 \u03b1\u03c0\u03b1\u03bd\u03c4\u03ae\u03c3\u03b5\u03b9\u03c2 \u03ba\u03b1\u03b9 \u03ba\u03ac\u03bc\u03c8\u03b7 \u03c4\u03c9\u03bd \u03b1\u03bd\u03b1\u03bc\u03b5\u03bd\u03cc\u03bc\u03b5\u03bd\u03c9\u03bd scaling curves. \u03a3\u03b5 \u03b5\u03b9\u03ba\u03cc\u03bd\u03b5\u03c2, \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b1\u03c5\u03be\u03ac\u03bd\u03b5\u03c4\u03b1\u03b9 \u03c4\u03bf FID, \u03bd\u03b1 \u03c0\u03ad\u03c6\u03c4\u03bf\u03c5\u03bd precision \u03ba\u03b1\u03b9 recall \u03ba\u03ac\u03bb\u03c5\u03c8\u03b7\u03c2 \u03ba\u03b1\u03b9 \u03bd\u03b1 \u03b5\u03be\u03b1\u03c6\u03b1\u03bd\u03af\u03b6\u03bf\u03bd\u03c4\u03b1\u03b9 \u03c0\u03c1\u03ce\u03c4\u03b1 \u03bf\u03b9 \u03c3\u03c0\u03ac\u03bd\u03b9\u03b5\u03c2 \u03c3\u03c5\u03bd\u03b8\u03ad\u03c3\u03b5\u03b9\u03c2. \u03a3\u03b5 multimodal \u03c3\u03c5\u03c3\u03c4\u03ae\u03bc\u03b1\u03c4\u03b1 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03c7\u03b1\u03bb\u03ac\u03b5\u03b9 \u03ba\u03b1\u03b9 \u03b7 \u03b5\u03c5\u03b8\u03c5\u03b3\u03c1\u03ac\u03bc\u03bc\u03b9\u03c3\u03b7 \u03ba\u03b5\u03b9\u03bc\u03ad\u03bd\u03bf\u03c5 \u03ba\u03b1\u03b9 \u03b5\u03b9\u03ba\u03cc\u03bd\u03b1\u03c2.<\/p>\n<p>\u0397 \u03b5\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03b7\u03bc\u03b1\u03c4\u03b9\u03ba\u03ae \u03c3\u03c5\u03bd\u03ad\u03c0\u03b5\u03b9\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03bf\u03c5\u03c3\u03b9\u03b1\u03c3\u03c4\u03b9\u03ba\u03ae. \u0388\u03bd\u03b1 chatbot \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03c3\u03c5\u03bd\u03b5\u03c7\u03af\u03c3\u03b5\u03b9 \u03bd\u03b1 \u03b1\u03c0\u03b1\u03bd\u03c4\u03ac \u03c3\u03c9\u03c3\u03c4\u03ac \u03c3\u03c4\u03b1 \u03c3\u03c5\u03c7\u03bd\u03cc\u03c4\u03b5\u03c1\u03b1 \u03b5\u03c1\u03c9\u03c4\u03ae\u03bc\u03b1\u03c4\u03b1, \u03b1\u03bb\u03bb\u03ac \u03bd\u03b1 \u03b1\u03c0\u03bf\u03c4\u03c5\u03b3\u03c7\u03ac\u03bd\u03b5\u03b9 \u03c3\u03b5 \u03b3\u03bb\u03c9\u03c3\u03c3\u03b9\u03ba\u03ad\u03c2 \u03c0\u03b1\u03c1\u03b1\u03bb\u03bb\u03b1\u03b3\u03ad\u03c2 \u03ae \u03b5\u03b9\u03b4\u03b9\u03ba\u03ad\u03c2 \u03b5\u03be\u03b1\u03b9\u03c1\u03ad\u03c3\u03b5\u03b9\u03c2. \u0388\u03bd\u03b1 \u03c3\u03cd\u03c3\u03c4\u03b7\u03bc\u03b1 product content \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03c0\u03b1\u03c1\u03ac\u03b3\u03b5\u03b9 \u03bf\u03bc\u03bf\u03b9\u03cc\u03bc\u03bf\u03c1\u03c6\u03b5\u03c2 \u03c0\u03b5\u03c1\u03b9\u03b3\u03c1\u03b1\u03c6\u03ad\u03c2 \u03c0\u03bf\u03c5 \u03b1\u03ba\u03bf\u03cd\u03b3\u03bf\u03bd\u03c4\u03b1\u03b9 \u03c3\u03c9\u03c3\u03c4\u03ad\u03c2, \u03b1\u03bb\u03bb\u03ac \u03c7\u03ac\u03bd\u03bf\u03c5\u03bd \u03c4\u03b1 \u03b9\u03b4\u03b9\u03b1\u03af\u03c4\u03b5\u03c1\u03b1 \u03b3\u03bd\u03c9\u03c1\u03af\u03c3\u03bc\u03b1\u03c4\u03b1 \u03bc\u03b9\u03ba\u03c1\u03ce\u03bd \u03ba\u03b1\u03c4\u03b7\u03b3\u03bf\u03c1\u03b9\u03ce\u03bd. \u0397 \u03bc\u03ad\u03c3\u03b7 \u03c0\u03bf\u03b9\u03cc\u03c4\u03b7\u03c4\u03b1 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03ba\u03c1\u03cd\u03b2\u03b5\u03b9 \u03c4\u03b7\u03bd \u03c5\u03c0\u03bf\u03c7\u03ce\u03c1\u03b7\u03c3\u03b7 \u03c4\u03b7\u03c2 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ae\u03c2 \u03ba\u03ac\u03bb\u03c5\u03c8\u03b7\u03c2.<\/p>\n<h2 id=\"diafores-collapse\">\u03a4\u03b9 \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 model collapse<\/h2>\n<p>\u0397 \u03bf\u03c1\u03bf\u03bb\u03bf\u03b3\u03af\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b5\u03cd\u03ba\u03bf\u03bb\u03bf \u03bd\u03b1 \u03bc\u03c0\u03b5\u03c1\u03b4\u03b5\u03c5\u03c4\u03b5\u03af. \u03a4\u03bf catastrophic forgetting \u03b1\u03c6\u03bf\u03c1\u03ac \u03ba\u03c5\u03c1\u03af\u03c9\u03c2 \u03c4\u03b7 \u03b4\u03b9\u03b1\u03b4\u03bf\u03c7\u03b9\u03ba\u03ae \u03b5\u03ba\u03bc\u03ac\u03b8\u03b7\u03c3\u03b7 \u03b5\u03c1\u03b3\u03b1\u03c3\u03b9\u03ce\u03bd, \u03cc\u03c0\u03bf\u03c5 \u03ad\u03bd\u03b1 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03c7\u03ac\u03bd\u03b5\u03b9 \u03c0\u03b1\u03bb\u03b9\u03cc\u03c4\u03b5\u03c1\u03b5\u03c2 \u03b3\u03bd\u03ce\u03c3\u03b5\u03b9\u03c2 \u03cc\u03c4\u03b1\u03bd \u03b5\u03ba\u03c0\u03b1\u03b9\u03b4\u03b5\u03cd\u03b5\u03c4\u03b1\u03b9 \u03c3\u03b5 \u03bd\u03ad\u03b5\u03c2. \u03a4\u03bf model collapse \u03b1\u03c6\u03bf\u03c1\u03ac \u03c4\u03b7 \u03bc\u03b5\u03c4\u03b1\u03c4\u03cc\u03c0\u03b9\u03c3\u03b7 \u03c0\u03bf\u03c5 \u03c0\u03c1\u03bf\u03ba\u03b1\u03bb\u03b5\u03af\u03c4\u03b1\u03b9 \u03cc\u03c4\u03b1\u03bd \u03c3\u03c5\u03bd\u03b8\u03b5\u03c4\u03b9\u03ba\u03ac outputs \u03b5\u03c0\u03b9\u03c3\u03c4\u03c1\u03ad\u03c6\u03bf\u03c5\u03bd \u03b1\u03bd\u03b1\u03b4\u03c1\u03bf\u03bc\u03b9\u03ba\u03ac \u03c9\u03c2 training data.<\/p>\n<p>\u03a4\u03bf neural collapse \u03b5\u03af\u03bd\u03b1\u03b9 \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03cc \u03c6\u03b1\u03b9\u03bd\u03cc\u03bc\u03b5\u03bd\u03bf \u03b1\u03c0\u03cc \u03c4\u03b7 \u03b3\u03b5\u03c9\u03bc\u03b5\u03c4\u03c1\u03af\u03b1 \u03c4\u03c9\u03bd \u03b1\u03bd\u03b1\u03c0\u03b1\u03c1\u03b1\u03c3\u03c4\u03ac\u03c3\u03b5\u03c9\u03bd \u03c3\u03c4\u03bf \u03c4\u03b5\u03bb\u03b9\u03ba\u03cc \u03c3\u03c4\u03ac\u03b4\u03b9\u03bf \u03b5\u03ba\u03c0\u03b1\u03af\u03b4\u03b5\u03c5\u03c3\u03b7\u03c2 \u03c4\u03b1\u03be\u03b9\u03bd\u03bf\u03bc\u03b7\u03c4\u03ce\u03bd \u03ba\u03b1\u03b9 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03c3\u03c5\u03bd\u03b4\u03ad\u03b5\u03c4\u03b1\u03b9 \u03bc\u03b5 \u03ba\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03b7 \u03b3\u03b5\u03bd\u03af\u03ba\u03b5\u03c5\u03c3\u03b7. \u03a4\u03bf data poisoning \u03c0\u03c1\u03bf\u03cb\u03c0\u03bf\u03b8\u03ad\u03c4\u03b5\u03b9 \u03ba\u03b1\u03ba\u03cc\u03b2\u03bf\u03c5\u03bb\u03b7 \u03c0\u03b1\u03c1\u03ad\u03bc\u03b2\u03b1\u03c3\u03b7 \u03c3\u03b5 \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03b1, \u03b5\u03bd\u03ce \u03c4\u03bf model collapse \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03c0\u03c1\u03bf\u03ba\u03cd\u03c8\u03b5\u03b9 \u03c7\u03c9\u03c1\u03af\u03c2 \u03b1\u03bd\u03c4\u03af\u03c0\u03b1\u03bb\u03bf, \u03bc\u03cc\u03bd\u03bf \u03b1\u03c0\u03cc \u03c6\u03c5\u03c3\u03b9\u03ba\u03ae \u03c3\u03c5\u03c3\u03c3\u03ce\u03c1\u03b5\u03c5\u03c3\u03b7 \u03c3\u03c6\u03b1\u03bb\u03bc\u03ac\u03c4\u03c9\u03bd \u03ba\u03b1\u03b9 \u03c3\u03c4\u03b5\u03bd\u03cc\u03c4\u03b5\u03c1\u03c9\u03bd \u03b4\u03b5\u03b9\u03b3\u03bc\u03ac\u03c4\u03c9\u03bd.<\/p>\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\">Model collapse<\/p>\n<p>\u0391\u03bd\u03b1\u03b4\u03c1\u03bf\u03bc\u03b9\u03ba\u03ae \u03b5\u03ba\u03c0\u03b1\u03af\u03b4\u03b5\u03c5\u03c3\u03b7 \u03c3\u03b5 \u03c3\u03c5\u03bd\u03b8\u03b5\u03c4\u03b9\u03ba\u03ac \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03b1 \u03c3\u03c4\u03b5\u03bd\u03b5\u03cd\u03b5\u03b9 \u03c4\u03b7\u03bd \u03ba\u03b1\u03c4\u03b1\u03bd\u03bf\u03bc\u03ae \u03ba\u03b1\u03b9 \u03b1\u03c6\u03b1\u03b9\u03c1\u03b5\u03af rare cases \u03c3\u03b5 \u03c0\u03bf\u03bb\u03bb\u03bf\u03cd\u03c2 \u03b3\u03cd\u03c1\u03bf\u03c5\u03c2.<\/p>\n<div class=\"td-badge-row\"><span class=\"td-badge\">Feedback loop<\/span><span class=\"td-badge\">Tail loss<\/span><\/div>\n<\/div>\n<div class=\"td-platform-card td-platform-card--navy\">\n<p class=\"td-comparison-title\">Catastrophic forgetting<\/p>\n<p>\u039d\u03ad\u03b1 tasks \u03ae \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03b1 \u03c0\u03b1\u03c1\u03b5\u03bc\u03b2\u03b1\u03af\u03bd\u03bf\u03c5\u03bd \u03c3\u03b5 \u03c0\u03b1\u03bb\u03b9\u03cc\u03c4\u03b5\u03c1\u03b5\u03c2 \u03b3\u03bd\u03ce\u03c3\u03b5\u03b9\u03c2 \u03bc\u03ad\u03c3\u03b1 \u03c3\u03b5 \u03b4\u03b9\u03b1\u03b4\u03bf\u03c7\u03b9\u03ba\u03ae \u03bc\u03ac\u03b8\u03b7\u03c3\u03b7, \u03c7\u03c9\u03c1\u03af\u03c2 \u03bd\u03b1 \u03b1\u03c0\u03b1\u03b9\u03c4\u03b5\u03af\u03c4\u03b1\u03b9 \u03c3\u03c5\u03bd\u03b8\u03b5\u03c4\u03b9\u03ba\u03cc\u03c2 \u03b2\u03c1\u03cc\u03c7\u03bf\u03c2.<\/p>\n<div class=\"td-badge-row\"><span class=\"td-badge\">Task interference<\/span><span class=\"td-badge\">Continual learning<\/span><\/div>\n<\/div>\n<div class=\"td-platform-card\">\n<p class=\"td-comparison-title\">Data poisoning<\/p>\n<p>\u0388\u03bd\u03b1\u03c2 \u03b1\u03bd\u03c4\u03af\u03c0\u03b1\u03bb\u03bf\u03c2 \u03b5\u03b9\u03c3\u03ac\u03b3\u03b5\u03b9 \u03c3\u03ba\u03cc\u03c0\u03b9\u03bc\u03b1 \u03b5\u03c0\u03b9\u03b2\u03bb\u03b1\u03b2\u03ae training samples \u03ae backdoors \u03b3\u03b9\u03b1 \u03bd\u03b1 \u03b1\u03bb\u03bb\u03bf\u03b9\u03ce\u03c3\u03b5\u03b9 \u03c4\u03b7 \u03c3\u03c5\u03bc\u03c0\u03b5\u03c1\u03b9\u03c6\u03bf\u03c1\u03ac \u03c4\u03bf\u03c5 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf\u03c5.<\/p>\n<div class=\"td-badge-row\"><span class=\"td-badge\">Adversarial<\/span><span class=\"td-badge\">Malicious samples<\/span><\/div>\n<\/div>\n<\/div>\n<\/div>\n<p>\u0397 subliminal learning \u03b5\u03af\u03bd\u03b1\u03b9 \u03b1\u03ba\u03cc\u03bc\u03b7 \u03bc\u03af\u03b1 \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03ae \u03c0\u03b5\u03c1\u03af\u03c0\u03c4\u03c9\u03c3\u03b7: \u03c3\u03c5\u03bc\u03c0\u03b5\u03c1\u03b9\u03c6\u03bf\u03c1\u03b9\u03ba\u03ac \u03c7\u03b1\u03c1\u03b1\u03ba\u03c4\u03b7\u03c1\u03b9\u03c3\u03c4\u03b9\u03ba\u03ac \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03bc\u03b5\u03c4\u03b1\u03c6\u03b5\u03c1\u03b8\u03bf\u03cd\u03bd \u03b1\u03c0\u03cc teacher \u03c3\u03b5 student \u03bc\u03ad\u03c3\u03c9 \u03c6\u03b1\u03b9\u03bd\u03bf\u03bc\u03b5\u03bd\u03b9\u03ba\u03ac \u03ac\u03c3\u03c7\u03b5\u03c4\u03c9\u03bd \u03c3\u03c5\u03bd\u03b8\u03b5\u03c4\u03b9\u03ba\u03ce\u03bd \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd, \u03c7\u03c9\u03c1\u03af\u03c2 \u03bd\u03b1 \u03c3\u03c5\u03bd\u03b5\u03c0\u03ac\u03b3\u03b5\u03c4\u03b1\u03b9 \u03b1\u03bd\u03b1\u03b3\u03ba\u03b1\u03c3\u03c4\u03b9\u03ba\u03ac \u03c3\u03c5\u03bd\u03bf\u03bb\u03b9\u03ba\u03ae \u03c0\u03c4\u03ce\u03c3\u03b7 \u03b5\u03c0\u03af\u03b4\u03bf\u03c3\u03b7\u03c2. \u039f\u03b9 \u03b4\u03b9\u03b1\u03ba\u03c1\u03af\u03c3\u03b5\u03b9\u03c2 \u03ad\u03c7\u03bf\u03c5\u03bd \u03c0\u03c1\u03b1\u03ba\u03c4\u03b9\u03ba\u03ae \u03b1\u03be\u03af\u03b1, \u03b5\u03c0\u03b5\u03b9\u03b4\u03ae \u03ba\u03ac\u03b8\u03b5 \u03c0\u03c1\u03cc\u03b2\u03bb\u03b7\u03bc\u03b1 \u03b1\u03c0\u03b1\u03b9\u03c4\u03b5\u03af \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03ac \u03b4\u03b9\u03b1\u03b3\u03bd\u03c9\u03c3\u03c4\u03b9\u03ba\u03ac \u03ba\u03b1\u03b9 \u03b1\u03bd\u03c4\u03af\u03bc\u03b5\u03c4\u03c1\u03b1.<\/p>\n<h2 id=\"llm-decoding\">\u03a0\u03ce\u03c2 \u03c4\u03bf \u03c3\u03c5\u03bd\u03c4\u03b7\u03c1\u03b7\u03c4\u03b9\u03ba\u03cc decoding \u03ba\u03cc\u03b2\u03b5\u03b9 \u03c4\u03b7\u03bd \u03bf\u03c5\u03c1\u03ac<\/h2>\n<p>\u0397 \u03c3\u03c5\u03bd\u03b8\u03b5\u03c4\u03b9\u03ba\u03ae \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae \u03b4\u03b5\u03bd \u03ba\u03b1\u03b8\u03bf\u03c1\u03af\u03b6\u03b5\u03c4\u03b1\u03b9 \u03bc\u03cc\u03bd\u03bf \u03b1\u03c0\u03cc \u03c4\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03b1\u03bb\u03bb\u03ac \u03ba\u03b1\u03b9 \u03b1\u03c0\u03cc \u03c4\u03b9\u03c2 \u03c1\u03c5\u03b8\u03bc\u03af\u03c3\u03b5\u03b9\u03c2 sampling. \u03a7\u03b1\u03bc\u03b7\u03bb\u03ae temperature, \u03c0\u03bf\u03bb\u03cd \u03bc\u03b9\u03ba\u03c1\u03cc top-p \u03ae top-k \u03ba\u03b1\u03b9 \u03c0\u03b5\u03c1\u03b9\u03bf\u03c1\u03b9\u03c3\u03bc\u03ad\u03bd\u03bf\u03c2 \u03b1\u03c1\u03b9\u03b8\u03bc\u03cc\u03c2 \u03c5\u03c0\u03bf\u03c8\u03b7\u03c6\u03af\u03c9\u03bd \u03b1\u03c6\u03b1\u03b9\u03c1\u03bf\u03cd\u03bd \u03c3\u03c0\u03ac\u03bd\u03b9\u03b5\u03c2 \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ad\u03c2 \u03c0\u03c1\u03b9\u03bd \u03c4\u03bf \u03c5\u03bb\u03b9\u03ba\u03cc \u03c6\u03c4\u03ac\u03c3\u03b5\u03b9 \u03c3\u03c4\u03bf training set. \u038c\u03c4\u03b1\u03bd \u03b1\u03c5\u03c4\u03ae \u03b7 \u03c0\u03b5\u03c1\u03b9\u03ba\u03bf\u03bc\u03bc\u03ad\u03bd\u03b7 \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03b7\u03b8\u03b5\u03af \u03be\u03b1\u03bd\u03ac \u03b3\u03b9\u03b1 \u03b5\u03ba\u03c0\u03b1\u03af\u03b4\u03b5\u03c5\u03c3\u03b7, \u03b7 \u03b5\u03c0\u03cc\u03bc\u03b5\u03bd\u03b7 \u03b3\u03b5\u03bd\u03b9\u03ac \u03ad\u03c7\u03b5\u03b9 \u03b1\u03ba\u03cc\u03bc\u03b7 \u03bb\u03b9\u03b3\u03cc\u03c4\u03b5\u03c1\u03b5\u03c2 \u03c0\u03b9\u03b8\u03b1\u03bd\u03cc\u03c4\u03b7\u03c4\u03b5\u03c2 \u03bd\u03b1 \u03b1\u03bd\u03b1\u03c0\u03b1\u03c1\u03b1\u03c3\u03c4\u03ae\u03c3\u03b5\u03b9 \u03c4\u03b7\u03bd \u03bf\u03c5\u03c1\u03ac.<\/p>\n<p>\u0391\u03c5\u03c4\u03cc \u03b4\u03b7\u03bc\u03b9\u03bf\u03c5\u03c1\u03b3\u03b5\u03af \u03ad\u03bd\u03b1 \u03c0\u03b1\u03c1\u03ac\u03b4\u03bf\u03be\u03bf \u03b3\u03b9\u03b1 production teams. \u039f\u03b9 \u03c3\u03c5\u03bd\u03c4\u03b7\u03c1\u03b7\u03c4\u03b9\u03ba\u03ad\u03c2 \u03c1\u03c5\u03b8\u03bc\u03af\u03c3\u03b5\u03b9\u03c2 \u03ba\u03ac\u03bd\u03bf\u03c5\u03bd \u03c4\u03b9\u03c2 \u03b1\u03c0\u03b1\u03bd\u03c4\u03ae\u03c3\u03b5\u03b9\u03c2 \u03c0\u03b9\u03bf \u03c0\u03c1\u03bf\u03b2\u03bb\u03ad\u03c8\u03b9\u03bc\u03b5\u03c2 \u03ba\u03b1\u03b9 \u03c3\u03c5\u03c7\u03bd\u03ac \u03b2\u03b5\u03bb\u03c4\u03b9\u03ce\u03bd\u03bf\u03c5\u03bd \u03c4\u03b7\u03bd \u03b5\u03c0\u03b9\u03c6\u03b1\u03bd\u03b5\u03b9\u03b1\u03ba\u03ae \u03c3\u03c5\u03bd\u03ad\u03c0\u03b5\u03b9\u03b1. \u0391\u03bd \u03cc\u03bc\u03c9\u03c2 \u03c4\u03b1 \u03af\u03b4\u03b9\u03b1 outputs \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03bf\u03cd\u03bd\u03c4\u03b1\u03b9 \u03b3\u03b9\u03b1 fine-tuning, distillation \u03ae \u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7 \u03c7\u03c9\u03c1\u03af\u03c2 \u03b1\u03bd\u03c4\u03b9\u03c3\u03c4\u03ac\u03b8\u03bc\u03b9\u03c3\u03b7, \u03b7 \u03c0\u03c1\u03bf\u03b2\u03bb\u03b5\u03c8\u03b9\u03bc\u03cc\u03c4\u03b7\u03c4\u03b1 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03bc\u03b5\u03c4\u03b1\u03c4\u03c1\u03b1\u03c0\u03b5\u03af \u03c3\u03b5 \u03b1\u03c0\u03ce\u03bb\u03b5\u03b9\u03b1 \u03c0\u03bf\u03b9\u03ba\u03b9\u03bb\u03af\u03b1\u03c2. \u0394\u03b5\u03bd \u03b1\u03c1\u03ba\u03b5\u03af \u03bd\u03b1 \u03b5\u03bb\u03ad\u03b3\u03c7\u03b5\u03c4\u03b1\u03b9 \u03b1\u03bd \u03ba\u03ac\u03b8\u03b5 sample \u03b5\u03af\u03bd\u03b1\u03b9 \u03ba\u03b1\u03bb\u03bf\u03b3\u03c1\u03b1\u03bc\u03bc\u03ad\u03bd\u03bf\u00b7 \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03bd\u03b1 \u03b5\u03bb\u03ad\u03b3\u03c7\u03b5\u03c4\u03b1\u03b9 \u03b1\u03bd \u03c4\u03bf corpus \u03b4\u03b9\u03b1\u03c4\u03b7\u03c1\u03b5\u03af \u03b5\u03cd\u03c1\u03bf\u03c2.<\/p>\n<aside class=\"td-article-note\"><strong>\u0397 \u03c0\u03bf\u03b9\u03cc\u03c4\u03b7\u03c4\u03b1 \u03b5\u03bd\u03cc\u03c2 sample \u03b4\u03b5\u03bd \u03b1\u03c0\u03bf\u03b4\u03b5\u03b9\u03ba\u03bd\u03cd\u03b5\u03b9 \u03ba\u03ac\u03bb\u03c5\u03c8\u03b7:<\/strong> \u03c7\u03af\u03bb\u03b9\u03b5\u03c2 \u03ac\u03c1\u03c4\u03b9\u03b5\u03c2 \u03b1\u03c0\u03b1\u03bd\u03c4\u03ae\u03c3\u03b5\u03b9\u03c2 \u03bc\u03c0\u03bf\u03c1\u03bf\u03cd\u03bd \u03bd\u03b1 \u03b1\u03bd\u03b1\u03ba\u03c5\u03ba\u03bb\u03ce\u03bd\u03bf\u03c5\u03bd \u03c4\u03bf \u03af\u03b4\u03b9\u03bf \u03c3\u03c4\u03b5\u03bd\u03cc \u03bc\u03bf\u03c4\u03af\u03b2\u03bf. \u03a4\u03bf QA \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03bc\u03b5\u03c4\u03c1\u03ac \u03ba\u03b1\u03b9 \u03c4\u03b9\u03c2 \u03ba\u03b1\u03c4\u03b7\u03b3\u03bf\u03c1\u03af\u03b5\u03c2 \u03c0\u03bf\u03c5 \u03bb\u03b5\u03af\u03c0\u03bf\u03c5\u03bd, \u03cc\u03c7\u03b9 \u03bc\u03cc\u03bd\u03bf \u03cc\u03c3\u03b5\u03c2 \u03b5\u03bc\u03c6\u03b1\u03bd\u03af\u03b6\u03bf\u03bd\u03c4\u03b1\u03b9.<\/aside>\n<p>\u039f\u03b9 \u03c0\u03bb\u03ae\u03c1\u03c9\u03c2 \u03c3\u03c5\u03bd\u03b8\u03b5\u03c4\u03b9\u03ba\u03bf\u03af \u03ba\u03bb\u03b5\u03b9\u03c3\u03c4\u03bf\u03af \u03ba\u03cd\u03ba\u03bb\u03bf\u03b9 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b9\u03b4\u03b9\u03b1\u03af\u03c4\u03b5\u03c1\u03b1 \u03b5\u03c5\u03ac\u03bb\u03c9\u03c4\u03bf\u03b9. \u03a3\u03c4\u03b1 \u03bc\u03b9\u03ba\u03c4\u03ac datasets, \u03b7 \u03b1\u03c3\u03c6\u03b1\u03bb\u03ae\u03c2 \u03b1\u03bd\u03b1\u03bb\u03bf\u03b3\u03af\u03b1 \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03c3\u03c4\u03b1\u03b8\u03b5\u03c1\u03ac \u03c4\u03bf\u03c5 \u03ba\u03bb\u03ac\u03b4\u03bf\u03c5 \u03b1\u03bb\u03bb\u03ac task-dependent \u03bc\u03b5\u03c4\u03b1\u03b2\u03bb\u03b7\u03c4\u03ae \u03c0\u03bf\u03c5 \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03b5\u03c0\u03b9\u03ba\u03c5\u03c1\u03ce\u03bd\u03b5\u03c4\u03b1\u03b9 \u03b1\u03bd\u03ac \u03b5\u03c6\u03b1\u03c1\u03bc\u03bf\u03b3\u03ae. \u03a4\u03bf \u03af\u03b4\u03b9\u03bf \u03b9\u03c3\u03c7\u03cd\u03b5\u03b9 \u03b3\u03b9\u03b1 preference data: \u03ad\u03bd\u03b1\u03c2 <a href=\"https:\/\/twodots.gr\/dpo-preference-data-audit-llm\/\">\u03ad\u03bb\u03b5\u03b3\u03c7\u03bf\u03c2 \u03c0\u03c1\u03b9\u03bd \u03b1\u03c0\u03cc \u03c4\u03bf fine-tuning \u03b5\u03bd\u03cc\u03c2 LLM<\/a> \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03b5\u03be\u03b5\u03c4\u03ac\u03b6\u03b5\u03b9 \u03c0\u03bf\u03b9\u03bf\u03c2 \u03c0\u03b1\u03c1\u03ae\u03b3\u03b1\u03b3\u03b5, \u03c6\u03b9\u03bb\u03c4\u03c1\u03ac\u03c1\u03b9\u03c3\u03b5 \u03ba\u03b1\u03b9 \u03b5\u03bd\u03ad\u03ba\u03c1\u03b9\u03bd\u03b5 \u03ba\u03ac\u03b8\u03b5 \u03b6\u03b5\u03cd\u03b3\u03bf\u03c2.<\/p>\n<h2 id=\"multimodal-bias\">\u03a3\u03c4\u03b1 multimodal \u03c3\u03c5\u03c3\u03c4\u03ae\u03bc\u03b1\u03c4\u03b1 \u03c4\u03bf bias \u03c4\u03b1\u03be\u03b9\u03b4\u03b5\u03cd\u03b5\u03b9<\/h2>\n<p>\u03a3\u03c4\u03b1 VAEs, \u03b7 \u03b5\u03c0\u03b1\u03bd\u03b1\u03bb\u03b1\u03bc\u03b2\u03b1\u03bd\u03cc\u03bc\u03b5\u03bd\u03b7 \u03b5\u03ba\u03c0\u03b1\u03af\u03b4\u03b5\u03c5\u03c3\u03b7 \u03c3\u03b5 \u03af\u03b4\u03b9\u03b1 outputs \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03bc\u03b5\u03b9\u03ce\u03bd\u03b5\u03b9 \u03c4\u03b7 \u03b4\u03b9\u03b1\u03ba\u03cd\u03bc\u03b1\u03bd\u03c3\u03b7 \u03c4\u03bf\u03c5 latent space \u03ba\u03b1\u03b9 \u03bd\u03b1 \u03c3\u03c5\u03bc\u03c0\u03b9\u03ad\u03b6\u03b5\u03b9 \u03c0\u03bf\u03bb\u03bb\u03ad\u03c2 \u03ba\u03bf\u03c1\u03c5\u03c6\u03ad\u03c2 \u03c4\u03b7\u03c2 \u03b1\u03bd\u03b8\u03c1\u03ce\u03c0\u03b9\u03bd\u03b7\u03c2 \u03ba\u03b1\u03c4\u03b1\u03bd\u03bf\u03bc\u03ae\u03c2 \u03c3\u03b5 \u03bb\u03b9\u03b3\u03cc\u03c4\u03b5\u03c1\u03b5\u03c2. \u03a3\u03c4\u03b1 diffusion models, \u03b7 \u03b1\u03c0\u03bf\u03ba\u03bb\u03b5\u03b9\u03c3\u03c4\u03b9\u03ba\u03ae \u03b5\u03ba\u03c0\u03b1\u03af\u03b4\u03b5\u03c5\u03c3\u03b7 \u03bc\u03b5 \u03c3\u03c5\u03bd\u03b8\u03b5\u03c4\u03b9\u03ba\u03ad\u03c2 \u03b5\u03b9\u03ba\u03cc\u03bd\u03b5\u03c2 \u03c0\u03b5\u03c1\u03b9\u03bf\u03c1\u03af\u03b6\u03b5\u03b9 \u03c4\u03b7\u03bd \u03c0\u03bf\u03b9\u03ba\u03b9\u03bb\u03af\u03b1, \u03b5\u03bd\u03ce \u03b1\u03c0\u03bb\u03ac Gaussian \u03c0\u03b1\u03c1\u03b1\u03b4\u03b5\u03af\u03b3\u03bc\u03b1\u03c4\u03b1 \u03b4\u03b5\u03af\u03c7\u03bd\u03bf\u03c5\u03bd \u03c4\u03b7\u03bd covariance \u03bd\u03b1 \u03c4\u03b5\u03af\u03bd\u03b5\u03b9 \u03c0\u03c1\u03bf\u03c2 \u03c4\u03bf \u03bc\u03b7\u03b4\u03ad\u03bd. \u03a3\u03c4\u03b1 ReFlow \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03b1, \u03c4\u03b1 self-produced \u03b6\u03b5\u03cd\u03b3\u03b7 \u03b8\u03bf\u03c1\u03cd\u03b2\u03bf\u03c5 \u03ba\u03b1\u03b9 \u03b5\u03b9\u03ba\u03cc\u03bd\u03b1\u03c2 \u03bc\u03c0\u03bf\u03c1\u03bf\u03cd\u03bd \u03bd\u03b1 \u03bc\u03b5\u03c4\u03b1\u03c4\u03bf\u03c0\u03af\u03b6\u03bf\u03c5\u03bd \u03c4\u03bf velocity field \u03c7\u03c9\u03c1\u03af\u03c2 \u03b1\u03bd\u03b8\u03c1\u03ce\u03c0\u03b9\u03bd\u03bf anchor.<\/p>\n<p>\u03a3\u03b5 \u03ad\u03bd\u03b1 multimodal pipeline, captioner, visual encoder \u03ba\u03b1\u03b9 generator \u03b1\u03bb\u03bb\u03b7\u03bb\u03bf\u03b5\u03c0\u03b7\u03c1\u03b5\u03ac\u03b6\u03bf\u03bd\u03c4\u03b1\u03b9. \u0391\u03bd \u03bf captioner \u03b1\u03b3\u03bd\u03bf\u03b5\u03af \u03c3\u03c0\u03ac\u03bd\u03b9\u03b1 attributes, \u03bf generator \u03bc\u03b1\u03b8\u03b1\u03af\u03bd\u03b5\u03b9 \u03b1\u03c0\u03cc \u03c3\u03c4\u03b5\u03bd\u03cc\u03c4\u03b5\u03c1\u03b5\u03c2 \u03c0\u03b5\u03c1\u03b9\u03b3\u03c1\u03b1\u03c6\u03ad\u03c2. \u0391\u03bd \u03bf generator \u03c0\u03b1\u03c1\u03ac\u03b3\u03b5\u03b9 \u03ba\u03c5\u03c1\u03af\u03b1\u03c1\u03c7\u03b1 \u03c3\u03c4\u03b9\u03bb, \u03bf captioner \u03b5\u03ba\u03c0\u03b1\u03b9\u03b4\u03b5\u03cd\u03b5\u03c4\u03b1\u03b9 \u03c3\u03b5 \u03b1\u03ba\u03cc\u03bc\u03b7 \u03c0\u03b9\u03bf \u03bf\u03bc\u03bf\u03b9\u03cc\u03bc\u03bf\u03c1\u03c6\u03bf \u03bf\u03c0\u03c4\u03b9\u03ba\u03cc \u03ba\u03cc\u03c3\u03bc\u03bf. \u0397 \u03b8\u03b5\u03c4\u03b9\u03ba\u03ae \u03b1\u03bd\u03b1\u03c4\u03c1\u03bf\u03c6\u03bf\u03b4\u03cc\u03c4\u03b7\u03c3\u03b7 \u03bc\u03b5\u03c4\u03b1\u03c6\u03ad\u03c1\u03b5\u03b9 bias \u03b1\u03c0\u03cc modality \u03c3\u03b5 modality.<\/p>\n<p>\u0393\u03b9\u03b1 \u03bf\u03bc\u03ac\u03b4\u03b5\u03c2 marketing \u03ba\u03b1\u03b9 e-commerce, \u03b7 \u03c0\u03bf\u03b9\u03cc\u03c4\u03b7\u03c4\u03b1 \u03b4\u03b5\u03bd \u03b1\u03be\u03b9\u03bf\u03bb\u03bf\u03b3\u03b5\u03af\u03c4\u03b1\u03b9 \u03bc\u03cc\u03bd\u03bf \u03c3\u03c4\u03bf \u03ba\u03b5\u03af\u03bc\u03b5\u03bd\u03bf \u03ae \u03bc\u03cc\u03bd\u03bf \u03c3\u03c4\u03b7\u03bd \u03b5\u03b9\u03ba\u03cc\u03bd\u03b1. \u03a7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03ad\u03bb\u03b5\u03b3\u03c7\u03bf\u03c2 \u03c4\u03b7\u03c2 \u03bc\u03b5\u03c4\u03b1\u03be\u03cd \u03c4\u03bf\u03c5\u03c2 \u03c3\u03c5\u03bc\u03c6\u03c9\u03bd\u03af\u03b1\u03c2: \u03b1\u03bd \u03bf\u03b9 \u03bb\u03b5\u03b6\u03ac\u03bd\u03c4\u03b5\u03c2 \u03b4\u03b9\u03b1\u03c4\u03b7\u03c1\u03bf\u03cd\u03bd \u03c4\u03b9\u03c2 \u03ba\u03c1\u03af\u03c3\u03b9\u03bc\u03b5\u03c2 \u03b9\u03b4\u03b9\u03cc\u03c4\u03b7\u03c4\u03b5\u03c2 \u03c4\u03bf\u03c5 \u03c0\u03c1\u03bf\u03ca\u03cc\u03bd\u03c4\u03bf\u03c2, \u03b1\u03bd \u03bf\u03b9 \u03b5\u03b9\u03ba\u03cc\u03bd\u03b5\u03c2 \u03b1\u03bd\u03b1\u03c0\u03b1\u03c1\u03b9\u03c3\u03c4\u03bf\u03cd\u03bd \u03c3\u03c0\u03ac\u03bd\u03b9\u03b5\u03c2 \u03c0\u03b1\u03c1\u03b1\u03bb\u03bb\u03b1\u03b3\u03ad\u03c2 \u03ba\u03b1\u03b9 \u03b1\u03bd \u03c4\u03bf retrieval \u03b2\u03c1\u03af\u03c3\u03ba\u03b5\u03b9 \u03bc\u03b7 \u03ba\u03c5\u03c1\u03af\u03b1\u03c1\u03c7\u03b5\u03c2 \u03c0\u03b5\u03c1\u03b9\u03c0\u03c4\u03ce\u03c3\u03b5\u03b9\u03c2. \u0397 \u03b1\u03c3\u03c4\u03bf\u03c7\u03af\u03b1 \u03b5\u03bd\u03cc\u03c2 vision-language model \u03c3\u03c4\u03b7 <a href=\"https:\/\/twodots.gr\/statesight-vision-language-models-choriki-domi\/\">\u03c7\u03c9\u03c1\u03b9\u03ba\u03ae \u03b4\u03bf\u03bc\u03ae \u03bc\u03b9\u03b1\u03c2 \u03c3\u03ba\u03b7\u03bd\u03ae\u03c2<\/a> \u03b5\u03af\u03bd\u03b1\u03b9 \u03ba\u03b1\u03bb\u03cc \u03c0\u03b1\u03c1\u03ac\u03b4\u03b5\u03b9\u03b3\u03bc\u03b1 \u03c4\u03bf\u03c5 \u03b3\u03b9\u03b1\u03c4\u03af \u03b7 \u03c3\u03c5\u03bd\u03bf\u03bb\u03b9\u03ba\u03ae \u03b2\u03b1\u03b8\u03bc\u03bf\u03bb\u03bf\u03b3\u03af\u03b1 \u03b4\u03b5\u03bd \u03b1\u03c1\u03ba\u03b5\u03af.<\/p>\n<h2 id=\"anthropos-pyrinas\">\u039f \u03b1\u03bd\u03b8\u03c1\u03ce\u03c0\u03b9\u03bd\u03bf\u03c2 \u03c0\u03c5\u03c1\u03ae\u03bd\u03b1\u03c2 \u03b5\u03af\u03bd\u03b1\u03b9 anchor<\/h2>\n<p>\u03a4\u03bf \u03c0\u03b9\u03bf \u03c3\u03c5\u03bd\u03b5\u03c0\u03ad\u03c2 \u03b1\u03bd\u03c4\u03af\u03bc\u03b5\u03c4\u03c1\u03bf \u03c3\u03c4\u03b7 \u03b2\u03b9\u03b2\u03bb\u03b9\u03bf\u03b3\u03c1\u03b1\u03c6\u03af\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03bd\u03b1 \u03b4\u03b9\u03b1\u03c4\u03b7\u03c1\u03b5\u03af\u03c4\u03b1\u03b9 \u03ad\u03bd\u03b1 \u03b5\u03c0\u03af\u03bc\u03bf\u03bd\u03bf \u03c3\u03cd\u03bd\u03bf\u03bb\u03bf \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ce\u03bd \u03b1\u03bd\u03b8\u03c1\u03ce\u03c0\u03b9\u03bd\u03c9\u03bd \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd \u03c3\u03b5 \u03ba\u03ac\u03b8\u03b5 \u03b3\u03cd\u03c1\u03bf. \u0397 \u03bb\u03bf\u03b3\u03b9\u03ba\u03ae \u03b5\u03af\u03bd\u03b1\u03b9 \u00abaccumulate, not replace\u00bb: \u03c4\u03b1 \u03bd\u03ad\u03b1 \u03c3\u03c5\u03bd\u03b8\u03b5\u03c4\u03b9\u03ba\u03ac \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03b1 \u03c0\u03c1\u03bf\u03c3\u03c4\u03af\u03b8\u03b5\u03bd\u03c4\u03b1\u03b9 \u03bc\u03b5 \u03ad\u03bb\u03b5\u03b3\u03c7\u03bf \u03ba\u03b1\u03b9 \u03b4\u03b5\u03bd \u03b5\u03ba\u03c4\u03bf\u03c0\u03af\u03b6\u03bf\u03c5\u03bd \u03c4\u03bf\u03bd \u03c0\u03c5\u03c1\u03ae\u03bd\u03b1 \u03b1\u03bd\u03b1\u03c6\u03bf\u03c1\u03ac\u03c2. \u039c\u03b5\u03bb\u03ad\u03c4\u03b5\u03c2 \u03c3\u03b5 \u03b3\u03bb\u03c9\u03c3\u03c3\u03b9\u03ba\u03ac \u03ba\u03b1\u03b9 \u03ac\u03bb\u03bb\u03b1 generative models \u03b4\u03b5\u03af\u03c7\u03bd\u03bf\u03c5\u03bd \u03cc\u03c4\u03b9 \u03b7 \u03c3\u03c5\u03c3\u03c3\u03ce\u03c1\u03b5\u03c5\u03c3\u03b7 \u03bc\u03b1\u03b6\u03af \u03bc\u03b5 \u03c4\u03b1 \u03b1\u03c1\u03c7\u03b9\u03ba\u03ac \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ac \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03b1 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b1\u03c0\u03bf\u03c4\u03c1\u03ad\u03c8\u03b5\u03b9 \u03c4\u03bf \u03b5\u03ba\u03c1\u03b7\u03ba\u03c4\u03b9\u03ba\u03cc \u03c3\u03c6\u03ac\u03bb\u03bc\u03b1 \u03c0\u03bf\u03c5 \u03b5\u03bc\u03c6\u03b1\u03bd\u03af\u03b6\u03b5\u03c4\u03b1\u03b9 \u03cc\u03c4\u03b1\u03bd \u03ba\u03ac\u03b8\u03b5 \u03b3\u03b5\u03bd\u03b9\u03ac \u03b1\u03bd\u03c4\u03b9\u03ba\u03b1\u03b8\u03b9\u03c3\u03c4\u03ac \u03c4\u03b7\u03bd \u03c0\u03c1\u03bf\u03b7\u03b3\u03bf\u03cd\u03bc\u03b5\u03bd\u03b7.<\/p>\n<p>\u0399\u03c3\u03c7\u03c5\u03c1\u03ae \u03b1\u03c1\u03c7\u03b9\u03ba\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03c0\u03c1\u03bf\u03c3\u03b5\u03ba\u03c4\u03b9\u03ba\u03cc schedule \u03ad\u03c7\u03bf\u03c5\u03bd \u03b5\u03c0\u03af\u03c3\u03b7\u03c2 \u03c3\u03b7\u03bc\u03b1\u03c3\u03af\u03b1. \u0397 \u03b1\u03bd\u03b1\u03bb\u03bf\u03b3\u03af\u03b1 \u03c3\u03c5\u03bd\u03b8\u03b5\u03c4\u03b9\u03ba\u03ce\u03bd \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03be\u03b5\u03ba\u03b9\u03bd\u03ac \u03c7\u03b1\u03bc\u03b7\u03bb\u03ac \u03ba\u03b1\u03b9 \u03bd\u03b1 \u03b1\u03c5\u03be\u03ac\u03bd\u03b5\u03c4\u03b1\u03b9 \u03bc\u03cc\u03bd\u03bf \u03b5\u03c6\u03cc\u03c3\u03bf\u03bd \u03bf\u03b9 \u03b4\u03b5\u03af\u03ba\u03c4\u03b5\u03c2 \u03bf\u03c5\u03c1\u03ac\u03c2, \u03c0\u03bf\u03b9\u03ba\u03b9\u03bb\u03af\u03b1\u03c2 \u03ba\u03b1\u03b9 learning curve \u03c0\u03b1\u03c1\u03b1\u03bc\u03ad\u03bd\u03bf\u03c5\u03bd \u03c5\u03b3\u03b9\u03b5\u03af\u03c2. \u03a3\u03b5 coupled pipelines, \u03b7 \u03b4\u03b9\u03b1\u03c4\u03ae\u03c1\u03b7\u03c3\u03b7 \u03b5\u03bd\u03cc\u03c2 \u03c0\u03b1\u03b3\u03c9\u03bc\u03ad\u03bd\u03bf\u03c5, \u03b5\u03ba\u03c0\u03b1\u03b9\u03b4\u03b5\u03c5\u03bc\u03ad\u03bd\u03bf\u03c5 \u03c3\u03b5 \u03b1\u03bd\u03b8\u03c1\u03ce\u03c0\u03b9\u03bd\u03b1 \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03b1 component \u2014\u03b3\u03b9\u03b1 \u03c0\u03b1\u03c1\u03ac\u03b4\u03b5\u03b9\u03b3\u03bc\u03b1 captioner \u03ae encoder\u2014 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03c3\u03c0\u03ac\u03c3\u03b5\u03b9 \u03c4\u03b7\u03bd \u03b5\u03c0\u03b9\u03ba\u03af\u03bd\u03b4\u03c5\u03bd\u03b7 \u03b1\u03bd\u03b1\u03c4\u03c1\u03bf\u03c6\u03bf\u03b4\u03cc\u03c4\u03b7\u03c3\u03b7.<\/p>\n<p>\u0393\u03b9\u03b1 \u03bc\u03b9\u03b1 \u03b5\u03c4\u03b1\u03b9\u03c1\u03b5\u03af\u03b1, \u00ab\u03b1\u03bd\u03b8\u03c1\u03ce\u03c0\u03b9\u03bd\u03bf\u03c2 \u03c0\u03c5\u03c1\u03ae\u03bd\u03b1\u03c2\u00bb \u03b4\u03b5\u03bd \u03c3\u03b7\u03bc\u03b1\u03af\u03bd\u03b5\u03b9 \u03c4\u03c5\u03c7\u03b1\u03af\u03bf \u03bc\u03b9\u03ba\u03c1\u03cc sample. \u03a0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03c0\u03b5\u03c1\u03b9\u03bb\u03b1\u03bc\u03b2\u03ac\u03bd\u03b5\u03b9 \u03c4\u03b9\u03c2 \u03ba\u03b1\u03c4\u03b7\u03b3\u03bf\u03c1\u03af\u03b5\u03c2 \u03c5\u03c8\u03b7\u03bb\u03bf\u03cd \u03c1\u03af\u03c3\u03ba\u03bf\u03c5, \u03c4\u03b9\u03c2 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ad\u03c2 \u03b5\u03be\u03b1\u03b9\u03c1\u03ad\u03c3\u03b5\u03b9\u03c2, \u03b4\u03cd\u03c3\u03ba\u03bf\u03bb\u03b1 support cases, \u03c4\u03bf brand voice \u03ba\u03b1\u03b9 \u03c4\u03b9\u03c2 \u03c3\u03c0\u03ac\u03bd\u03b9\u03b5\u03c2 \u03b1\u03bb\u03bb\u03ac \u03ba\u03c1\u03af\u03c3\u03b9\u03bc\u03b5\u03c2 \u03c3\u03c5\u03bd\u03b1\u03bb\u03bb\u03b1\u03b3\u03ad\u03c2. \u0394\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03ac, \u03c4\u03bf anchor \u03c0\u03c1\u03bf\u03c3\u03c4\u03b1\u03c4\u03b5\u03cd\u03b5\u03b9 \u03bc\u03cc\u03bd\u03bf \u03c4\u03bf\u03bd \u03bc\u03ad\u03c3\u03bf \u03cc\u03c1\u03bf.<\/p>\n<h2 id=\"provenance\">Provenance: \u03c0\u03bf\u03b9\u03bf\u03c2 \u03c0\u03b1\u03c1\u03ae\u03b3\u03b1\u03b3\u03b5 \u03ba\u03ac\u03b8\u03b5 sample<\/h2>\n<p>\u0397 \u03c0\u03c1\u03bf\u03ad\u03bb\u03b5\u03c5\u03c3\u03b7 \u03c4\u03c9\u03bd \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03b9\u03ba\u03cc\u03c2 \u03bc\u03b7\u03c7\u03b1\u03bd\u03b9\u03c3\u03bc\u03cc\u03c2 \u03b1\u03c3\u03c6\u03ac\u03bb\u03b5\u03b9\u03b1\u03c2. \u0393\u03b9\u03b1 \u03ba\u03ac\u03b8\u03b5 \u03c3\u03c5\u03bd\u03b8\u03b5\u03c4\u03b9\u03ba\u03ae \u03c0\u03c1\u03bf\u03c3\u03b8\u03ae\u03ba\u03b7 \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03ba\u03b1\u03c4\u03b1\u03b3\u03c1\u03ac\u03c6\u03bf\u03bd\u03c4\u03b1\u03b9 \u03c4\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03ba\u03b1\u03b9 \u03c4\u03bf checkpoint, \u03bf\u03b9 \u03c1\u03c5\u03b8\u03bc\u03af\u03c3\u03b5\u03b9\u03c2 temperature\/top-p\/top-k, \u03bf candidate budget, \u03c4\u03b1 \u03c6\u03af\u03bb\u03c4\u03c1\u03b1, \u03b7 \u03b4\u03b9\u03b1\u03b4\u03b9\u03ba\u03b1\u03c3\u03af\u03b1 \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ae\u03c2 \u03ba\u03b1\u03b9 \u03b7 \u03b3\u03b5\u03bd\u03b5\u03b1\u03bb\u03bf\u03b3\u03af\u03b1 \u03c4\u03bf\u03c5 sample. \u0388\u03c4\u03c3\u03b9 \u03b7 \u03bf\u03bc\u03ac\u03b4\u03b1 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b5\u03bd\u03c4\u03bf\u03c0\u03af\u03c3\u03b5\u03b9 \u03c0\u03bf\u03b9\u03b1 \u03b1\u03bb\u03bb\u03b1\u03b3\u03ae \u03c0\u03b5\u03c1\u03b9\u03cc\u03c1\u03b9\u03c3\u03b5 \u03c4\u03b7\u03bd \u03bf\u03c5\u03c1\u03ac \u03ba\u03b1\u03b9 \u03bd\u03b1 \u03b5\u03c0\u03b9\u03c3\u03c4\u03c1\u03ad\u03c8\u03b5\u03b9 \u03c3\u03b5 \u03c3\u03c4\u03b1\u03b8\u03b5\u03c1\u03cc \u03c3\u03b7\u03bc\u03b5\u03af\u03bf.<\/p>\n<p>\u0397 \u03af\u03b4\u03b9\u03b1 \u03c0\u03c1\u03b1\u03ba\u03c4\u03b9\u03ba\u03ae \u03b1\u03c0\u03b1\u03bd\u03c4\u03ac \u03ba\u03b1\u03b9 \u03c3\u03b5 \u03bd\u03bf\u03bc\u03b9\u03ba\u03ac \u03ae licensing \u03b5\u03c1\u03c9\u03c4\u03ae\u03bc\u03b1\u03c4\u03b1. \u038c\u03c3\u03bf \u03c4\u03bf \u03c0\u03b1\u03c1\u03b1\u03b3\u03cc\u03bc\u03b5\u03bd\u03bf \u03c0\u03b5\u03c1\u03b9\u03b5\u03c7\u03cc\u03bc\u03b5\u03bd\u03bf \u03b5\u03c0\u03b9\u03c3\u03c4\u03c1\u03ad\u03c6\u03b5\u03b9 \u03c3\u03c4\u03bf\u03bd \u03b9\u03c3\u03c4\u03cc \u03ba\u03b1\u03b9 \u03be\u03b1\u03bd\u03b1\u03bc\u03c0\u03b1\u03af\u03bd\u03b5\u03b9 \u03c3\u03b5 crawls, \u03b3\u03af\u03bd\u03b5\u03c4\u03b1\u03b9 \u03b4\u03c5\u03c3\u03ba\u03bf\u03bb\u03cc\u03c4\u03b5\u03c1\u03bf \u03bd\u03b1 \u03b4\u03b9\u03b1\u03c7\u03c9\u03c1\u03b9\u03c3\u03c4\u03b5\u03af \u03c4\u03bf \u03c0\u03c1\u03c9\u03c4\u03bf\u03b3\u03b5\u03bd\u03ad\u03c2 \u03b1\u03c0\u03cc \u03c4\u03bf \u03c0\u03b1\u03c1\u03ac\u03b3\u03c9\u03b3\u03bf \u03c5\u03bb\u03b9\u03ba\u03cc. \u0397 \u03b1\u03bd\u03b1\u03c3\u03ba\u03cc\u03c0\u03b7\u03c3\u03b7 \u03b5\u03be\u03b5\u03c4\u03ac\u03b6\u03b5\u03b9 watermarks \u03c9\u03c2 \u03c0\u03b9\u03b8\u03b1\u03bd\u03cc \u03b5\u03c1\u03b3\u03b1\u03bb\u03b5\u03af\u03bf \u03b1\u03bd\u03b1\u03b3\u03bd\u03ce\u03c1\u03b9\u03c3\u03b7\u03c2 \u03c3\u03c5\u03bd\u03b8\u03b5\u03c4\u03b9\u03ba\u03ce\u03bd \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd, \u03c7\u03c9\u03c1\u03af\u03c2 \u03bd\u03b1 \u03c4\u03b1 \u03c0\u03b1\u03c1\u03bf\u03c5\u03c3\u03b9\u03ac\u03b6\u03b5\u03b9 \u03c9\u03c2 \u03c0\u03bb\u03ae\u03c1\u03b7 \u03bb\u03cd\u03c3\u03b7.<\/p>\n<p>\u0393\u03b9\u03b1 content operations, \u03b1\u03c5\u03c4\u03cc \u03bc\u03b5\u03c4\u03b1\u03c6\u03c1\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03c3\u03b5 dataset manifest \u03ba\u03b1\u03b9 versioning: \u03c0\u03b7\u03b3\u03ae, \u03ac\u03b4\u03b5\u03b9\u03b1, \u03b7\u03bc\u03b5\u03c1\u03bf\u03bc\u03b7\u03bd\u03af\u03b1, generator, prompt family, reviewer \u03ba\u03b1\u03b9 \u03c4\u03b5\u03bb\u03b9\u03ba\u03ae \u03b1\u03c0\u03cc\u03c6\u03b1\u03c3\u03b7. \u0391\u03bd \u03b4\u03b5\u03bd \u03bc\u03c0\u03bf\u03c1\u03b5\u03af\u03c2 \u03bd\u03b1 \u03b1\u03c0\u03b1\u03bd\u03c4\u03ae\u03c3\u03b5\u03b9\u03c2 \u03b1\u03c0\u03cc \u03c0\u03bf\u03cd \u03ae\u03c1\u03b8\u03b5 \u03ad\u03bd\u03b1 training example, \u03b4\u03cd\u03c3\u03ba\u03bf\u03bb\u03b1 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af\u03c2 \u03bd\u03b1 \u03b1\u03be\u03b9\u03bf\u03bb\u03bf\u03b3\u03ae\u03c3\u03b5\u03b9\u03c2 \u03c0\u03ce\u03c2 \u03b5\u03c0\u03b7\u03c1\u03b5\u03ac\u03b6\u03b5\u03b9 \u03c4\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf. \u0397 \u03bc\u03b5\u03c4\u03ac\u03b2\u03b1\u03c3\u03b7 <a href=\"https:\/\/twodots.gr\/data-silos-audit-trail-smart-manufacturing\/\">\u03b1\u03c0\u03cc data silos \u03c3\u03b5 audit trail<\/a> \u03b5\u03af\u03bd\u03b1\u03b9 \u03b5\u03be\u03af\u03c3\u03bf\u03c5 \u03ba\u03c1\u03af\u03c3\u03b9\u03bc\u03b7 \u03b5\u03b4\u03ce: \u03c4\u03bf lineage \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03bc\u03ad\u03c1\u03bf\u03c2 \u03c4\u03bf\u03c5 pipeline \u03ba\u03b1\u03b9 \u03cc\u03c7\u03b9 \u03bc\u03b5\u03c4\u03b1\u03b3\u03b5\u03bd\u03ad\u03c3\u03c4\u03b5\u03c1\u03bf spreadsheet.<\/p>\n<h2 id=\"metrikes-oura\">\u039c\u03b5\u03c4\u03c1\u03ae\u03c3\u03b5\u03b9\u03c2 \u03b3\u03b9\u03b1 \u03c4\u03b7\u03bd \u03bf\u03c5\u03c1\u03ac \u03ba\u03b1\u03b9 \u03cc\u03c7\u03b9 \u03bc\u03cc\u03bd\u03bf \u03c4\u03bf\u03bd \u03bc\u03ad\u03c3\u03bf \u03cc\u03c1\u03bf<\/h2>\n<p>\u039f \u03ba\u03af\u03bd\u03b4\u03c5\u03bd\u03bf\u03c2 \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03b1\u03bd\u03c4\u03b9\u03bc\u03b5\u03c4\u03c9\u03c0\u03af\u03b6\u03b5\u03c4\u03b1\u03b9 \u03cc\u03c0\u03c9\u03c2 \u03ad\u03bd\u03b1 reliability \u03c3\u03cd\u03c3\u03c4\u03b7\u03bc\u03b1. \u03a3\u03b5 \u03ba\u03ac\u03b8\u03b5 \u03b3\u03cd\u03c1\u03bf \u03c0\u03b1\u03c1\u03b1\u03ba\u03bf\u03bb\u03bf\u03c5\u03b8\u03bf\u03cd\u03bd\u03c4\u03b1\u03b9 tail coverage, diversity signals \u03ba\u03b1\u03b9 \u03b7 \u03ba\u03bb\u03af\u03c3\u03b7 \u03c4\u03c9\u03bd scaling curves. \u0393\u03b9\u03b1 \u03ba\u03b5\u03af\u03bc\u03b5\u03bd\u03bf, \u03c7\u03c1\u03ae\u03c3\u03b9\u03bc\u03b1 \u03c3\u03ae\u03bc\u03b1\u03c4\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b7 \u03b5\u03bd\u03c4\u03c1\u03bf\u03c0\u03af\u03b1 \u03ba\u03b1\u03b9 \u03c4\u03b1 distinct n-grams. \u0393\u03b9\u03b1 \u03b5\u03b9\u03ba\u03cc\u03bd\u03b5\u03c2, precision, recall, FID \u03ba\u03b1\u03b9 feature spread. \u0393\u03b9\u03b1 multimodal \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03b1, CLIP-style alignment, modality gap \u03ba\u03b1\u03b9 retrieval recall@k \u03bc\u03c0\u03bf\u03c1\u03bf\u03cd\u03bd \u03bd\u03b1 \u03b1\u03c0\u03bf\u03ba\u03b1\u03bb\u03cd\u03c8\u03bf\u03c5\u03bd \u03c3\u03c5\u03bc\u03c0\u03b9\u03b5\u03c3\u03bc\u03ad\u03bd\u03b5\u03c2 \u03b1\u03bd\u03b1\u03c0\u03b1\u03c1\u03b1\u03c3\u03c4\u03ac\u03c3\u03b5\u03b9\u03c2.<\/p>\n<p>\u0388\u03bd\u03b1 traffic-light \u03c3\u03cd\u03c3\u03c4\u03b7\u03bc\u03b1 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03c3\u03c5\u03bd\u03b4\u03ad\u03c3\u03b5\u03b9 \u03c4\u03b9\u03c2 \u03bc\u03b5\u03c4\u03c1\u03ae\u03c3\u03b5\u03b9\u03c2 \u03bc\u03b5 \u03b5\u03bd\u03ad\u03c1\u03b3\u03b5\u03b9\u03b5\u03c2. \u03a3\u03c4\u03bf amber \u03bc\u03b5\u03b9\u03ce\u03bd\u03b5\u03c4\u03b1\u03b9 \u03b7 \u03b1\u03bd\u03b1\u03bb\u03bf\u03b3\u03af\u03b1 \u03c3\u03c5\u03bd\u03b8\u03b5\u03c4\u03b9\u03ba\u03ce\u03bd \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd \u03ba\u03b1\u03b9 \u03c0\u03b1\u03b3\u03ce\u03bd\u03bf\u03c5\u03bd \u03bf\u03b9 \u03b5\u03c0\u03b9\u03b8\u03b5\u03c4\u03b9\u03ba\u03ad\u03c2 \u03b1\u03c5\u03be\u03ae\u03c3\u03b5\u03b9\u03c2 learning rate. \u03a3\u03c4\u03bf red \u03b1\u03c5\u03be\u03ac\u03bd\u03b5\u03c4\u03b1\u03b9 \u03b7 \u03c0\u03bf\u03b9\u03ba\u03b9\u03bb\u03af\u03b1 decoding, \u03b5\u03bd\u03b9\u03c3\u03c7\u03cd\u03b5\u03c4\u03b1\u03b9 \u03c4\u03bf \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03cc anchor \u03ba\u03b1\u03b9 \u03b3\u03af\u03bd\u03b5\u03c4\u03b1\u03b9 rollback \u03c3\u03c4\u03bf \u03c4\u03b5\u03bb\u03b5\u03c5\u03c4\u03b1\u03af\u03bf \u03c3\u03c4\u03b1\u03b8\u03b5\u03c1\u03cc checkpoint. \u03a4\u03b1 thresholds \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03c0\u03c1\u03bf\u03ba\u03cd\u03c0\u03c4\u03bf\u03c5\u03bd \u03b1\u03c0\u03cc baseline, z-scores \u03ae bootstrap intervals \u03c4\u03b7\u03c2 \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03b7\u03c2 \u03b5\u03c6\u03b1\u03c1\u03bc\u03bf\u03b3\u03ae\u03c2.<\/p>\n<div class=\"td-decision-band\">\n<p class=\"td-decision-kicker\">Production gate \u03b3\u03b9\u03b1 recursive training<\/p>\n<p class=\"td-decision-title\">\u03a4\u03bf synthetic ratio \u03b1\u03c5\u03be\u03ac\u03bd\u03b5\u03c4\u03b1\u03b9 \u03bc\u03cc\u03bd\u03bf \u03cc\u03c4\u03b1\u03bd \u03b7 \u03bf\u03c5\u03c1\u03ac \u03c0\u03b1\u03c1\u03b1\u03bc\u03ad\u03bd\u03b5\u03b9 \u03bc\u03b5\u03c4\u03c1\u03ae\u03c3\u03b9\u03bc\u03b1 \u03c5\u03b3\u03b9\u03ae\u03c2<\/p>\n<p>\u03a0\u03c1\u03bf\u03c7\u03c9\u03c1\u03ae\u03c3\u03c4\u03b5 \u03c3\u03b5 \u03bd\u03ad\u03bf \u03b3\u03cd\u03c1\u03bf \u03bc\u03cc\u03bd\u03bf \u03cc\u03c4\u03b1\u03bd \u03c4\u03bf human golden set \u03b5\u03af\u03bd\u03b1\u03b9 \u03b1\u03bc\u03b5\u03c4\u03ac\u03b2\u03bb\u03b7\u03c4\u03bf, \u03c4\u03b1 rare-case slices \u03c0\u03b5\u03c1\u03bd\u03bf\u03cd\u03bd \u03c4\u03b1 \u03c3\u03c5\u03bc\u03c6\u03c9\u03bd\u03b7\u03bc\u03ad\u03bd\u03b1 \u03cc\u03c1\u03b9\u03b1, \u03c4\u03bf dataset manifest \u03b5\u03af\u03bd\u03b1\u03b9 \u03c0\u03bb\u03ae\u03c1\u03b5\u03c2 \u03ba\u03b1\u03b9 \u03c5\u03c0\u03ac\u03c1\u03c7\u03b5\u03b9 \u03b4\u03bf\u03ba\u03b9\u03bc\u03b1\u03c3\u03bc\u03ad\u03bd\u03bf rollback. \u0391\u03bd \u03c0\u03ad\u03c3\u03b5\u03b9 tail coverage, entropy, image recall \u03ae cross-modal alignment, \u03c3\u03c4\u03b1\u03bc\u03b1\u03c4\u03ae\u03c3\u03c4\u03b5 \u03c4\u03b7\u03bd \u03b1\u03cd\u03be\u03b7\u03c3\u03b7 \u03c3\u03c5\u03bd\u03b8\u03b5\u03c4\u03b9\u03ba\u03ce\u03bd \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd \u03ba\u03b1\u03b9 \u03b5\u03c0\u03b9\u03c3\u03c4\u03c1\u03ad\u03c8\u03c4\u03b5 \u03c3\u03c4\u03b7\u03bd \u03c4\u03b5\u03bb\u03b5\u03c5\u03c4\u03b1\u03af\u03b1 \u03c3\u03c4\u03b1\u03b8\u03b5\u03c1\u03ae \u03ad\u03ba\u03b4\u03bf\u03c3\u03b7.<\/p>\n<\/div>\n<p>\u0397 \u03b5\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03b7\u03bc\u03b1\u03c4\u03b9\u03ba\u03ae \u03c0\u03b1\u03c1\u03b1\u03ba\u03bf\u03bb\u03bf\u03cd\u03b8\u03b7\u03c3\u03b7 \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03c0\u03c1\u03bf\u03c3\u03b8\u03ad\u03c3\u03b5\u03b9 slices \u03c0\u03bf\u03c5 \u03ad\u03c7\u03bf\u03c5\u03bd \u03bd\u03cc\u03b7\u03bc\u03b1: \u03b3\u03bb\u03ce\u03c3\u03c3\u03b1, \u03b1\u03b3\u03bf\u03c1\u03ac, product taxonomy, \u03c4\u03cd\u03c0\u03bf\u03c2 \u03c0\u03b5\u03bb\u03ac\u03c4\u03b7 \u03ba\u03b1\u03b9 severity. \u0391\u03bd \u03ad\u03bd\u03b1 \u03c3\u03c5\u03bd\u03bf\u03bb\u03b9\u03ba\u03cc score \u03bc\u03ad\u03bd\u03b5\u03b9 \u03c3\u03c4\u03b1\u03b8\u03b5\u03c1\u03cc \u03b5\u03bd\u03ce \u03b7 \u03b5\u03c0\u03af\u03b4\u03bf\u03c3\u03b7 \u03c3\u03b5 \u03c3\u03c0\u03ac\u03bd\u03b9\u03b5\u03c2 \u03b5\u03c0\u03b9\u03c3\u03c4\u03c1\u03bf\u03c6\u03ad\u03c2 \u03c0\u03c1\u03bf\u03ca\u03cc\u03bd\u03c4\u03c9\u03bd \u03ae \u03bc\u03b7 \u03c4\u03c5\u03c0\u03b9\u03ba\u03bf\u03cd\u03c2 \u03cc\u03c1\u03bf\u03c5\u03c2 \u03c3\u03c5\u03bc\u03b2\u03bf\u03bb\u03b1\u03af\u03c9\u03bd \u03c0\u03ad\u03c6\u03c4\u03b5\u03b9, \u03c4\u03bf dashboard \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03c4\u03bf \u03b4\u03b5\u03af\u03be\u03b5\u03b9. \u038c\u03c0\u03c9\u03c2 \u03ba\u03b1\u03b9 \u03c3\u03c4\u03b1 <a href=\"https:\/\/twodots.gr\/every-eval-ever-ai-benchmarks-diafaneia\/\">AI benchmarks \u03c0\u03bf\u03c5 \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03bf\u03bd\u03c4\u03b1\u03b9 \u03b4\u03b9\u03b1\u03c6\u03ac\u03bd\u03b5\u03b9\u03b1<\/a>, \u03b7 \u03bc\u03ad\u03c4\u03c1\u03b7\u03c3\u03b7 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c7\u03c1\u03ae\u03c3\u03b9\u03bc\u03b7 \u03bc\u03cc\u03bd\u03bf \u03cc\u03c4\u03b1\u03bd \u03b3\u03bd\u03c9\u03c1\u03af\u03b6\u03bf\u03c5\u03bc\u03b5 \u03c4\u03bf \u03c0\u03c1\u03c9\u03c4\u03cc\u03ba\u03bf\u03bb\u03bb\u03bf, \u03c4\u03b1 slices \u03ba\u03b1\u03b9 \u03c4\u03b1 \u03cc\u03c1\u03b9\u03ac \u03c4\u03b7\u03c2.<\/p>\n<h2 id=\"algorithmika-guardrails\">\u0391\u03bb\u03b3\u03bf\u03c1\u03b9\u03b8\u03bc\u03b9\u03ba\u03ac guardrails \u03bc\u03b5 \u03c3\u03b1\u03c6\u03ae \u03cc\u03c1\u03b9\u03b1<\/h2>\n<p>\u0397 \u03b1\u03bd\u03b1\u03c3\u03ba\u03cc\u03c0\u03b7\u03c3\u03b7 \u03c0\u03b1\u03c1\u03bf\u03c5\u03c3\u03b9\u03ac\u03b6\u03b5\u03b9 tail-aware weighting, \u03cc\u03c0\u03bf\u03c5 \u03c4\u03b1 \u03c3\u03c0\u03ac\u03bd\u03b9\u03b1 \u03b4\u03b5\u03af\u03b3\u03bc\u03b1\u03c4\u03b1 \u03bb\u03b1\u03bc\u03b2\u03ac\u03bd\u03bf\u03c5\u03bd \u03bc\u03b5\u03b3\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03bf \u03b2\u03ac\u03c1\u03bf\u03c2, \u03ba\u03b1\u03b9 entropy \u03ae diversity regularization, \u03c0\u03bf\u03c5 \u03b1\u03c0\u03bf\u03b8\u03b1\u03c1\u03c1\u03cd\u03bd\u03b5\u03b9 \u03c5\u03c0\u03b5\u03c1\u03b2\u03bf\u03bb\u03b9\u03ba\u03ac \u03b1\u03b9\u03c7\u03bc\u03b7\u03c1\u03ad\u03c2 \u03ae \u03b5\u03c0\u03b1\u03bd\u03b1\u03bb\u03b7\u03c0\u03c4\u03b9\u03ba\u03ad\u03c2 \u03b5\u03be\u03cc\u03b4\u03bf\u03c5\u03c2. \u03a0\u03c1\u03bf\u03c4\u03b5\u03af\u03bd\u03b5\u03b9 \u03b5\u03c0\u03af\u03c3\u03b7\u03c2 stability-aware scheduling \u03bc\u03b5 proxies \u03cc\u03c0\u03c9\u03c2 empirical Jacobian norms, Fisher blocks \u03ae sharpness measures, \u03ce\u03c3\u03c4\u03b5 \u03b7 \u03bc\u03ac\u03b8\u03b7\u03c3\u03b7 \u03bd\u03b1 \u03b5\u03c0\u03b9\u03b2\u03c1\u03b1\u03b4\u03cd\u03bd\u03b5\u03c4\u03b1\u03b9 \u03cc\u03c4\u03b1\u03bd \u03b7 \u03b4\u03c5\u03bd\u03b1\u03bc\u03b9\u03ba\u03ae \u03b3\u03af\u03bd\u03b5\u03c4\u03b1\u03b9 \u03b5\u03c0\u03b5\u03ba\u03c4\u03b1\u03c4\u03b9\u03ba\u03ae \u03b1\u03bd\u03c4\u03af \u03c3\u03c5\u03c3\u03c4\u03b1\u03bb\u03c4\u03b9\u03ba\u03ae.<\/p>\n<p>\u0391\u03c5\u03c4\u03ac \u03b5\u03af\u03bd\u03b1\u03b9 guardrails, \u03cc\u03c7\u03b9 \u03c5\u03c0\u03bf\u03ba\u03b1\u03c4\u03ac\u03c3\u03c4\u03b1\u03c4\u03b1 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ce\u03bd \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd. \u039c\u03c0\u03bf\u03c1\u03bf\u03cd\u03bd \u03bd\u03b1 \u03bc\u03b5\u03b9\u03ce\u03c3\u03bf\u03c5\u03bd \u03c4\u03b7\u03bd \u03c0\u03af\u03b5\u03c3\u03b7 \u03c0\u03c1\u03bf\u03c2 \u03bb\u03af\u03b3\u03b1 \u03ba\u03c5\u03c1\u03af\u03b1\u03c1\u03c7\u03b1 modes, \u03b1\u03bb\u03bb\u03ac \u03b4\u03b5\u03bd \u03b1\u03bd\u03b1\u03ba\u03b1\u03c4\u03b1\u03c3\u03ba\u03b5\u03c5\u03ac\u03b6\u03bf\u03c5\u03bd \u03b1\u03c0\u03cc \u03bc\u03cc\u03bd\u03b1 \u03c4\u03bf\u03c5\u03c2 \u03b1\u03bd\u03b8\u03c1\u03ce\u03c0\u03b9\u03bd\u03b5\u03c2 \u03c0\u03b5\u03c1\u03b9\u03c0\u03c4\u03ce\u03c3\u03b5\u03b9\u03c2 \u03c0\u03bf\u03c5 \u03ad\u03c7\u03bf\u03c5\u03bd \u03ae\u03b4\u03b7 \u03c7\u03b1\u03b8\u03b5\u03af. \u03a4\u03bf \u03af\u03b4\u03b9\u03bf \u03b9\u03c3\u03c7\u03cd\u03b5\u03b9 \u03b3\u03b9\u03b1 \u03b1\u03c5\u03be\u03b7\u03bc\u03ad\u03bd\u03b1 decoding budgets: \u03b2\u03bf\u03b7\u03b8\u03bf\u03cd\u03bd \u03bd\u03b1 \u03c0\u03b1\u03c1\u03b1\u03bc\u03b5\u03af\u03bd\u03bf\u03c5\u03bd \u03c0\u03b5\u03c1\u03b9\u03c3\u03c3\u03cc\u03c4\u03b5\u03c1\u03b5\u03c2 \u03c7\u03b1\u03bc\u03b7\u03bb\u03ae\u03c2 \u03c0\u03b9\u03b8\u03b1\u03bd\u03cc\u03c4\u03b7\u03c4\u03b1\u03c2 \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ad\u03c2 \u03c3\u03c4\u03bf corpus, \u03b1\u03bb\u03bb\u03ac \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03bf\u03bd\u03c4\u03b1\u03b9 \u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7 \u03c0\u03bf\u03b9\u03cc\u03c4\u03b7\u03c4\u03b1\u03c2 \u03ba\u03b1\u03b9 provenance.<\/p>\n<p>\u0397 \u03c3\u03c9\u03c3\u03c4\u03ae \u03b1\u03c0\u03cc\u03c6\u03b1\u03c3\u03b7 \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u00absynthetic \u03ae real\u00bb. \u0395\u03af\u03bd\u03b1\u03b9 \u03c3\u03c7\u03b5\u03b4\u03b9\u03b1\u03c3\u03bc\u03cc\u03c2 \u03b5\u03bb\u03b5\u03b3\u03c7\u03cc\u03bc\u03b5\u03bd\u03bf\u03c5 \u03bc\u03af\u03b3\u03bc\u03b1\u03c4\u03bf\u03c2 \u03bc\u03b5 \u03c3\u03b1\u03c6\u03ae \u03cc\u03c1\u03b9\u03b1, \u03c0\u03b1\u03c1\u03b1\u03ba\u03bf\u03bb\u03bf\u03cd\u03b8\u03b7\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03b4\u03c5\u03bd\u03b1\u03c4\u03cc\u03c4\u03b7\u03c4\u03b1 \u03b1\u03bd\u03b1\u03af\u03c1\u03b5\u03c3\u03b7\u03c2. \u03a4\u03bf guardrail \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03c3\u03c5\u03bd\u03b4\u03ad\u03b5\u03c4\u03b1\u03b9 \u03bc\u03b5 \u03b9\u03b4\u03b9\u03bf\u03ba\u03c4\u03ae\u03c4\u03b7, cadence \u03b5\u03bb\u03ad\u03b3\u03c7\u03bf\u03c5 \u03ba\u03b1\u03b9 \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03b7 \u03b5\u03bd\u03ad\u03c1\u03b3\u03b5\u03b9\u03b1 \u03cc\u03c4\u03b1\u03bd \u03c0\u03b1\u03c1\u03b1\u03b2\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9.<\/p>\n<h2 id=\"pososta-survey\">\u0393\u03b9\u03b1\u03c4\u03af \u03c4\u03b1 \u03c0\u03bf\u03c3\u03bf\u03c3\u03c4\u03ac \u03c4\u03bf\u03c5 survey \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03ba\u03b1\u03bd\u03cc\u03bd\u03b1\u03c2<\/h2>\n<p>\u0397 \u03b1\u03bd\u03b1\u03c3\u03ba\u03cc\u03c0\u03b7\u03c3\u03b7 \u03c0\u03c1\u03bf\u03c4\u03b5\u03af\u03bd\u03b5\u03b9 \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03b9\u03ba\u03ad\u03c2 \u03b6\u03ce\u03bd\u03b5\u03c2 \u03b1\u03bd\u03ac \u03c1\u03af\u03c3\u03ba\u03bf: \u03c3\u03c5\u03bd\u03b8\u03b5\u03c4\u03b9\u03ba\u03cc \u03bc\u03b5\u03c1\u03af\u03b4\u03b9\u03bf 60%\u201390% \u03b3\u03b9\u03b1 \u03b4\u03b7\u03bc\u03b9\u03bf\u03c5\u03c1\u03b3\u03b9\u03ba\u03ad\u03c2 \u03b5\u03c1\u03b3\u03b1\u03c3\u03af\u03b5\u03c2 \u03c7\u03b1\u03bc\u03b7\u03bb\u03bf\u03cd \u03c1\u03af\u03c3\u03ba\u03bf\u03c5, \u03b5\u03c6\u03cc\u03c3\u03bf\u03bd \u03c0\u03bf\u03b9\u03ba\u03b9\u03bb\u03af\u03b1 \u03ba\u03b1\u03b9 \u03b5\u03bd\u03c4\u03c1\u03bf\u03c0\u03af\u03b1 \u03c0\u03b1\u03c1\u03b1\u03bc\u03ad\u03bd\u03bf\u03c5\u03bd \u03c5\u03b3\u03b9\u03b5\u03af\u03c2\u00b7 30%\u201350% \u03b3\u03b9\u03b1 instruction-following \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03b1 \u03bc\u03b5 tail-aware weighting\u00b7 \u03ba\u03b1\u03b9 10% \u03ae \u03bb\u03b9\u03b3\u03cc\u03c4\u03b5\u03c1\u03bf \u03b3\u03b9\u03b1 \u03b9\u03b1\u03c4\u03c1\u03b9\u03ba\u03ad\u03c2, \u03bd\u03bf\u03bc\u03b9\u03ba\u03ad\u03c2 \u03ae \u03c7\u03c1\u03b7\u03bc\u03b1\u03c4\u03bf\u03bf\u03b9\u03ba\u03bf\u03bd\u03bf\u03bc\u03b9\u03ba\u03ad\u03c2 \u03b5\u03c1\u03b3\u03b1\u03c3\u03af\u03b5\u03c2. \u0391\u03c5\u03c4\u03bf\u03af \u03bf\u03b9 \u03b1\u03c1\u03b9\u03b8\u03bc\u03bf\u03af \u03b5\u03af\u03bd\u03b1\u03b9 \u03c3\u03c5\u03c3\u03c4\u03ac\u03c3\u03b5\u03b9\u03c2 \u03c4\u03c9\u03bd \u03c3\u03c5\u03b3\u03b3\u03c1\u03b1\u03c6\u03ad\u03c9\u03bd \u03ba\u03b1\u03b9 \u03b4\u03b5\u03bd \u03b1\u03c0\u03bf\u03c4\u03b5\u03bb\u03bf\u03cd\u03bd \u03ba\u03b1\u03b8\u03bf\u03bb\u03b9\u03ba\u03ac \u03b5\u03c0\u03b9\u03ba\u03c5\u03c1\u03c9\u03bc\u03ad\u03bd\u03b1 safety thresholds.<\/p>\n<aside class=\"td-article-note\"><strong>\u039c\u03b7\u03bd \u03b1\u03bd\u03c4\u03b9\u03b3\u03c1\u03ac\u03c6\u03b5\u03c4\u03b5 \u03c4\u03bf \u03c0\u03bf\u03c3\u03bf\u03c3\u03c4\u03cc \u03c3\u03b5 policy:<\/strong> \u03b7 \u03af\u03b4\u03b9\u03b1 \u03b7 \u03b1\u03bd\u03b1\u03c3\u03ba\u03cc\u03c0\u03b7\u03c3\u03b7 \u03c7\u03b1\u03c1\u03b1\u03ba\u03c4\u03b7\u03c1\u03af\u03b6\u03b5\u03b9 \u03c4\u03bf \u03b1\u03c3\u03c6\u03b1\u03bb\u03ad\u03c2 \u03cc\u03c1\u03b9\u03bf task-dependent. \u039a\u03ac\u03b8\u03b5 \u03b1\u03bd\u03b1\u03bb\u03bf\u03b3\u03af\u03b1 \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03c0\u03b5\u03af\u03c1\u03b1\u03bc\u03b1 \u03c3\u03c4\u03b1 \u03b4\u03b9\u03ba\u03ac \u03c3\u03b1\u03c2 \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03b1, rare-case suites, \u03b1\u03c0\u03bf\u03b4\u03b5\u03ba\u03c4\u03cc \u03ba\u03cc\u03c3\u03c4\u03bf\u03c2 \u03b1\u03c0\u03bf\u03c4\u03c5\u03c7\u03af\u03b1\u03c2 \u03ba\u03b1\u03b9 \u03ad\u03b3\u03ba\u03c1\u03b9\u03c3\u03b7 \u03b5\u03b9\u03b4\u03b9\u03ba\u03ce\u03bd \u03cc\u03c0\u03bf\u03c5 \u03c4\u03bf \u03c1\u03af\u03c3\u03ba\u03bf \u03b5\u03af\u03bd\u03b1\u03b9 \u03c5\u03c8\u03b7\u03bb\u03cc.<\/aside>\n<p>\u03a0\u03c1\u03b1\u03ba\u03c4\u03b9\u03ba\u03ac, \u03bf synthetic-data ratio \u03b5\u03af\u03bd\u03b1\u03b9 control variable. \u0391\u03c5\u03be\u03ac\u03bd\u03b5\u03c4\u03b1\u03b9 \u03bc\u03cc\u03bd\u03bf \u03cc\u03c4\u03b1\u03bd \u03bf\u03b9 \u03bc\u03b5\u03c4\u03c1\u03ae\u03c3\u03b5\u03b9\u03c2 \u03bc\u03ad\u03bd\u03bf\u03c5\u03bd \u03b5\u03bd\u03c4\u03cc\u03c2 \u03bf\u03c1\u03af\u03c9\u03bd \u03ba\u03b1\u03b9 \u03bc\u03b5\u03b9\u03ce\u03bd\u03b5\u03c4\u03b1\u03b9 \u03bc\u03cc\u03bb\u03b9\u03c2 \u03b5\u03bc\u03c6\u03b1\u03bd\u03b9\u03c3\u03c4\u03bf\u03cd\u03bd \u03c3\u03b7\u03bc\u03ac\u03b4\u03b9\u03b1 drift. \u03a3\u03b5 high-stakes \u03c7\u03c1\u03ae\u03c3\u03b7, \u03b7 \u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7 \u03b1\u03c0\u03cc \u03b5\u03b9\u03b4\u03b9\u03ba\u03bf\u03cd\u03c2 \u03ba\u03b1\u03b9 \u03b7 \u03c3\u03c5\u03bc\u03bc\u03cc\u03c1\u03c6\u03c9\u03c3\u03b7 \u03c5\u03c0\u03b5\u03c1\u03b9\u03c3\u03c7\u03cd\u03bf\u03c5\u03bd \u03bf\u03c0\u03bf\u03b9\u03bf\u03c5\u03b4\u03ae\u03c0\u03bf\u03c4\u03b5 \u03b3\u03b5\u03bd\u03b9\u03ba\u03bf\u03cd heuristic.<\/p>\n<h2 id=\"omada-epta-vimata\">\u0388\u03bd\u03b1 \u03c0\u03c1\u03b1\u03ba\u03c4\u03b9\u03ba\u03cc \u03c3\u03c7\u03ad\u03b4\u03b9\u03bf \u03c3\u03b5 \u03b5\u03c0\u03c4\u03ac \u03b2\u03ae\u03bc\u03b1\u03c4\u03b1<\/h2>\n<p>\u039c\u03b9\u03b1 \u03bf\u03bc\u03ac\u03b4\u03b1 AI, marketing \u03ae e-commerce \u03b4\u03b5\u03bd \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03bd\u03b1 \u03c0\u03b5\u03c1\u03b9\u03bc\u03ad\u03bd\u03b5\u03b9 \u03bd\u03ad\u03bf foundation-model training \u03b3\u03b9\u03b1 \u03bd\u03b1 \u03b2\u03c1\u03b5\u03b9 \u03b1\u03bd\u03b1\u03b4\u03c1\u03bf\u03bc\u03b9\u03ba\u03cc \u03b2\u03c1\u03cc\u03c7\u03bf. Generated answers \u03c0\u03bf\u03c5 \u03b3\u03af\u03bd\u03bf\u03bd\u03c4\u03b1\u03b9 knowledge-base content, AI labels \u03c0\u03bf\u03c5 \u03b5\u03b3\u03ba\u03c1\u03af\u03bd\u03bf\u03bd\u03c4\u03b1\u03b9 \u03b1\u03c5\u03c4\u03cc\u03bc\u03b1\u03c4\u03b1 \u03ba\u03b1\u03b9 \u03c3\u03c5\u03bd\u03b8\u03b5\u03c4\u03b9\u03ba\u03ad\u03c2 \u03b1\u03be\u03b9\u03bf\u03bb\u03bf\u03b3\u03ae\u03c3\u03b5\u03b9\u03c2 \u03c0\u03bf\u03c5 \u03b5\u03ba\u03c0\u03b1\u03b9\u03b4\u03b5\u03cd\u03bf\u03c5\u03bd \u03c4\u03bf\u03bd \u03b5\u03c0\u03cc\u03bc\u03b5\u03bd\u03bf evaluator \u03bc\u03c0\u03bf\u03c1\u03bf\u03cd\u03bd \u03bd\u03b1 \u03b4\u03b7\u03bc\u03b9\u03bf\u03c5\u03c1\u03b3\u03ae\u03c3\u03bf\u03c5\u03bd \u03c0\u03b1\u03c1\u03cc\u03bc\u03bf\u03b9\u03bf drift.<\/p>\n<div class=\"td-step-list\">\n<p class=\"td-step-list-title\">\u0395\u03c0\u03c4\u03ac \u03b2\u03ae\u03bc\u03b1\u03c4\u03b1 \u03b3\u03b9\u03b1 \u03bd\u03b1 \u03bc\u03b7 \u03bc\u03b1\u03b8\u03b1\u03af\u03bd\u03b5\u03b9 \u03b7 AI \u03bc\u03cc\u03bd\u03bf \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03b7\u03c7\u03ce \u03c4\u03b7\u03c2<\/p>\n<ol>\n<li><span class=\"td-step-kicker\">\u0421\u0442\u044a\u043f\u043a\u0430 1<\/span><strong>\u03a7\u03b1\u03c1\u03c4\u03bf\u03b3\u03c1\u03b1\u03c6\u03ae\u03c3\u03c4\u03b5 \u03cc\u03bb\u03bf\u03c5\u03c2 \u03c4\u03bf\u03c5\u03c2 feedback loops<\/strong>\n<p>\u039a\u03b1\u03c4\u03b1\u03b3\u03c1\u03ac\u03c8\u03c4\u03b5 \u03c0\u03bf\u03cd AI outputs \u03b5\u03c0\u03b9\u03c3\u03c4\u03c1\u03ad\u03c6\u03bf\u03c5\u03bd \u03c9\u03c2 training examples, labels, preference pairs, embeddings, \u03b1\u03be\u03b9\u03bf\u03bb\u03bf\u03b3\u03ae\u03c3\u03b5\u03b9\u03c2 \u03ae knowledge-base content.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">\u0421\u0442\u044a\u043f\u043a\u0430 2<\/span><strong>\u03a7\u03c9\u03c1\u03af\u03c3\u03c4\u03b5 \u03b1\u03bd\u03b8\u03c1\u03ce\u03c0\u03b9\u03bd\u03b1, \u03c3\u03c5\u03bd\u03b8\u03b5\u03c4\u03b9\u03ba\u03ac \u03ba\u03b1\u03b9 \u03ac\u03b3\u03bd\u03c9\u03c3\u03c4\u03b1 samples<\/strong>\n<p>\u039c\u03b7\u03bd \u03b1\u03c6\u03ae\u03bd\u03b5\u03c4\u03b5 \u03c5\u03bb\u03b9\u03ba\u03cc \u03ac\u03b3\u03bd\u03c9\u03c3\u03c4\u03b7\u03c2 \u03c0\u03c1\u03bf\u03ad\u03bb\u03b5\u03c5\u03c3\u03b7\u03c2 \u03bd\u03b1 \u03b5\u03bd\u03c3\u03c9\u03bc\u03b1\u03c4\u03ce\u03bd\u03b5\u03c4\u03b1\u03b9 \u03c3\u03b9\u03c9\u03c0\u03b7\u03c1\u03ac. \u039a\u03ac\u03b8\u03b5 \u03ba\u03b1\u03c4\u03b7\u03b3\u03bf\u03c1\u03af\u03b1 \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03be\u03b5\u03c7\u03c9\u03c1\u03b9\u03c3\u03c4\u03ae \u03ad\u03ba\u03b4\u03bf\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03bc\u03b5\u03c4\u03c1\u03ae\u03c3\u03b9\u03bc\u03bf \u03bc\u03b5\u03c1\u03af\u03b4\u03b9\u03bf.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">\u0421\u0442\u044a\u043f\u043a\u0430 3<\/span><strong>\u039a\u03bb\u03b5\u03b9\u03b4\u03ce\u03c3\u03c4\u03b5 \u03b1\u03bd\u03b8\u03c1\u03ce\u03c0\u03b9\u03bd\u03bf golden set<\/strong>\n<p>\u0394\u03b9\u03b1\u03c4\u03b7\u03c1\u03ae\u03c3\u03c4\u03b5 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ad\u03c2 \u03c3\u03c5\u03c7\u03bd\u03ad\u03c2 \u03ba\u03b1\u03b9 \u03c3\u03c0\u03ac\u03bd\u03b9\u03b5\u03c2 \u03c0\u03b5\u03c1\u03b9\u03c0\u03c4\u03ce\u03c3\u03b5\u03b9\u03c2 \u03c0\u03bf\u03c5 \u03b4\u03b5\u03bd \u03b1\u03bd\u03b1\u03ba\u03c5\u03ba\u03bb\u03ce\u03bd\u03bf\u03bd\u03c4\u03b1\u03b9 \u03ba\u03b1\u03b9 \u03b4\u03b5\u03bd \u03b2\u03b1\u03b8\u03bc\u03bf\u03bb\u03bf\u03b3\u03bf\u03cd\u03bd\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc \u03c4\u03bf \u03af\u03b4\u03b9\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03c0\u03bf\u03c5 \u03c0\u03b1\u03c1\u03ac\u03b3\u03b5\u03b9 \u03c4\u03b1 samples.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">\u0421\u0442\u044a\u043f\u043a\u0430 4<\/span><strong>\u039f\u03c1\u03af\u03c3\u03c4\u03b5 tail \u03ba\u03b1\u03b9 diversity baselines<\/strong>\n<p>\u039c\u03b5\u03c4\u03c1\u03ae\u03c3\u03c4\u03b5 entropy, distinct n-grams, coverage \u03ae feature spread \u03b1\u03bd\u03ac \u03b5\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03b7\u03bc\u03b1\u03c4\u03b9\u03ba\u03cc slice \u03c0\u03c1\u03b9\u03bd \u03b1\u03bb\u03bb\u03ac\u03be\u03b5\u03c4\u03b5 \u03c4\u03b7 \u03c3\u03c5\u03bd\u03b8\u03b5\u03c4\u03b9\u03ba\u03ae \u03b1\u03bd\u03b1\u03bb\u03bf\u03b3\u03af\u03b1.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">\u0421\u0442\u044a\u043f\u043a\u0430 5<\/span><strong>\u039a\u03b1\u03c4\u03b1\u03b3\u03c1\u03ac\u03c8\u03c4\u03b5 generator \u03ba\u03b1\u03b9 \u03c6\u03af\u03bb\u03c4\u03c1\u03b1<\/strong>\n<p>\u0391\u03c0\u03bf\u03b8\u03b7\u03ba\u03b5\u03cd\u03c3\u03c4\u03b5 model, checkpoint, decoding settings, prompt family, candidate budget, filters, reviewer \u03ba\u03b1\u03b9 \u03c4\u03b5\u03bb\u03b9\u03ba\u03ae \u03b1\u03c0\u03cc\u03c6\u03b1\u03c3\u03b7 \u03b3\u03b9\u03b1 \u03ba\u03ac\u03b8\u03b5 dataset version.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">\u0421\u0442\u044a\u043f\u043a\u0430 6<\/span><strong>\u0391\u03c5\u03be\u03ae\u03c3\u03c4\u03b5 \u03c4\u03bf synthetic ratio \u03c3\u03c4\u03b1\u03b4\u03b9\u03b1\u03ba\u03ac<\/strong>\n<p>\u03a7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03c4\u03b5 holdout \u03ba\u03b1\u03b9 rare-case suites \u03c3\u03b5 \u03ba\u03ac\u03b8\u03b5 \u03b3\u03cd\u03c1\u03bf. \u039c\u03b7\u03bd \u03b1\u03c6\u03ae\u03bd\u03b5\u03c4\u03b5 \u03c4\u03bf \u03af\u03b4\u03b9\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03bd\u03b1 \u03c0\u03b1\u03c1\u03ac\u03b3\u03b5\u03b9, \u03bd\u03b1 \u03b2\u03b1\u03b8\u03bc\u03bf\u03bb\u03bf\u03b3\u03b5\u03af \u03ba\u03b1\u03b9 \u03bd\u03b1 \u03b5\u03b3\u03ba\u03c1\u03af\u03bd\u03b5\u03b9 \u03c7\u03c9\u03c1\u03af\u03c2 \u03b1\u03bd\u03b5\u03be\u03ac\u03c1\u03c4\u03b7\u03c4\u03bf anchor.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">\u0421\u0442\u044a\u043f\u043a\u0430 7<\/span><strong>\u0394\u03bf\u03ba\u03b9\u03bc\u03ac\u03c3\u03c4\u03b5 rollback \u03c0\u03c1\u03b9\u03bd \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae<\/strong>\n<p>\u039f\u03c1\u03af\u03c3\u03c4\u03b5 amber\/red thresholds, owner \u03ba\u03b1\u03b9 \u03c4\u03b5\u03bb\u03b5\u03c5\u03c4\u03b1\u03af\u03b1 \u03c3\u03c4\u03b1\u03b8\u03b5\u03c1\u03ae \u03ad\u03ba\u03b4\u03bf\u03c3\u03b7\u00b7 \u03b5\u03c0\u03b1\u03bb\u03b7\u03b8\u03b5\u03cd\u03c3\u03c4\u03b5 \u03cc\u03c4\u03b9 dataset \u03ba\u03b1\u03b9 checkpoint \u03bc\u03c0\u03bf\u03c1\u03bf\u03cd\u03bd \u03c0\u03c1\u03ac\u03b3\u03bc\u03b1\u03c4\u03b9 \u03bd\u03b1 \u03b5\u03c0\u03b1\u03bd\u03ad\u03bb\u03b8\u03bf\u03c5\u03bd.<\/p>\n<\/li>\n<\/ol>\n<\/div>\n<p>\u0397 \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae \u03c3\u03c5\u03bd\u03b8\u03b5\u03c4\u03b9\u03ba\u03ce\u03bd \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03c0\u03c1\u03bf\u03c3\u03c6\u03ad\u03c1\u03b5\u03b9 \u03ba\u03bb\u03af\u03bc\u03b1\u03ba\u03b1, \u03ba\u03ac\u03bb\u03c5\u03c8\u03b7 \u03ba\u03b1\u03b9 \u03b5\u03bb\u03b5\u03b3\u03c7\u03cc\u03bc\u03b5\u03bd\u03b1 tests. \u0397 \u03b1\u03be\u03af\u03b1 \u03c4\u03b7\u03c2, \u03cc\u03bc\u03c9\u03c2, \u03b5\u03be\u03b1\u03c1\u03c4\u03ac\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03b9\u03ba\u03b1\u03bd\u03cc\u03c4\u03b7\u03c4\u03b1 \u03c4\u03b7\u03c2 \u03bf\u03bc\u03ac\u03b4\u03b1\u03c2 \u03bd\u03b1 \u03b1\u03c0\u03bf\u03b4\u03b5\u03af\u03be\u03b5\u03b9 \u03c4\u03b9 \u03ac\u03bb\u03bb\u03b1\u03be\u03b5, \u03c0\u03bf\u03b9\u03b1 cases \u03c7\u03ac\u03b8\u03b7\u03ba\u03b1\u03bd \u03ba\u03b1\u03b9 \u03c0\u03ce\u03c2 \u03b5\u03c0\u03b9\u03c3\u03c4\u03c1\u03ad\u03c6\u03b5\u03b9 \u03c3\u03b5 \u03b1\u03c3\u03c6\u03b1\u03bb\u03ad\u03c2 \u03c3\u03b7\u03bc\u03b5\u03af\u03bf.<\/p>\n<h2 id=\"anoikta-erotimata-agora\">\u0391\u03bd\u03bf\u03b9\u03c7\u03c4\u03ac \u03b5\u03c1\u03c9\u03c4\u03ae\u03bc\u03b1\u03c4\u03b1 \u03c0\u03bf\u03c5 \u03b1\u03c6\u03bf\u03c1\u03bf\u03cd\u03bd \u03ae\u03b4\u03b7 \u03c4\u03b7\u03bd \u03b1\u03b3\u03bf\u03c1\u03ac<\/h2>\n<p>\u0397 \u03b1\u03bd\u03b1\u03c3\u03ba\u03cc\u03c0\u03b7\u03c3\u03b7 \u03b5\u03c0\u03b9\u03c3\u03b7\u03bc\u03b1\u03af\u03bd\u03b5\u03b9 \u03cc\u03c4\u03b9 \u03c4\u03bf speech \u03c0\u03b1\u03c1\u03b1\u03bc\u03ad\u03bd\u03b5\u03b9 \u03bf\u03c5\u03c3\u03b9\u03b1\u03c3\u03c4\u03b9\u03ba\u03ac \u03b1\u03bd\u03b5\u03be\u03b5\u03c1\u03b5\u03cd\u03bd\u03b7\u03c4\u03bf: \u03b4\u03b5\u03bd \u03c5\u03c0\u03ac\u03c1\u03c7\u03bf\u03c5\u03bd \u03b1\u03ba\u03cc\u03bc\u03b7 \u03c3\u03c5\u03c3\u03c4\u03b7\u03bc\u03b1\u03c4\u03b9\u03ba\u03ad\u03c2 \u03bc\u03b5\u03bb\u03ad\u03c4\u03b5\u03c2 \u03b3\u03b9\u03b1 \u03c4\u03bf \u03b1\u03bd \u03b7 \u03b1\u03bd\u03b1\u03b4\u03c1\u03bf\u03bc\u03b9\u03ba\u03ae \u03b5\u03ba\u03c0\u03b1\u03af\u03b4\u03b5\u03c5\u03c3\u03b7 \u03c5\u03c0\u03bf\u03b2\u03b1\u03b8\u03bc\u03af\u03b6\u03b5\u03b9 \u03c0\u03c1\u03bf\u03c3\u03c9\u03b4\u03af\u03b1, \u03c6\u03c9\u03bd\u03b7\u03c4\u03b9\u03ba\u03ae \u03c0\u03bf\u03b9\u03ba\u03b9\u03bb\u03af\u03b1 \u03ae \u03b3\u03b5\u03bd\u03af\u03ba\u03b5\u03c5\u03c3\u03b7 \u03bf\u03bc\u03b9\u03bb\u03b7\u03c4\u03ce\u03bd. \u03a3\u03c4\u03bf federated learning, \u03c3\u03c5\u03bd\u03b8\u03b5\u03c4\u03b9\u03ba\u03ac \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03b1 \u03b1\u03c0\u03cc \u03c4\u03bf\u03c0\u03b9\u03ba\u03ac \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03b1 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b4\u03b9\u03b1\u03b4\u03bf\u03b8\u03bf\u03cd\u03bd \u03bc\u03ad\u03c3\u03c9 aggregation, \u03b9\u03b4\u03b9\u03b1\u03af\u03c4\u03b5\u03c1\u03b1 \u03c3\u03b5 non-IID \u03c0\u03b5\u03c1\u03b9\u03b2\u03ac\u03bb\u03bb\u03bf\u03bd\u03c4\u03b1.<\/p>\n<p>\u0386\u03bb\u03bb\u03b5\u03c2 \u03ba\u03b1\u03c4\u03b5\u03c5\u03b8\u03cd\u03bd\u03c3\u03b5\u03b9\u03c2 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c4\u03bf machine unlearning \u03b3\u03b9\u03b1 \u03b1\u03c6\u03b1\u03af\u03c1\u03b5\u03c3\u03b7 \u03b5\u03c0\u03b9\u03b2\u03bb\u03b1\u03b2\u03ce\u03bd artifacts, \u03b7 immune AI, \u03b7 \u03c3\u03c5\u03bd\u03b5\u03c7\u03ae\u03c2 \u03b2\u03b1\u03b8\u03bc\u03bf\u03bd\u03cc\u03bc\u03b7\u03c3\u03b7 \u03ad\u03bd\u03b1\u03bd\u03c4\u03b9 trusted datasets \u03ae golden models \u03ba\u03b1\u03b9 \u03b7 \u03c3\u03cd\u03bd\u03b4\u03b5\u03c3\u03b7 \u03c4\u03bf\u03c5 collapse \u03bc\u03b5 forgetting \u03ba\u03b1\u03b9 adversarial robustness. \u0391\u03c5\u03c4\u03ad\u03c2 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b5\u03c1\u03b5\u03c5\u03bd\u03b7\u03c4\u03b9\u03ba\u03ad\u03c2 \u03c0\u03c1\u03bf\u03c4\u03ac\u03c3\u03b5\u03b9\u03c2, \u03cc\u03c7\u03b9 \u03ce\u03c1\u03b9\u03bc\u03b5\u03c2 \u03b5\u03b3\u03b3\u03c5\u03ae\u03c3\u03b5\u03b9\u03c2.<\/p>\n<p>\u0393\u03b9\u03b1 \u03c4\u03b9\u03c2 \u03b5\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03ae\u03c3\u03b5\u03b9\u03c2, \u03c4\u03bf \u03ce\u03c1\u03b9\u03bc\u03bf \u03c3\u03c5\u03bc\u03c0\u03ad\u03c1\u03b1\u03c3\u03bc\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03ae\u03b4\u03b7 \u03b5\u03c6\u03b1\u03c1\u03bc\u03cc\u03c3\u03b9\u03bc\u03bf: \u03ba\u03c1\u03b1\u03c4\u03ae\u03c3\u03c4\u03b5 \u03b1\u03bd\u03b8\u03c1\u03ce\u03c0\u03b9\u03bd\u03bf \u03c0\u03c5\u03c1\u03ae\u03bd\u03b1, \u03c0\u03c1\u03bf\u03c3\u03c4\u03b1\u03c4\u03ad\u03c8\u03c4\u03b5 \u03c4\u03b7\u03bd \u03bf\u03c5\u03c1\u03ac, \u03ba\u03b1\u03c4\u03b1\u03b3\u03c1\u03ac\u03c8\u03c4\u03b5 \u03c4\u03b7\u03bd \u03c0\u03c1\u03bf\u03ad\u03bb\u03b5\u03c5\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03c3\u03c5\u03bd\u03b4\u03ad\u03c3\u03c4\u03b5 \u03c4\u03b9\u03c2 \u03bc\u03b5\u03c4\u03c1\u03ae\u03c3\u03b5\u03b9\u03c2 \u03bc\u03b5 rollback. \u03a4\u03bf model collapse \u03b4\u03b5\u03bd \u03b1\u03bd\u03c4\u03b9\u03bc\u03b5\u03c4\u03c9\u03c0\u03af\u03b6\u03b5\u03c4\u03b1\u03b9 \u03bc\u03b5 \u03ad\u03bd\u03b1 \u03ba\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03bf prompt \u03b1\u03bb\u03bb\u03ac \u03bc\u03b5 \u03b1\u03c1\u03c7\u03b9\u03c4\u03b5\u03ba\u03c4\u03bf\u03bd\u03b9\u03ba\u03ae \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd \u03ba\u03b1\u03b9 \u03b4\u03b9\u03b1\u03ba\u03c5\u03b2\u03ad\u03c1\u03bd\u03b7\u03c3\u03b7.<\/p>\n<section class=\"td-service-cta\">\n<div class=\"td-service-cta-content\">\n<p class=\"td-service-cta-kicker\">\u0391\u03c0\u03cc \u03c4\u03bf synthetic data \u03c3\u03b5 \u03b5\u03bb\u03b5\u03b3\u03c7\u03cc\u03bc\u03b5\u03bd\u03b7 \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae<\/p>\n<p class=\"td-service-cta-title\">\u03a3\u03c7\u03b5\u03b4\u03b9\u03ac\u03c3\u03c4\u03b5 AI workflows \u03c0\u03bf\u03c5 \u03b4\u03b5\u03bd \u03b1\u03bd\u03b1\u03ba\u03c5\u03ba\u03bb\u03ce\u03bd\u03bf\u03c5\u03bd \u03c3\u03b9\u03c9\u03c0\u03b7\u03c1\u03ac \u03c4\u03bf \u03af\u03b4\u03b9\u03bf \u03c3\u03c6\u03ac\u03bb\u03bc\u03b1<\/p>\n<p>\u0397 TWO DOTS \u03c7\u03b1\u03c1\u03c4\u03bf\u03b3\u03c1\u03b1\u03c6\u03b5\u03af data lineage, human anchors, \u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7 \u03b1\u03bd\u03ac slice, approval gates, monitoring \u03ba\u03b1\u03b9 rollback \u03ce\u03c3\u03c4\u03b5 \u03b7 \u03b1\u03c5\u03c4\u03bf\u03bc\u03b1\u03c4\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7 \u03bd\u03b1 \u03ba\u03bb\u03b9\u03bc\u03b1\u03ba\u03ce\u03bd\u03b5\u03c4\u03b1\u03b9 \u03c7\u03c9\u03c1\u03af\u03c2 \u03bd\u03b1 \u03c7\u03ac\u03bd\u03b5\u03b9 \u03c4\u03b9\u03c2 \u03b5\u03be\u03b1\u03b9\u03c1\u03ad\u03c3\u03b5\u03b9\u03c2 \u03c0\u03bf\u03c5 \u03bc\u03b5\u03c4\u03c1\u03bf\u03cd\u03bd \u03b3\u03b9\u03b1 \u03c4\u03b7\u03bd \u03b5\u03c0\u03b9\u03c7\u03b5\u03af\u03c1\u03b7\u03c3\u03ae \u03c3\u03b1\u03c2.<\/p>\n<div class=\"td-service-cta-actions\"><a class=\"td-service-cta-button\" href=\"https:\/\/twodots.gr\/aftomatismoi-epicheiriseon-ai\/\">\u03a3\u03c5\u03b6\u03b7\u03c4\u03ae\u03c3\u03c4\u03b5 \u03ad\u03bd\u03b1 \u03b5\u03bb\u03b5\u03b3\u03c7\u03cc\u03bc\u03b5\u03bd\u03bf AI workflow<\/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 model collapse;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u0395\u03af\u03bd\u03b1\u03b9 \u03b7 \u03c3\u03c4\u03b1\u03b4\u03b9\u03b1\u03ba\u03ae \u03c5\u03c0\u03bf\u03b2\u03ac\u03b8\u03bc\u03b9\u03c3\u03b7 \u03b5\u03bd\u03cc\u03c2 generative model \u03cc\u03c4\u03b1\u03bd \u03c3\u03c5\u03bd\u03b8\u03b5\u03c4\u03b9\u03ba\u03ac outputs \u03b5\u03c0\u03b9\u03c3\u03c4\u03c1\u03ad\u03c6\u03bf\u03c5\u03bd \u03b1\u03bd\u03b1\u03b4\u03c1\u03bf\u03bc\u03b9\u03ba\u03ac \u03c3\u03c4\u03b7\u03bd \u03b5\u03ba\u03c0\u03b1\u03af\u03b4\u03b5\u03c5\u03c3\u03b7 \u03b5\u03c0\u03cc\u03bc\u03b5\u03bd\u03c9\u03bd \u03b3\u03b5\u03bd\u03b9\u03ce\u03bd, \u03c0\u03c1\u03bf\u03ba\u03b1\u03bb\u03ce\u03bd\u03c4\u03b1\u03c2 drift, \u03b1\u03c0\u03ce\u03bb\u03b5\u03b9\u03b1 \u03c0\u03bf\u03b9\u03ba\u03b9\u03bb\u03af\u03b1\u03c2 \u03ba\u03b1\u03b9 \u03c6\u03c4\u03c9\u03c7\u03cc\u03c4\u03b5\u03c1\u03b7 \u03ba\u03ac\u03bb\u03c5\u03c8\u03b7 \u03c3\u03c0\u03ac\u03bd\u03b9\u03c9\u03bd \u03c0\u03b5\u03c1\u03b9\u03c0\u03c4\u03ce\u03c3\u03b5\u03c9\u03bd.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u03a3\u03c5\u03bc\u03b2\u03b1\u03af\u03bd\u03b5\u03b9 \u03bc\u03cc\u03bd\u03bf \u03c3\u03c4\u03b1 \u03bc\u03b5\u03b3\u03ac\u03bb\u03b1 \u03b3\u03bb\u03c9\u03c3\u03c3\u03b9\u03ba\u03ac \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03b1;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u038c\u03c7\u03b9. \u0397 \u03b2\u03b9\u03b2\u03bb\u03b9\u03bf\u03b3\u03c1\u03b1\u03c6\u03af\u03b1 \u03ba\u03b1\u03bb\u03cd\u03c0\u03c4\u03b5\u03b9 VAEs, diffusion \u03ba\u03b1\u03b9 ReFlow models, LLMs \u03ba\u03b1\u03b9 multimodal \u03c3\u03c5\u03c3\u03c4\u03ae\u03bc\u03b1\u03c4\u03b1. \u039f\u03b9 \u03b5\u03ba\u03b4\u03b7\u03bb\u03ce\u03c3\u03b5\u03b9\u03c2 \u03b4\u03b9\u03b1\u03c6\u03ad\u03c1\u03bf\u03c5\u03bd, \u03b1\u03bb\u03bb\u03ac \u03b7 \u03b1\u03c0\u03ce\u03bb\u03b5\u03b9\u03b1 \u03bf\u03c5\u03c1\u03ac\u03c2 \u03ba\u03b1\u03b9 \u03b7 \u03c3\u03c5\u03c3\u03c3\u03ce\u03c1\u03b5\u03c5\u03c3\u03b7 bias \u03b5\u03af\u03bd\u03b1\u03b9 \u03ba\u03bf\u03b9\u03bd\u03ac \u03bc\u03bf\u03c4\u03af\u03b2\u03b1.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u0395\u03af\u03bd\u03b1\u03b9 \u03cc\u03bb\u03b1 \u03c4\u03b1 \u03c3\u03c5\u03bd\u03b8\u03b5\u03c4\u03b9\u03ba\u03ac \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03b1 \u03b5\u03c0\u03b9\u03ba\u03af\u03bd\u03b4\u03c5\u03bd\u03b1;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u038c\u03c7\u03b9. \u039c\u03c0\u03bf\u03c1\u03bf\u03cd\u03bd \u03bd\u03b1 \u03b5\u03c0\u03b5\u03ba\u03c4\u03b5\u03af\u03bd\u03bf\u03c5\u03bd \u03c4\u03b7\u03bd \u03ba\u03ac\u03bb\u03c5\u03c8\u03b7 \u03ba\u03b1\u03b9 \u03bd\u03b1 \u03bc\u03b5\u03b9\u03ce\u03c3\u03bf\u03c5\u03bd \u03c0\u03b5\u03c1\u03b9\u03bf\u03c1\u03b9\u03c3\u03bc\u03bf\u03cd\u03c2 \u03c0\u03c1\u03bf\u03c3\u03c6\u03bf\u03c1\u03ac\u03c2 \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd. \u039f \u03ba\u03af\u03bd\u03b4\u03c5\u03bd\u03bf\u03c2 \u03b1\u03c5\u03be\u03ac\u03bd\u03b5\u03c4\u03b1\u03b9 \u03cc\u03c4\u03b1\u03bd \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03bf\u03cd\u03bd\u03c4\u03b1\u03b9 \u03c7\u03c9\u03c1\u03af\u03c2 \u03b1\u03bd\u03b8\u03c1\u03ce\u03c0\u03b9\u03bd\u03bf anchor, provenance, \u03ad\u03bb\u03b5\u03b3\u03c7\u03bf diversity \u03ba\u03b1\u03b9 task-specific \u03cc\u03c1\u03b9\u03b1.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u03a5\u03c0\u03ac\u03c1\u03c7\u03b5\u03b9 \u03b1\u03c3\u03c6\u03b1\u03bb\u03ad\u03c2 \u03c0\u03bf\u03c3\u03bf\u03c3\u03c4\u03cc \u03c3\u03c5\u03bd\u03b8\u03b5\u03c4\u03b9\u03ba\u03ce\u03bd \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u0394\u03b5\u03bd \u03c5\u03c0\u03ac\u03c1\u03c7\u03b5\u03b9 \u03ba\u03b1\u03b8\u03bf\u03bb\u03b9\u03ba\u03cc \u03c0\u03bf\u03c3\u03bf\u03c3\u03c4\u03cc. \u0397 \u03b1\u03bd\u03b1\u03c3\u03ba\u03cc\u03c0\u03b7\u03c3\u03b7 \u03b4\u03af\u03bd\u03b5\u03b9 \u03b5\u03bd\u03b4\u03b5\u03b9\u03ba\u03c4\u03b9\u03ba\u03ad\u03c2 \u03b6\u03ce\u03bd\u03b5\u03c2 \u03b1\u03bd\u03ac \u03b5\u03c0\u03af\u03c0\u03b5\u03b4\u03bf \u03c1\u03af\u03c3\u03ba\u03bf\u03c5, \u03b1\u03bb\u03bb\u03ac \u03c4\u03bf\u03bd\u03af\u03b6\u03b5\u03b9 \u03cc\u03c4\u03b9 \u03c4\u03bf \u03b1\u03c3\u03c6\u03b1\u03bb\u03ad\u03c2 \u03cc\u03c1\u03b9\u03bf \u03b5\u03be\u03b1\u03c1\u03c4\u03ac\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03b5\u03c1\u03b3\u03b1\u03c3\u03af\u03b1 \u03ba\u03b1\u03b9 \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03b5\u03c0\u03b9\u03ba\u03cd\u03c1\u03c9\u03c3\u03b7 \u03bc\u03b5 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ac baselines \u03ba\u03b1\u03b9 rare-case tests.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u03a0\u03bf\u03b9\u03b1 \u03c3\u03b7\u03bc\u03ac\u03b4\u03b9\u03b1 \u03b5\u03bc\u03c6\u03b1\u03bd\u03af\u03b6\u03bf\u03bd\u03c4\u03b1\u03b9 \u03c0\u03c1\u03ce\u03c4\u03b1;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u03a0\u03c4\u03ce\u03c3\u03b7 \u03b5\u03bd\u03c4\u03c1\u03bf\u03c0\u03af\u03b1\u03c2 \u03ba\u03b1\u03b9 distinct n-grams, \u03b5\u03c0\u03b1\u03bd\u03b1\u03bb\u03b7\u03c0\u03c4\u03b9\u03ba\u03ad\u03c2 \u03ad\u03be\u03bf\u03b4\u03bf\u03b9, \u03b1\u03c0\u03ce\u03bb\u03b5\u03b9\u03b1 \u03c3\u03c0\u03ac\u03bd\u03b9\u03c9\u03bd \u03ba\u03b1\u03c4\u03b7\u03b3\u03bf\u03c1\u03b9\u03ce\u03bd, \u03c7\u03b5\u03b9\u03c1\u03cc\u03c4\u03b5\u03c1\u03bf image coverage, \u03ba\u03ac\u03bc\u03c8\u03b7 scaling curves \u03ba\u03b1\u03b9 drift \u03c3\u03c4\u03b7 \u03c3\u03c5\u03bc\u03c6\u03c9\u03bd\u03af\u03b1 \u03bc\u03b5\u03c4\u03b1\u03be\u03cd modalities.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u03a0\u03ce\u03c2 \u03b2\u03bf\u03b7\u03b8\u03ac \u03c4\u03bf data provenance;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u0395\u03c0\u03b9\u03c4\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03b5\u03bd\u03c4\u03bf\u03c0\u03b9\u03c3\u03c4\u03bf\u03cd\u03bd \u03c4\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf, \u03bf\u03b9 \u03c1\u03c5\u03b8\u03bc\u03af\u03c3\u03b5\u03b9\u03c2, \u03c4\u03b1 \u03c6\u03af\u03bb\u03c4\u03c1\u03b1 \u03ba\u03b1\u03b9 \u03b7 \u03b3\u03b5\u03bd\u03b5\u03b1\u03bb\u03bf\u03b3\u03af\u03b1 \u03c0\u03bf\u03c5 \u03c0\u03c1\u03bf\u03ba\u03ac\u03bb\u03b5\u03c3\u03b1\u03bd \u03c4\u03b7 \u03bc\u03b5\u03c4\u03b1\u03c4\u03cc\u03c0\u03b9\u03c3\u03b7, \u03ce\u03c3\u03c4\u03b5 \u03bd\u03b1 \u03b3\u03af\u03bd\u03b5\u03b9 rebalancing \u03ae rollback. \u03a5\u03c0\u03bf\u03c3\u03c4\u03b7\u03c1\u03af\u03b6\u03b5\u03b9 \u03b5\u03c0\u03af\u03c3\u03b7\u03c2 licensing \u03ba\u03b1\u03b9 audit.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u0391\u03c1\u03ba\u03b5\u03af \u03bd\u03b1 \u03b1\u03c5\u03be\u03ae\u03c3\u03bf\u03c5\u03bc\u03b5 \u03c4\u03bf temperature;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u038c\u03c7\u03b9. \u03a0\u03b5\u03c1\u03b9\u03c3\u03c3\u03cc\u03c4\u03b5\u03c1\u03b7 decoding diversity \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b4\u03b9\u03b1\u03c4\u03b7\u03c1\u03ae\u03c3\u03b5\u03b9 \u03c3\u03c0\u03ac\u03bd\u03b9\u03b5\u03c2 \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ad\u03c2, \u03b1\u03bb\u03bb\u03ac \u03b4\u03b5\u03bd \u03b1\u03bd\u03c4\u03b9\u03ba\u03b1\u03b8\u03b9\u03c3\u03c4\u03ac \u03c4\u03bf\u03bd \u03b1\u03bd\u03b8\u03c1\u03ce\u03c0\u03b9\u03bd\u03bf \u03c0\u03c5\u03c1\u03ae\u03bd\u03b1, \u03c4\u03b7\u03bd \u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7 \u03c0\u03bf\u03b9\u03cc\u03c4\u03b7\u03c4\u03b1\u03c2, \u03c4\u03bf provenance \u03ba\u03b1\u03b9 \u03c4\u03b1 task-specific thresholds.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u03a0\u03bf\u03b9\u03bf \u03b5\u03af\u03bd\u03b1\u03b9 \u03c4\u03bf \u03c0\u03c1\u03ce\u03c4\u03bf \u03c0\u03c1\u03b1\u03ba\u03c4\u03b9\u03ba\u03cc \u03b2\u03ae\u03bc\u03b1 \u03b3\u03b9\u03b1 \u03bc\u03b9\u03b1 \u03b5\u03c0\u03b9\u03c7\u03b5\u03af\u03c1\u03b7\u03c3\u03b7;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u039d\u03b1 \u03c7\u03b1\u03c1\u03c4\u03bf\u03b3\u03c1\u03b1\u03c6\u03ae\u03c3\u03b5\u03b9 \u03c0\u03bf\u03cd \u03c4\u03b1 AI outputs \u03b5\u03c0\u03b9\u03c3\u03c4\u03c1\u03ad\u03c6\u03bf\u03c5\u03bd \u03c9\u03c2 training data \u03ae labels, \u03bd\u03b1 \u03b4\u03b9\u03b1\u03c7\u03c9\u03c1\u03af\u03c3\u03b5\u03b9 \u03b1\u03bd\u03b8\u03c1\u03ce\u03c0\u03b9\u03bd\u03b1 \u03ba\u03b1\u03b9 \u03c3\u03c5\u03bd\u03b8\u03b5\u03c4\u03b9\u03ba\u03ac samples \u03ba\u03b1\u03b9 \u03bd\u03b1 \u03b4\u03b7\u03bc\u03b9\u03bf\u03c5\u03c1\u03b3\u03ae\u03c3\u03b5\u03b9 \u03c3\u03c4\u03b1\u03b8\u03b5\u03c1\u03cc golden set \u03bc\u03b5 \u03c3\u03c0\u03ac\u03bd\u03b9\u03b5\u03c2, \u03c5\u03c8\u03b7\u03bb\u03bf\u03cd \u03c1\u03af\u03c3\u03ba\u03bf\u03c5 \u03c0\u03b5\u03c1\u03b9\u03c0\u03c4\u03ce\u03c3\u03b5\u03b9\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\/2608.21366\" target=\"_blank\" rel=\"noopener\">arXiv \u2014 Reviewing Model Collapse and Countermeasures<\/a><\/li>\n<li><a href=\"https:\/\/arxiv.org\/abs\/2305.17493\" target=\"_blank\" rel=\"noopener\">arXiv \u2014 The Curse of Recursion: Training on Generated Data Makes Models Forget<\/a><\/li>\n<li><a href=\"https:\/\/arxiv.org\/abs\/2404.01413\" target=\"_blank\" rel=\"noopener\">arXiv \u2014 Is Model Collapse Inevitable? Breaking the Curse of Recursion by Accumulating Real and Synthetic Data<\/a><\/li>\n<li><a href=\"https:\/\/arxiv.org\/abs\/2402.07043\" target=\"_blank\" rel=\"noopener\">arXiv \u2014 A Tale of Tails: Model Collapse as a Change of Scaling Laws<\/a><\/li>\n<li><a href=\"https:\/\/www.nist.gov\/publications\/artificial-intelligence-risk-management-framework-generative-artificial-intelligence\" target=\"_blank\" rel=\"noopener\">NIST \u2014 Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile<\/a><\/li>\n<\/ul>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>\u03a4\u03bf model collapse \u03b4\u03b5\u03af\u03c7\u03bd\u03b5\u03b9 \u03c0\u03ce\u03c2 \u03b7 \u03b1\u03bd\u03b1\u03b4\u03c1\u03bf\u03bc\u03b9\u03ba\u03ae \u03c7\u03c1\u03ae\u03c3\u03b7 \u03c3\u03c5\u03bd\u03b8\u03b5\u03c4\u03b9\u03ba\u03ce\u03bd \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd \u03c3\u03c4\u03b5\u03bd\u03b5\u03cd\u03b5\u03b9 \u03c4\u03b7\u03bd \u03ba\u03b1\u03c4\u03b1\u03bd\u03bf\u03bc\u03ae \u03ba\u03b1\u03b9 \u03b3\u03b9\u03b1\u03c4\u03af \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03bf\u03bd\u03c4\u03b1\u03b9 human anchors, provenance \u03ba\u03b1\u03b9 rollback.<\/p>","protected":false},"author":1,"featured_media":98251,"comment_status":"open","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_gspb_post_css":"","content-type":"","footnotes":""},"categories":[199],"tags":[9260,20573,7204,20571,20572],"class_list":["post-97672","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-techniti-noimosyni","tag-ai-governance","tag-data-provenance","tag-generative-ai","tag-model-collapse","tag-synthetic-data"],"blocksy_meta":{"styles_descriptor":{"styles":{"desktop":"","tablet":"","mobile":""},"google_fonts":[],"version":8}},"_links":{"self":[{"href":"https:\/\/twodots.gr\/bg\/wp-json\/wp\/v2\/posts\/97672","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=97672"}],"version-history":[{"count":1,"href":"https:\/\/twodots.gr\/bg\/wp-json\/wp\/v2\/posts\/97672\/revisions"}],"predecessor-version":[{"id":98252,"href":"https:\/\/twodots.gr\/bg\/wp-json\/wp\/v2\/posts\/97672\/revisions\/98252"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/twodots.gr\/bg\/wp-json\/wp\/v2\/media\/98251"}],"wp:attachment":[{"href":"https:\/\/twodots.gr\/bg\/wp-json\/wp\/v2\/media?parent=97672"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/twodots.gr\/bg\/wp-json\/wp\/v2\/categories?post=97672"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/twodots.gr\/bg\/wp-json\/wp\/v2\/tags?post=97672"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}