{"id":97127,"date":"2026-09-11T13:56:10","date_gmt":"2026-09-11T10:56:10","guid":{"rendered":"https:\/\/twodots.gr\/?p=97127"},"modified":"2026-09-11T13:56:10","modified_gmt":"2026-09-11T10:56:10","slug":"rad-ai-xerei-apantisi-den-borei-na-tin-pei","status":"publish","type":"post","link":"https:\/\/twodots.gr\/bg\/rad-ai-xerei-apantisi-den-borei-na-tin-pei\/","title":{"rendered":"RAD \u03c3\u03c4\u03b7\u03bd AI: \u03cc\u03c4\u03b1\u03bd \u03c4\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03be\u03ad\u03c1\u03b5\u03b9 \u03c4\u03b7\u03bd \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7 \u03b1\u03bb\u03bb\u03ac \u03b4\u03b5\u03bd \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03c4\u03b7\u03bd \u03c0\u03b5\u03b9"},"content":{"rendered":"<div class=\"td-article-lede\">\n<p><strong>\u03a4\u03bf RAD \u03c3\u03c4\u03b7\u03bd AI \u03b1\u03c0\u03b1\u03bd\u03c4\u03ac \u03c3\u03b5 \u03ad\u03bd\u03b1 \u03c0\u03c1\u03b1\u03ba\u03c4\u03b9\u03ba\u03cc \u03c0\u03c1\u03cc\u03b2\u03bb\u03b7\u03bc\u03b1: \u03ad\u03bd\u03b1 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b4\u03b9\u03b1\u03c4\u03b7\u03c1\u03b5\u03af \u03bc\u03b9\u03b1 \u03c0\u03bb\u03b7\u03c1\u03bf\u03c6\u03bf\u03c1\u03af\u03b1, \u03b1\u03bb\u03bb\u03ac \u03bc\u03b5\u03c4\u03ac \u03c4\u03bf fine-tuning \u03bd\u03b1 \u03bc\u03b7\u03bd \u03c4\u03b7\u03bd \u03b1\u03bd\u03b1\u03ba\u03b1\u03bb\u03b5\u03af \u03ae \u03bd\u03b1 \u03bc\u03b7\u03bd \u03c4\u03b7\u03bd \u03b5\u03ba\u03c6\u03c1\u03ac\u03b6\u03b5\u03b9 \u03c3\u03c4\u03b7 \u03bc\u03bf\u03c1\u03c6\u03ae \u03c0\u03bf\u03c5 \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03bf \u03c7\u03c1\u03ae\u03c3\u03c4\u03b7\u03c2.<\/strong> \u0397 \u03bc\u03b5\u03bb\u03ad\u03c4\u03b7 <em>Knowing but Not Saying<\/em> \u03be\u03b5\u03c7\u03c9\u03c1\u03af\u03b6\u03b5\u03b9 \u03c4\u03b7\u03bd \u03b1\u03bd\u03b1\u03b3\u03bd\u03ce\u03c1\u03b9\u03c3\u03b7 \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03b1\u03bd\u03bf\u03b9\u03ba\u03c4\u03ae \u03b1\u03bd\u03ac\u03ba\u03bb\u03b7\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03b4\u03b5\u03af\u03c7\u03bd\u03b5\u03b9 \u03b3\u03b9\u03b1\u03c4\u03af \u03b7 \u03c7\u03b1\u03bc\u03b7\u03bb\u03cc\u03c4\u03b5\u03c1\u03b7 \u03b5\u03c0\u03af\u03b4\u03bf\u03c3\u03b7 \u03c3\u03b5 exact match \u03b4\u03b5\u03bd \u03b1\u03c0\u03bf\u03b4\u03b5\u03b9\u03ba\u03bd\u03cd\u03b5\u03b9 \u03b1\u03c0\u03cc \u03bc\u03cc\u03bd\u03b7 \u03c4\u03b7\u03c2 \u03cc\u03c4\u03b9 \u03b7 \u03b3\u03bd\u03ce\u03c3\u03b7 \u03b4\u03b9\u03b1\u03b3\u03c1\u03ac\u03c6\u03b7\u03ba\u03b5.<\/p>\n<p>\u03a3\u03c4\u03bf Llama-3.1-8B, \u03c4\u03bf TriviaQA exact match \u03ad\u03c0\u03b5\u03c3\u03b5 \u03b1\u03c0\u03cc 65,03 \u03c3\u03c4\u03b7 \u03b2\u03b1\u03c3\u03b9\u03ba\u03ae \u03ad\u03ba\u03b4\u03bf\u03c3\u03b7 \u03c3\u03b5 43,95 \u03bc\u03b5\u03c4\u03ac \u03c4\u03bf \u03c4\u03c5\u03c0\u03b9\u03ba\u03cc SFT. \u039c\u03b5 Recall-Anchored Distillation \u03b1\u03bd\u03ad\u03b2\u03b7\u03ba\u03b5 \u03c3\u03b5 51,62, \u03b5\u03bd\u03ce \u03c4\u03bf MedMCQA \u03ad\u03bc\u03b5\u03b9\u03bd\u03b5 \u03b1\u03bd\u03c4\u03b1\u03b3\u03c9\u03bd\u03b9\u03c3\u03c4\u03b9\u03ba\u03cc. \u03a0\u03c1\u03cc\u03ba\u03b5\u03b9\u03c4\u03b1\u03b9 \u03b3\u03b9\u03b1 \u03bc\u03b5\u03c1\u03b9\u03ba\u03ae \u03b1\u03bd\u03ac\u03ba\u03c4\u03b7\u03c3\u03b7 \u03c3\u03b5 \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03bf \u03c0\u03b5\u03af\u03c1\u03b1\u03bc\u03b1, \u03cc\u03c7\u03b9 \u03b3\u03b9\u03b1 \u03ba\u03b1\u03b8\u03bf\u03bb\u03b9\u03ba\u03ae \u03b5\u03b3\u03b3\u03cd\u03b7\u03c3\u03b7 \u03b4\u03b9\u03b1\u03c4\u03ae\u03c1\u03b7\u03c3\u03b7\u03c2 \u03b3\u03bd\u03ce\u03c3\u03b7\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=\"#fine-tuning-metatopisi\">\u03a4\u03bf fine-tuning \u03b1\u03bb\u03bb\u03ac\u03b6\u03b5\u03b9 \u03c0\u03b5\u03c1\u03b9\u03c3\u03c3\u03cc\u03c4\u03b5\u03c1\u03b1 \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03b5\u03be\u03b5\u03b9\u03b4\u03af\u03ba\u03b5\u03c5\u03c3\u03b7<\/a><\/li>\n<li><a href=\"#anagnorisi-anaklisi-ekfrasi\">\u0391\u03bd\u03b1\u03b3\u03bd\u03ce\u03c1\u03b9\u03c3\u03b7, \u03b1\u03bd\u03ac\u03ba\u03bb\u03b7\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03ad\u03ba\u03c6\u03c1\u03b1\u03c3\u03b7<\/a><\/li>\n<li><a href=\"#format-apotyxies\">\u03a0\u03cc\u03c4\u03b5 \u03c4\u03bf \u03bb\u03ac\u03b8\u03bf\u03c2 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b6\u03ae\u03c4\u03b7\u03bc\u03b1 format<\/a><\/li>\n<li><a href=\"#ti-einai-rad\">\u03a4\u03b9 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c4\u03bf Recall-Anchored Distillation<\/a><\/li>\n<li><a href=\"#teacher-student\">\u0388\u03bd\u03b1\u03c2 teacher \u03ba\u03b1\u03b9 \u03ad\u03bd\u03b1\u03c2 student \u03c3\u03c4\u03bf \u03af\u03b4\u03b9\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf<\/a><\/li>\n<li><a href=\"#replay-sygkrisi\">\u0393\u03b9\u03b1\u03c4\u03af \u03c4\u03bf \u03b1\u03c0\u03bb\u03cc replay \u03b4\u03b5\u03bd \u03b1\u03c1\u03ba\u03b5\u03af<\/a><\/li>\n<li><a href=\"#tria-backbones\">\u03a4\u03b1 \u03b1\u03c0\u03bf\u03c4\u03b5\u03bb\u03ad\u03c3\u03bc\u03b1\u03c4\u03b1 \u03c3\u03c4\u03b1 \u03c4\u03c1\u03af\u03b1 backbones<\/a><\/li>\n<li><a href=\"#kostos-oria\">\u039a\u03cc\u03c3\u03c4\u03bf\u03c2, \u03b1\u03c0\u03bf\u03b4\u03bf\u03c4\u03b9\u03ba\u03cc\u03c4\u03b7\u03c4\u03b1 \u03ba\u03b1\u03b9 \u03cc\u03c1\u03b9\u03b1<\/a><\/li>\n<li><a href=\"#epicheirisi-diagnosi\">\u03a4\u03b9 \u03b1\u03bb\u03bb\u03ac\u03b6\u03b5\u03b9 \u03c3\u03c4\u03b7 \u03b4\u03b9\u03ac\u03b3\u03bd\u03c9\u03c3\u03b7 \u03bc\u03b9\u03b1\u03c2 \u03b5\u03c0\u03b9\u03c7\u03b5\u03af\u03c1\u03b7\u03c3\u03b7\u03c2<\/a><\/li>\n<li><a href=\"#regression-suite\">\u03a0\u03c1\u03b1\u03ba\u03c4\u03b9\u03ba\u03ae \u03b4\u03b9\u03b1\u03b4\u03b9\u03ba\u03b1\u03c3\u03af\u03b1 \u03c0\u03c1\u03b9\u03bd \u03b1\u03c0\u03cc \u03c4\u03bf deployment<\/a><\/li>\n<li><a href=\"#sosto-symperasma\">\u03a4\u03bf \u03c3\u03c9\u03c3\u03c4\u03cc \u03c3\u03c5\u03bc\u03c0\u03ad\u03c1\u03b1\u03c3\u03bc\u03b1 \u03b3\u03b9\u03b1 \u03c4\u03bf RAD \u03c3\u03c4\u03b7\u03bd AI<\/a><\/li>\n<\/ul>\n<\/div>\n<h2 id=\"fine-tuning-metatopisi\">\u03a4\u03bf fine-tuning \u03b1\u03bb\u03bb\u03ac\u03b6\u03b5\u03b9 \u03c0\u03b5\u03c1\u03b9\u03c3\u03c3\u03cc\u03c4\u03b5\u03c1\u03b1 \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03b5\u03be\u03b5\u03b9\u03b4\u03af\u03ba\u03b5\u03c5\u03c3\u03b7<\/h2>\n<p>\u03a4\u03bf supervised fine-tuning \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03b5\u03af\u03c4\u03b1\u03b9 \u03b3\u03b9\u03b1 \u03bd\u03b1 \u03bc\u03ac\u03b8\u03b5\u03b9 \u03ad\u03bd\u03b1 \u03b3\u03b5\u03bd\u03b9\u03ba\u03cc \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03bd\u03b1 \u03b1\u03ba\u03bf\u03bb\u03bf\u03c5\u03b8\u03b5\u03af \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03b5\u03c2 \u03bf\u03b4\u03b7\u03b3\u03af\u03b5\u03c2, \u03bd\u03b1 \u03b1\u03c0\u03b1\u03bd\u03c4\u03ac \u03bc\u03b5 \u03bf\u03c1\u03b9\u03c3\u03bc\u03ad\u03bd\u03bf format \u03ae \u03bd\u03b1 \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03b5\u03af \u03bc\u03ad\u03c3\u03b1 \u03c3\u03b5 \u03ad\u03bd\u03b1\u03bd \u03b5\u03c0\u03b1\u03b3\u03b3\u03b5\u03bb\u03bc\u03b1\u03c4\u03b9\u03ba\u03cc \u03c4\u03bf\u03bc\u03ad\u03b1. \u0397 \u03c0\u03c1\u03bf\u03c3\u03b1\u03c1\u03bc\u03bf\u03b3\u03ae \u03b5\u03af\u03bd\u03b1\u03b9 \u03c7\u03c1\u03ae\u03c3\u03b9\u03bc\u03b7, \u03b1\u03bb\u03bb\u03ac \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03bf\u03c5\u03b4\u03ad\u03c4\u03b5\u03c1\u03b7: \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03bc\u03b5\u03c4\u03b1\u03b2\u03ac\u03bb\u03b5\u03b9 \u03c4\u03b9\u03c2 \u03b8\u03b5\u03bc\u03b1\u03c4\u03b9\u03ba\u03ad\u03c2 \u03c0\u03c1\u03bf\u03c4\u03b9\u03bc\u03ae\u03c3\u03b5\u03b9\u03c2, \u03c4\u03bf \u03cd\u03c6\u03bf\u03c2, \u03c4\u03b7 \u03c3\u03c5\u03bd\u03c4\u03bf\u03bc\u03af\u03b1, \u03c4\u03b7\u03bd \u03c4\u03ac\u03c3\u03b7 \u03b3\u03b9\u03b1 \u03b5\u03c0\u03b5\u03be\u03ae\u03b3\u03b7\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03c4\u03bf\u03bd \u03c4\u03c1\u03cc\u03c0\u03bf \u03bc\u03b5 \u03c4\u03bf\u03bd \u03bf\u03c0\u03bf\u03af\u03bf \u03b5\u03bd\u03b5\u03c1\u03b3\u03bf\u03c0\u03bf\u03b9\u03b5\u03af\u03c4\u03b1\u03b9 \u03b7 \u03b3\u03bd\u03ce\u03c3\u03b7 \u03c4\u03b7\u03c2 \u03c0\u03c1\u03bf\u03b5\u03ba\u03c0\u03b1\u03af\u03b4\u03b5\u03c5\u03c3\u03b7\u03c2.<\/p>\n<p>\u0397 \u03bc\u03b5\u03bb\u03ad\u03c4\u03b7 \u03b5\u03be\u03b5\u03c4\u03ac\u03b6\u03b5\u03b9 LoRA fine-tuning \u03c0\u03ac\u03bd\u03c9 \u03c3\u03c4\u03bf MedMCQA, \u03ad\u03bd\u03b1 \u03c3\u03cd\u03bd\u03bf\u03bb\u03bf \u03b9\u03b1\u03c4\u03c1\u03b9\u03ba\u03ce\u03bd \u03b5\u03c1\u03c9\u03c4\u03ae\u03c3\u03b5\u03c9\u03bd \u03c0\u03bf\u03bb\u03bb\u03b1\u03c0\u03bb\u03ae\u03c2 \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ae\u03c2. \u039c\u03b5\u03c4\u03ac \u03c4\u03b7\u03bd \u03c0\u03c1\u03bf\u03c3\u03b1\u03c1\u03bc\u03bf\u03b3\u03ae, \u03c4\u03b1 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03b1 \u03b2\u03b5\u03bb\u03c4\u03b9\u03ce\u03bd\u03bf\u03bd\u03c4\u03b1\u03b9 \u03c3\u03c4\u03bf\u03bd \u03c3\u03c4\u03cc\u03c7\u03bf \u03c4\u03bf\u03c5\u03c2, \u03b1\u03bb\u03bb\u03ac \u03c5\u03c0\u03bf\u03c7\u03c9\u03c1\u03bf\u03cd\u03bd \u03c3\u03b5 benchmarks \u03b1\u03bd\u03bf\u03b9\u03ba\u03c4\u03ae\u03c2 \u03b1\u03bd\u03ac\u03ba\u03bb\u03b7\u03c3\u03b7\u03c2 \u03b5\u03ba\u03c4\u03cc\u03c2 \u03c4\u03bf\u03c5 \u03b9\u03b1\u03c4\u03c1\u03b9\u03ba\u03bf\u03cd domain. \u0397 \u03c0\u03b1\u03c1\u03b1\u03c4\u03ae\u03c1\u03b7\u03c3\u03b7 \u03ad\u03c7\u03b5\u03b9 \u03ac\u03bc\u03b5\u03c3\u03b7 \u03c3\u03b7\u03bc\u03b1\u03c3\u03af\u03b1 \u03b3\u03b9\u03b1 customer support, \u03c0\u03c9\u03bb\u03ae\u03c3\u03b5\u03b9\u03c2, \u03b5\u03c3\u03c9\u03c4\u03b5\u03c1\u03b9\u03ba\u03ae \u03b3\u03bd\u03ce\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae \u03c0\u03b5\u03c1\u03b9\u03b5\u03c7\u03bf\u03bc\u03ad\u03bd\u03bf\u03c5: \u03ad\u03bd\u03b1 aggregate score \u03c4\u03bf\u03c5 \u03c3\u03c4\u03b5\u03bd\u03bf\u03cd domain \u03b4\u03b5\u03bd \u03b1\u03c1\u03ba\u03b5\u03af \u03b3\u03b9\u03b1 \u03bd\u03b1 \u03b1\u03c0\u03bf\u03b4\u03b5\u03af\u03be\u03b5\u03b9 \u03cc\u03c4\u03b9 \u03bf \u03b3\u03b5\u03bd\u03b9\u03ba\u03cc\u03c2 \u03b2\u03bf\u03b7\u03b8\u03cc\u03c2 \u03c0\u03b1\u03c1\u03ad\u03bc\u03b5\u03b9\u03bd\u03b5 \u03b1\u03be\u03b9\u03cc\u03c0\u03b9\u03c3\u03c4\u03bf\u03c2.<\/p>\n<p>\u03a4\u03bf \u03c0\u03c1\u03ce\u03c4\u03bf \u03bb\u03ac\u03b8\u03bf\u03c2 \u03b4\u03b9\u03ac\u03b3\u03bd\u03c9\u03c3\u03b7\u03c2 \u03b5\u03af\u03bd\u03b1\u03b9 \u03bd\u03b1 \u03bf\u03bd\u03bf\u03bc\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03ba\u03ac\u03b8\u03b5 \u03c0\u03c4\u03ce\u03c3\u03b7 \u00ab\u03ba\u03b1\u03c4\u03b1\u03c3\u03c4\u03c1\u03bf\u03c6\u03b9\u03ba\u03ae \u03bb\u03ae\u03b8\u03b7\u00bb. \u0391\u03bd \u03c4\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03b5\u03be\u03b1\u03ba\u03bf\u03bb\u03bf\u03c5\u03b8\u03b5\u03af \u03bd\u03b1 \u03b5\u03c0\u03b9\u03bb\u03ad\u03b3\u03b5\u03b9 \u03c4\u03b7 \u03c3\u03c9\u03c3\u03c4\u03ae \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7 \u03b1\u03bd\u03ac\u03bc\u03b5\u03c3\u03b1 \u03c3\u03b5 \u03c5\u03c0\u03bf\u03c8\u03b7\u03c6\u03af\u03bf\u03c5\u03c2, \u03b1\u03bb\u03bb\u03ac \u03b1\u03c0\u03bf\u03c4\u03c5\u03b3\u03c7\u03ac\u03bd\u03b5\u03b9 \u03bd\u03b1 \u03c4\u03b7\u03bd \u03c0\u03b1\u03c1\u03ac\u03b3\u03b5\u03b9 \u03c7\u03c9\u03c1\u03af\u03c2 \u03b2\u03bf\u03ae\u03b8\u03b5\u03b9\u03b1, \u03c4\u03cc\u03c4\u03b5 \u03c4\u03bf \u03bf\u03c1\u03b1\u03c4\u03cc \u03c3\u03c6\u03ac\u03bb\u03bc\u03b1 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b2\u03c1\u03af\u03c3\u03ba\u03b5\u03c4\u03b1\u03b9 \u03c3\u03c4\u03b7\u03bd \u03c0\u03c1\u03cc\u03c3\u03b2\u03b1\u03c3\u03b7, \u03c3\u03c4\u03b7\u03bd elicitation \u03c3\u03c5\u03bd\u03b8\u03ae\u03ba\u03b7 \u03ae \u03c3\u03c4\u03b7\u03bd \u03c4\u03b5\u03bb\u03b9\u03ba\u03ae \u03bc\u03bf\u03c1\u03c6\u03ae. \u0391\u03c5\u03c4\u03ae \u03b7 \u03b4\u03b9\u03ac\u03ba\u03c1\u03b9\u03c3\u03b7 \u03b4\u03b5\u03bd \u03b1\u03b8\u03c9\u03ce\u03bd\u03b5\u03b9 \u03c4\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf\u00b7 \u03b1\u03bb\u03bb\u03ac\u03b6\u03b5\u03b9 \u03c4\u03b7\u03bd \u03c4\u03b5\u03c7\u03bd\u03b9\u03ba\u03ae \u03b8\u03b5\u03c1\u03b1\u03c0\u03b5\u03af\u03b1 \u03ba\u03b1\u03b9 \u03c4\u03bf\u03bd \u03c4\u03c1\u03cc\u03c0\u03bf \u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7\u03c2.<\/p>\n<h2 id=\"anagnorisi-anaklisi-ekfrasi\">\u0391\u03bd\u03b1\u03b3\u03bd\u03ce\u03c1\u03b9\u03c3\u03b7, \u03b1\u03bd\u03ac\u03ba\u03bb\u03b7\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03ad\u03ba\u03c6\u03c1\u03b1\u03c3\u03b7<\/h2>\n<p>\u039f\u03b9 \u03c3\u03c5\u03b3\u03b3\u03c1\u03b1\u03c6\u03b5\u03af\u03c2 \u03c7\u03c9\u03c1\u03af\u03b6\u03bf\u03c5\u03bd \u03c4\u03b7 \u03c3\u03c5\u03bc\u03c0\u03b5\u03c1\u03b9\u03c6\u03bf\u03c1\u03ac \u03c3\u03b5 \u03c4\u03c1\u03af\u03b1 \u03c0\u03b1\u03c1\u03b1\u03c4\u03b7\u03c1\u03ae\u03c3\u03b9\u03bc\u03b1 \u03b5\u03c0\u03af\u03c0\u03b5\u03b4\u03b1. \u0397 <strong>\u041f\u0440\u0438\u0437\u043d\u0430\u043d\u0438\u0435<\/strong> \u03b5\u03bb\u03ad\u03b3\u03c7\u03b5\u03b9 \u03b1\u03bd \u03c4\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b5\u03c0\u03b9\u03bb\u03ad\u03be\u03b5\u03b9 \u03ae \u03bd\u03b1 \u03ba\u03b1\u03c4\u03b1\u03c4\u03ac\u03be\u03b5\u03b9 \u03c4\u03b7 \u03c3\u03c9\u03c3\u03c4\u03ae \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7 \u03b1\u03bd\u03ac\u03bc\u03b5\u03c3\u03b1 \u03c3\u03b5 \u03c5\u03c0\u03bf\u03c8\u03b7\u03c6\u03af\u03bf\u03c5\u03c2. \u0397 <strong>\u03b1\u03bd\u03ac\u03ba\u03bb\u03b7\u03c3\u03b7<\/strong> \u03b1\u03c0\u03b1\u03b9\u03c4\u03b5\u03af \u03bd\u03b1 \u03c0\u03b1\u03c1\u03b1\u03b3\u03ac\u03b3\u03b5\u03b9 \u03c4\u03b7\u03bd \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7 \u03c7\u03c9\u03c1\u03af\u03c2 \u03c5\u03c0\u03bf\u03c3\u03c4\u03ae\u03c1\u03b9\u03be\u03b7 \u03c5\u03c0\u03bf\u03c8\u03b7\u03c6\u03af\u03c9\u03bd. \u0397 <strong>\u03ad\u03ba\u03c6\u03c1\u03b1\u03c3\u03b7<\/strong> \u03b1\u03c6\u03bf\u03c1\u03ac \u03c4\u03bf \u03b1\u03bd \u03b1\u03c0\u03bf\u03b4\u03af\u03b4\u03b5\u03b9 \u03c4\u03b7 \u03b3\u03bd\u03ce\u03c3\u03b7 \u03c3\u03c4\u03b7 \u03bc\u03bf\u03c1\u03c6\u03ae \u03c0\u03bf\u03c5 \u03c0\u03b5\u03c1\u03b9\u03bc\u03ad\u03bd\u03b5\u03b9 \u03bf \u03c7\u03c1\u03ae\u03c3\u03c4\u03b7\u03c2, \u03ad\u03bd\u03b1 schema \u03ae \u03c4\u03bf metric.<\/p>\n<p>\u03a3\u03c4\u03bf \u03c0\u03bb\u03ae\u03c1\u03b5\u03c2 TriviaQA, \u03c4\u03bf Llama-3.1-8B \u03ad\u03c0\u03b5\u03c3\u03b5 \u03b1\u03c0\u03cc 65,03 \u03c3\u03b5 43,95 exact match \u03bc\u03b5\u03c4\u03ac \u03c4\u03bf SFT, \u03b5\u03bd\u03ce \u03bf\u03b9 \u03c0\u03bf\u03bb\u03bb\u03b1\u03c0\u03bb\u03ae\u03c2 \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ae\u03c2 \u03bc\u03b5\u03c4\u03c1\u03ae\u03c3\u03b5\u03b9\u03c2 MMLU \u03ad\u03bc\u03b5\u03b9\u03bd\u03b1\u03bd \u03c3\u03c4\u03b1\u03b8\u03b5\u03c1\u03ad\u03c2 \u03ae \u03b2\u03b5\u03bb\u03c4\u03b9\u03ce\u03b8\u03b7\u03ba\u03b1\u03bd \u03b5\u03bb\u03b1\u03c6\u03c1\u03ac. \u0395\u03c0\u03b5\u03b9\u03b4\u03ae \u03cc\u03bc\u03c9\u03c2 \u03b1\u03c5\u03c4\u03ac \u03c4\u03b1 benchmarks \u03b4\u03b9\u03b1\u03c6\u03ad\u03c1\u03bf\u03c5\u03bd \u03c3\u03b5 \u03c0\u03b5\u03c1\u03b9\u03b5\u03c7\u03cc\u03bc\u03b5\u03bd\u03bf \u03ba\u03b1\u03b9 format, \u03b7 \u03c3\u03cd\u03b3\u03ba\u03c1\u03b9\u03c3\u03b7 \u03b1\u03c0\u03cc \u03bc\u03cc\u03bd\u03b7 \u03c4\u03b7\u03c2 \u03b4\u03b5\u03bd \u03b1\u03c0\u03bf\u03b4\u03b5\u03b9\u03ba\u03bd\u03cd\u03b5\u03b9 \u03cc\u03c4\u03b9 \u03c4\u03bf \u03af\u03b4\u03b9\u03bf fact \u03c0\u03b1\u03c1\u03b1\u03bc\u03ad\u03bd\u03b5\u03b9 \u03c0\u03c1\u03bf\u03c3\u03b2\u03ac\u03c3\u03b9\u03bc\u03bf.<\/p>\n<p>\u0393\u03b9\u2019 \u03b1\u03c5\u03c4\u03cc \u03b7 \u03b5\u03c1\u03b3\u03b1\u03c3\u03af\u03b1 \u03ba\u03b1\u03c4\u03b1\u03c3\u03ba\u03b5\u03c5\u03ac\u03b6\u03b5\u03b9 \u03ba\u03b1\u03b9 same-fact probes: \u03c4\u03bf \u03af\u03b4\u03b9\u03bf \u03b1\u03bd\u03c4\u03b9\u03ba\u03b5\u03af\u03bc\u03b5\u03bd\u03bf \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7\u03c2 \u03b5\u03bb\u03ad\u03b3\u03c7\u03b5\u03c4\u03b1\u03b9 \u03c9\u03c2 \u03b1\u03bd\u03bf\u03b9\u03ba\u03c4\u03ae \u03b5\u03c1\u03ce\u03c4\u03b7\u03c3\u03b7, \u03c9\u03c2 \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ae \u03b1\u03bd\u03ac\u03bc\u03b5\u03c3\u03b1 \u03c3\u03b5 \u03c5\u03c0\u03bf\u03c8\u03b7\u03c6\u03af\u03bf\u03c5\u03c2 \u03ba\u03b1\u03b9 \u03c9\u03c2 ranking \u03c5\u03c0\u03cc teacher forcing. \u0395\u03ba\u03b5\u03af \u03b7 \u03b1\u03bd\u03bf\u03b9\u03ba\u03c4\u03ae \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae \u03bc\u03b5\u03b9\u03ce\u03bd\u03b5\u03c4\u03b1\u03b9 \u03b1\u03b9\u03c3\u03b8\u03b7\u03c4\u03ac, \u03b5\u03bd\u03ce \u03b7 multiple-choice accuracy \u03b1\u03bb\u03bb\u03ac\u03b6\u03b5\u03b9 \u03bf\u03c1\u03b9\u03b1\u03ba\u03ac \u03ba\u03b1\u03b9 \u03b7 \u03ba\u03b1\u03c4\u03ac\u03c4\u03b1\u03be\u03b7 \u03c4\u03bf\u03c5 \u03c3\u03c9\u03c3\u03c4\u03bf\u03cd \u03c0\u03c1\u03ce\u03c4\u03bf\u03c5 token \u03bc\u03ad\u03bd\u03b5\u03b9 \u03ba\u03bf\u03bd\u03c4\u03ac \u03c3\u03c4\u03b7 \u03b2\u03ac\u03c3\u03b7. \u03a4\u03bf evidence \u03c3\u03c4\u03b7\u03c1\u03af\u03b6\u03b5\u03b9 \u03c4\u03bf\u03bd \u03cc\u03c1\u03bf <em>factual access failure<\/em>: \u03b5\u03c0\u03b9\u03bb\u03b5\u03ba\u03c4\u03b9\u03ba\u03ae \u03b1\u03c0\u03bf\u03c4\u03c5\u03c7\u03af\u03b1 \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae\u03c2, \u03cc\u03c7\u03b9 \u03b1\u03c5\u03c4\u03cc\u03bc\u03b1\u03c4\u03b7 \u03b1\u03c0\u03cc\u03b4\u03b5\u03b9\u03be\u03b7 \u03cc\u03c4\u03b9 \u03c4\u03bf fact \u03ad\u03c0\u03b1\u03c8\u03b5 \u03bd\u03b1 \u03ba\u03c9\u03b4\u03b9\u03ba\u03bf\u03c0\u03bf\u03b9\u03b5\u03af\u03c4\u03b1\u03b9.<\/p>\n<aside class=\"td-article-note\">\n<p><strong>\u03a0\u03c1\u03cc\u03c3\u03b2\u03b1\u03c3\u03b7 \u03b4\u03b5\u03bd \u03c3\u03b7\u03bc\u03b1\u03af\u03bd\u03b5\u03b9 \u03b1\u03c0\u03bf\u03b8\u03ae\u03ba\u03b5\u03c5\u03c3\u03b7:<\/strong> \u03bf\u03b9 constrained probes \u03b4\u03b5\u03af\u03c7\u03bd\u03bf\u03c5\u03bd \u03cc\u03c4\u03b9 \u03bc\u03b9\u03b1 \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7 \u03c0\u03b1\u03c1\u03b1\u03bc\u03ad\u03bd\u03b5\u03b9 \u03b1\u03bd\u03b1\u03b3\u03bd\u03c9\u03c1\u03af\u03c3\u03b9\u03bc\u03b7, \u03b1\u03bb\u03bb\u03ac \u03b4\u03b5\u03bd \u03b1\u03c0\u03bf\u03ba\u03b1\u03bb\u03cd\u03c0\u03c4\u03bf\u03c5\u03bd \u03c0\u03bb\u03ae\u03c1\u03c9\u03c2 \u03c0\u03bf\u03cd \u03ae \u03c0\u03ce\u03c2 \u03ba\u03c9\u03b4\u03b9\u03ba\u03bf\u03c0\u03bf\u03b9\u03b5\u03af\u03c4\u03b1\u03b9 \u03b7 \u03b3\u03bd\u03ce\u03c3\u03b7. \u03a4\u03bf RAD \u03c3\u03c4\u03b7\u03bd AI \u03b5\u03af\u03bd\u03b1\u03b9 \u03c3\u03c5\u03bc\u03c0\u03b5\u03c1\u03b9\u03c6\u03bf\u03c1\u03b9\u03ba\u03ae \u03b4\u03b9\u03ac\u03b3\u03bd\u03c9\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03c4\u03b5\u03c7\u03bd\u03b9\u03ba\u03ae \u03b4\u03b9\u03b1\u03c4\u03ae\u03c1\u03b7\u03c3\u03b7\u03c2 \u03c4\u03b7\u03c2 \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae\u03c2, \u03cc\u03c7\u03b9 \u03bd\u03b5\u03c5\u03c1\u03bf\u03b5\u03c0\u03b9\u03c3\u03c4\u03b7\u03bc\u03bf\u03bd\u03b9\u03ba\u03ae \u03b1\u03c0\u03cc\u03b4\u03b5\u03b9\u03be\u03b7 \u03bc\u03bd\u03ae\u03bc\u03b7\u03c2.<\/p>\n<\/aside>\n<p>\u0397 \u03b4\u03b9\u03ac\u03ba\u03c1\u03b9\u03c3\u03b7 \u03c4\u03b1\u03b9\u03c1\u03b9\u03ac\u03b6\u03b5\u03b9 \u03bc\u03b5 \u03ad\u03bd\u03b1 \u03b5\u03c5\u03c1\u03cd\u03c4\u03b5\u03c1\u03bf \u03bc\u03ac\u03b8\u03b7\u03bc\u03b1 \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7 agentic \u03c3\u03c5\u03c3\u03c4\u03b7\u03bc\u03ac\u03c4\u03c9\u03bd: \u03c4\u03bf observed failure \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 decomposition \u03c0\u03c1\u03b9\u03bd \u03b3\u03af\u03bd\u03b5\u03b9 \u03c0\u03b1\u03c1\u03ad\u03bc\u03b2\u03b1\u03c3\u03b7. \u0397 \u03af\u03b4\u03b9\u03b1 \u03c0\u03b5\u03b9\u03b8\u03b1\u03c1\u03c7\u03af\u03b1 \u03b5\u03bc\u03c6\u03b1\u03bd\u03af\u03b6\u03b5\u03c4\u03b1\u03b9 \u03c3\u03c4\u03b7\u03bd <a href=\"https:\/\/twodots.gr\/aces-ai-skill-evaluation-skill-lift\/\">\u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7 skill lift \u03b3\u03b9\u03b1 AI agents<\/a>, \u03cc\u03c0\u03bf\u03c5 \u03c4\u03bf \u03b1\u03c0\u03bf\u03c4\u03ad\u03bb\u03b5\u03c3\u03bc\u03b1 \u03b5\u03bd\u03cc\u03c2 \u03b5\u03c1\u03b3\u03b1\u03bb\u03b5\u03af\u03bf\u03c5 \u03c3\u03c5\u03b3\u03ba\u03c1\u03af\u03bd\u03b5\u03c4\u03b1\u03b9 \u03bc\u03b5 paired baseline \u03b1\u03bd\u03c4\u03af \u03bd\u03b1 \u03b1\u03c0\u03bf\u03b4\u03af\u03b4\u03b5\u03c4\u03b1\u03b9 \u03c3\u03b5 \u03bc\u03af\u03b1 \u03b1\u03c3\u03b1\u03c6\u03ae \u00ab\u03b9\u03ba\u03b1\u03bd\u03cc\u03c4\u03b7\u03c4\u03b1\u00bb.<\/p>\n<h2 id=\"format-apotyxies\">\u03a0\u03cc\u03c4\u03b5 \u03c4\u03bf \u03bb\u03ac\u03b8\u03bf\u03c2 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b6\u03ae\u03c4\u03b7\u03bc\u03b1 format<\/h2>\n<p>\u0397 \u03b1\u03bd\u03ac\u03bb\u03c5\u03c3\u03b7 \u03b5\u03be\u03b5\u03c4\u03ac\u03b6\u03b5\u03b9 300 \u03c0\u03b5\u03c1\u03b9\u03c0\u03c4\u03ce\u03c3\u03b5\u03b9\u03c2 TriviaQA \u03c3\u03c4\u03b9\u03c2 \u03bf\u03c0\u03bf\u03af\u03b5\u03c2 \u03b7 \u03b2\u03b1\u03c3\u03b9\u03ba\u03ae \u03ad\u03ba\u03b4\u03bf\u03c3\u03b7 \u03ae\u03c4\u03b1\u03bd \u03c3\u03c9\u03c3\u03c4\u03ae \u03ba\u03b1\u03b9 \u03b7 SFT \u03ad\u03ba\u03b4\u03bf\u03c3\u03b7 \u03bb\u03ac\u03b8\u03bf\u03c2 \u03bc\u03b5 \u03b2\u03ac\u03c3\u03b7 exact match. \u03a4\u03b1 outputs \u03c4\u03b1\u03be\u03b9\u03bd\u03bf\u03bc\u03ae\u03b8\u03b7\u03ba\u03b1\u03bd \u03c3\u03b5 \u03c4\u03ad\u03c3\u03c3\u03b5\u03c1\u03b9\u03c2 \u03ba\u03b1\u03c4\u03b7\u03b3\u03bf\u03c1\u03af\u03b5\u03c2: \u03bb\u03ac\u03b8\u03bf\u03c2 \u03bf\u03bd\u03c4\u03cc\u03c4\u03b7\u03c4\u03b1, \u03b1\u03c3\u03c4\u03bf\u03c7\u03af\u03b1 \u03bc\u03bf\u03c1\u03c6\u03ae\u03c2 \u03ae \u03c5\u03c0\u03b5\u03c1\u03b2\u03bf\u03bb\u03b9\u03ba\u03ae \u03c6\u03bb\u03c5\u03b1\u03c1\u03af\u03b1, \u03c3\u03b7\u03bc\u03b1\u03c3\u03b9\u03bf\u03bb\u03bf\u03b3\u03b9\u03ba\u03ac \u03b1\u03c0\u03bf\u03b4\u03b5\u03ba\u03c4\u03ae \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7 \u03c0\u03bf\u03c5 \u03b1\u03c0\u03bf\u03c1\u03c1\u03af\u03c6\u03b8\u03b7\u03ba\u03b5 \u03b1\u03c0\u03cc \u03c4\u03bf metric \u03ba\u03b1\u03b9 \u03bc\u03b7 \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7 \u03ae \u03ac\u03c1\u03bd\u03b7\u03c3\u03b7.<\/p>\n<p>\u039f\u03b9 \u03b1\u03c3\u03c4\u03bf\u03c7\u03af\u03b5\u03c2 format \u03ae verbosity \u03b1\u03bd\u03c4\u03b9\u03c3\u03c4\u03bf\u03b9\u03c7\u03bf\u03cd\u03c3\u03b1\u03bd \u03c3\u03c4\u03bf 77,3% \u03b1\u03c5\u03c4\u03bf\u03cd \u03c4\u03bf\u03c5 \u03b5\u03c0\u03b9\u03bb\u03b5\u03b3\u03bc\u03ad\u03bd\u03bf\u03c5 \u03b4\u03b5\u03af\u03b3\u03bc\u03b1\u03c4\u03bf\u03c2. \u039f\u03b9 \u03b5\u03c4\u03b9\u03ba\u03ad\u03c4\u03b5\u03c2 \u03c3\u03c5\u03bc\u03c6\u03ce\u03bd\u03b7\u03c3\u03b1\u03bd \u03c3\u03b5 97,3% \u03c4\u03c9\u03bd \u03c0\u03b5\u03c1\u03b9\u03c0\u03c4\u03ce\u03c3\u03b5\u03c9\u03bd \u03bc\u03b5 \u03b1\u03bd\u03b5\u03be\u03ac\u03c1\u03c4\u03b7\u03c4\u03bf LLM judge \u03c0\u03bf\u03c5 \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b1\u03bd \u03bf\u03b9 \u03c3\u03c5\u03b3\u03b3\u03c1\u03b1\u03c6\u03b5\u03af\u03c2. \u0388\u03bd\u03b1 \u03b1\u03c0\u03bb\u03cc prompt \u03c4\u03b5\u03c3\u03c3\u03ac\u03c1\u03c9\u03bd \u03c0\u03b1\u03c1\u03b1\u03b4\u03b5\u03b9\u03b3\u03bc\u03ac\u03c4\u03c9\u03bd \u03b1\u03bd\u03ad\u03ba\u03c4\u03b7\u03c3\u03b5 \u03c4\u03bf 90,0% \u03c4\u03c9\u03bd \u03af\u03b4\u03b9\u03c9\u03bd cases, \u03ad\u03bd\u03b4\u03b5\u03b9\u03be\u03b7 \u03cc\u03c4\u03b9 \u03c0\u03bf\u03bb\u03bb\u03ad\u03c2 \u03b1\u03c0\u03bf\u03c4\u03c5\u03c7\u03af\u03b5\u03c2 \u03ae\u03c4\u03b1\u03bd \u03b5\u03c5\u03b1\u03af\u03c3\u03b8\u03b7\u03c4\u03b5\u03c2 \u03c3\u03c4\u03bf\u03bd \u03c4\u03c1\u03cc\u03c0\u03bf elicitation.<\/p>\n<div class=\"td-chart td-chart--metrics\">\n<div class=\"td-chart-head\">\n<p class=\"td-chart-title\">\u03a4\u03b9 \u03bc\u03b5\u03c4\u03c1\u03ae\u03b8\u03b7\u03ba\u03b5 \u03c3\u03c4\u03bf RAD<\/p>\n<p class=\"td-chart-subtitle\">\u039f\u03b9 \u03c4\u03b9\u03bc\u03ad\u03c2 \u03b1\u03bd\u03ae\u03ba\u03bf\u03c5\u03bd \u03c3\u03c4\u03b1 \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03b1 experiments \u03c4\u03b7\u03c2 \u03b5\u03c1\u03b3\u03b1\u03c3\u03af\u03b1\u03c2. \u03a4\u03b1 \u03b4\u03cd\u03bf \u03c0\u03bf\u03c3\u03bf\u03c3\u03c4\u03ac \u03b1\u03c6\u03bf\u03c1\u03bf\u03cd\u03bd \u03c4\u03bf \u03b5\u03c0\u03b9\u03bb\u03b5\u03b3\u03bc\u03ad\u03bd\u03bf \u03b4\u03b5\u03af\u03b3\u03bc\u03b1 300 Base-correct\/SFT-wrong \u03c0\u03b5\u03c1\u03b9\u03c0\u03c4\u03ce\u03c3\u03b5\u03c9\u03bd \u03ba\u03b1\u03b9 \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03b3\u03b5\u03bd\u03b9\u03ba\u03ac rates \u03b3\u03b9\u03b1 \u03cc\u03bb\u03b1 \u03c4\u03b1 LLMs.<\/p>\n<\/div>\n<div class=\"td-chart-body\">\n<div class=\"td-metric-grid\">\n<div class=\"td-metric-card\"><span class=\"td-metric-value\">65,03 \u2192 43,95<\/span><span class=\"td-metric-label\">TriviaQA EM, Llama Base \u2192 Standard SFT<\/span><\/div>\n<div class=\"td-metric-card\"><span class=\"td-metric-value\">51,62<\/span><span class=\"td-metric-label\">TriviaQA EM \u03bc\u03b5 RAD \u03c3\u03c4\u03bf Llama-3.1-8B<\/span><\/div>\n<div class=\"td-metric-card\"><span class=\"td-metric-value\">77,3%<\/span><span class=\"td-metric-label\">Format \u03ae verbosity mismatch \u03c3\u03c4\u03bf \u03b4\u03b5\u03af\u03b3\u03bc\u03b1 300 cases<\/span><\/div>\n<div class=\"td-metric-card\"><span class=\"td-metric-value\">90,0%<\/span><span class=\"td-metric-label\">Cases \u03c0\u03bf\u03c5 \u03b1\u03bd\u03ad\u03ba\u03c4\u03b7\u03c3\u03b5 \u03c4\u03bf 4-shot prompt \u03c3\u03c4\u03bf \u03af\u03b4\u03b9\u03bf \u03b4\u03b5\u03af\u03b3\u03bc\u03b1<\/span><\/div>\n<\/div>\n<\/div>\n<\/div>\n<p>\u0391\u03c5\u03c4\u03ac \u03c4\u03b1 \u03c0\u03bf\u03c3\u03bf\u03c3\u03c4\u03ac \u03b4\u03b5\u03bd \u03c3\u03b7\u03bc\u03b1\u03af\u03bd\u03bf\u03c5\u03bd \u03cc\u03c4\u03b9 \u03c4\u03bf prompting \u03bb\u03cd\u03bd\u03b5\u03b9 \u03ba\u03ac\u03b8\u03b5 factual error. \u03a4\u03bf sample \u03b5\u03c0\u03b9\u03bb\u03ad\u03c7\u03b8\u03b7\u03ba\u03b5 \u03b1\u03ba\u03c1\u03b9\u03b2\u03ce\u03c2 \u03b5\u03c0\u03b5\u03b9\u03b4\u03ae \u03b7 \u03b2\u03ac\u03c3\u03b7 \u03ae\u03c4\u03b1\u03bd \u03c3\u03c9\u03c3\u03c4\u03ae \u03ba\u03b1\u03b9 \u03c4\u03bf SFT output \u03b1\u03c0\u03ad\u03c4\u03c5\u03c7\u03b5 \u03c3\u03c4\u03bf exact match, \u03b5\u03bd\u03ce \u03b7 \u03b5\u03c1\u03b3\u03b1\u03c3\u03af\u03b1 \u03ba\u03b1\u03c4\u03b1\u03b3\u03c1\u03ac\u03c6\u03b5\u03b9 \u03ba\u03b1\u03b9 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ad\u03c2 \u03bb\u03ac\u03b8\u03bf\u03c2 \u03bf\u03bd\u03c4\u03cc\u03c4\u03b7\u03c4\u03b5\u03c2. \u03a3\u03b5 production, \u03b7 \u03c3\u03b7\u03bc\u03b1\u03c3\u03b9\u03bf\u03bb\u03bf\u03b3\u03b9\u03ba\u03ae \u03ba\u03c1\u03af\u03c3\u03b7, \u03c4\u03bf schema validation \u03ba\u03b1\u03b9 \u03b7 \u03b1\u03bd\u03b8\u03c1\u03ce\u03c0\u03b9\u03bd\u03b7 \u03b5\u03c0\u03b9\u03b8\u03b5\u03ce\u03c1\u03b7\u03c3\u03b7 \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03c3\u03c5\u03bc\u03c0\u03bb\u03b7\u03c1\u03ce\u03bd\u03bf\u03c5\u03bd \u03c4\u03bf exact match, \u03cc\u03c7\u03b9 \u03bd\u03b1 \u03c4\u03bf \u03b1\u03bd\u03c4\u03b9\u03ba\u03b1\u03b8\u03b9\u03c3\u03c4\u03bf\u03cd\u03bd \u03bc\u03b5 \u03ad\u03bd\u03b1 \u03ac\u03bb\u03bb\u03bf \u03bc\u03bf\u03bd\u03b1\u03b4\u03b9\u03ba\u03cc metric.<\/p>\n<h2 id=\"ti-einai-rad\">\u03a4\u03b9 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c4\u03bf Recall-Anchored Distillation<\/h2>\n<p>\u0393\u03b9\u03b1 \u03bd\u03b1 \u03c0\u03b5\u03c1\u03b9\u03bf\u03c1\u03af\u03c3\u03bf\u03c5\u03bd \u03c4\u03b7 \u03bc\u03b5\u03c4\u03b1\u03c4\u03cc\u03c0\u03b9\u03c3\u03b7, \u03bf\u03b9 \u03b5\u03c1\u03b5\u03c5\u03bd\u03b7\u03c4\u03ad\u03c2 \u03c0\u03c1\u03bf\u03c4\u03b5\u03af\u03bd\u03bf\u03c5\u03bd Recall-Anchored Distillation. \u03a4\u03bf RAD \u03c3\u03c5\u03bd\u03b4\u03c5\u03ac\u03b6\u03b5\u03b9 \u03b4\u03cd\u03bf \u03c1\u03bf\u03ad\u03c2 \u03b5\u03ba\u03c0\u03b1\u03af\u03b4\u03b5\u03c5\u03c3\u03b7\u03c2: \u03c4\u03b7\u03bd \u03ba\u03b1\u03bd\u03bf\u03bd\u03b9\u03ba\u03ae supervised loss \u03c4\u03bf\u03c5 target domain \u03ba\u03b1\u03b9 \u03bc\u03af\u03b1 OOD \u03c1\u03bf\u03ae \u03bc\u03b5 \u03bc\u03b7 \u03b5\u03c0\u03b9\u03c3\u03b7\u03bc\u03b1\u03c3\u03bc\u03ad\u03bd\u03bf \u03b3\u03b5\u03bd\u03b9\u03ba\u03cc \u03ba\u03b5\u03af\u03bc\u03b5\u03bd\u03bf. \u03a3\u03c4\u03b7 \u03b4\u03b5\u03cd\u03c4\u03b5\u03c1\u03b7 \u03c1\u03bf\u03ae, \u03c4\u03bf \u03c0\u03c1\u03bf\u03c3\u03b1\u03c1\u03bc\u03bf\u03c3\u03bc\u03ad\u03bd\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03bc\u03b1\u03b8\u03b1\u03af\u03bd\u03b5\u03b9 \u03bd\u03b1 \u03c0\u03b1\u03c1\u03b1\u03bc\u03ad\u03bd\u03b5\u03b9 \u03ba\u03bf\u03bd\u03c4\u03ac \u03c3\u03c4\u03b7 soft next-token distribution \u03c4\u03b7\u03c2 \u03b1\u03c1\u03c7\u03b9\u03ba\u03ae\u03c2 \u03c4\u03bf\u03c5 \u03ad\u03ba\u03b4\u03bf\u03c3\u03b7\u03c2.<\/p>\n<p>\u03a4\u03bf anchor corpus \u03c0\u03b5\u03c1\u03b9\u03bb\u03b1\u03bc\u03b2\u03ac\u03bd\u03b5\u03b9 10.000 \u03b6\u03b5\u03cd\u03b3\u03b7 prefix\u2013continuation \u03b1\u03c0\u03cc Wikipedia-style \u03ba\u03b5\u03af\u03bc\u03b5\u03bd\u03bf. \u03a4\u03bf prefix \u03b4\u03af\u03bd\u03b5\u03b9 \u03c3\u03c5\u03bc\u03c6\u03c1\u03b1\u03b6\u03cc\u03bc\u03b5\u03bd\u03b1 \u03ba\u03b1\u03b9 \u03b7 \u03c3\u03c5\u03bd\u03ad\u03c7\u03b5\u03b9\u03b1 \u03bf\u03c1\u03af\u03b6\u03b5\u03b9 \u03bc\u03cc\u03bd\u03bf \u03c4\u03b9\u03c2 token positions \u03cc\u03c0\u03bf\u03c5 \u03b3\u03af\u03bd\u03b5\u03c4\u03b1\u03b9 \u03b7 \u03b5\u03c5\u03b8\u03c5\u03b3\u03c1\u03ac\u03bc\u03bc\u03b9\u03c3\u03b7. \u039f\u03b9 \u03c3\u03c5\u03b3\u03b3\u03c1\u03b1\u03c6\u03b5\u03af\u03c2 \u03c6\u03b9\u03bb\u03c4\u03c1\u03ac\u03c1\u03bf\u03c5\u03bd \u03b5\u03c1\u03c9\u03c4\u03ae\u03c3\u03b5\u03b9\u03c2, answer strings \u03ba\u03b1\u03b9 aliases \u03b1\u03c0\u03cc PopQA \u03ba\u03b1\u03b9 TriviaQA \u03b3\u03b9\u03b1 \u03bd\u03b1 \u03bc\u03b5\u03b9\u03ce\u03c3\u03bf\u03c5\u03bd \u03c4\u03bf\u03bd \u03ba\u03af\u03bd\u03b4\u03c5\u03bd\u03bf contamination.<\/p>\n<p>\u0397 \u03bc\u03ad\u03b8\u03bf\u03b4\u03bf\u03c2 \u03b4\u03b5\u03bd \u03b6\u03b7\u03c4\u03ac gold OOD answers, \u03bd\u03ad\u03bf labeled factual dataset \u03ae \u03b5\u03be\u03c9\u03c4\u03b5\u03c1\u03b9\u03ba\u03cc judge. \u039f teacher \u03b4\u03b5\u03bd \u03b4\u03af\u03bd\u03b5\u03b9 \u03bc\u03af\u03b1 \u03c3\u03ba\u03bb\u03b7\u03c1\u03ae \u00ab\u03c3\u03c9\u03c3\u03c4\u03ae\u00bb \u03c3\u03c5\u03bd\u03ad\u03c7\u03b5\u03b9\u03b1\u00b7 \u03c0\u03b1\u03c1\u03ad\u03c7\u03b5\u03b9 \u03c4\u03b7 \u03c3\u03c7\u03b5\u03c4\u03b9\u03ba\u03ae \u03c0\u03b9\u03b8\u03b1\u03bd\u03cc\u03c4\u03b7\u03c4\u03b1 \u03c0\u03bf\u03bb\u03bb\u03ce\u03bd \u03c0\u03b9\u03b8\u03b1\u03bd\u03ce\u03bd \u03b5\u03c0\u03cc\u03bc\u03b5\u03bd\u03c9\u03bd tokens. \u0388\u03c4\u03c3\u03b9 \u03c4\u03bf preservation signal \u03b1\u03c6\u03bf\u03c1\u03ac \u03c4\u03b7 \u03c3\u03c5\u03bc\u03c0\u03b5\u03c1\u03b9\u03c6\u03bf\u03c1\u03ac \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae\u03c2 \u03c4\u03b7\u03c2 \u03b2\u03ac\u03c3\u03b7\u03c2 \u03c0\u03ac\u03bd\u03c9 \u03c3\u03b5 \u03b3\u03b5\u03bd\u03b9\u03ba\u03cc \u03ba\u03b5\u03af\u03bc\u03b5\u03bd\u03bf \u03ba\u03b1\u03b9 \u03cc\u03c7\u03b9 \u03b1\u03c0\u03bb\u03ce\u03c2 \u03bd\u03ad\u03b1 \u03ad\u03ba\u03b8\u03b5\u03c3\u03b7 \u03c3\u03c4\u03bf \u03af\u03b4\u03b9\u03bf corpus.<\/p>\n<h2 id=\"teacher-student\">\u0388\u03bd\u03b1\u03c2 teacher \u03ba\u03b1\u03b9 \u03ad\u03bd\u03b1\u03c2 student \u03c3\u03c4\u03bf \u03af\u03b4\u03b9\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf<\/h2>\n<p>\u0397 \u03c5\u03bb\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7 \u03b1\u03be\u03b9\u03bf\u03c0\u03bf\u03b9\u03b5\u03af \u03c4\u03bf\u03bd \u03b4\u03b9\u03b1\u03ba\u03cc\u03c0\u03c4\u03b7 \u03c4\u03bf\u03c5 LoRA adapter. \u039c\u03b5 \u03b1\u03c0\u03b5\u03bd\u03b5\u03c1\u03b3\u03bf\u03c0\u03bf\u03b9\u03b7\u03bc\u03ad\u03bd\u03bf adapter, \u03c4\u03bf \u03c0\u03b1\u03b3\u03c9\u03bc\u03ad\u03bd\u03bf base model \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03b5\u03af \u03c9\u03c2 teacher \u03ba\u03b1\u03b9 \u03c0\u03b1\u03c1\u03ac\u03b3\u03b5\u03b9 logits \u03c7\u03c9\u03c1\u03af\u03c2 gradients. \u039c\u03b5 \u03b5\u03bd\u03b5\u03c1\u03b3\u03bf\u03c0\u03bf\u03b9\u03b7\u03bc\u03ad\u03bd\u03bf adapter, \u03b7 \u03af\u03b4\u03b9\u03b1 \u03b1\u03c1\u03c7\u03b9\u03c4\u03b5\u03ba\u03c4\u03bf\u03bd\u03b9\u03ba\u03ae \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03b5\u03af \u03c9\u03c2 student \u03ba\u03b1\u03b9 \u03b4\u03ad\u03c7\u03b5\u03c4\u03b1\u03b9 gradients. \u0394\u03b5\u03bd \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03b4\u03b5\u03cd\u03c4\u03b5\u03c1\u03bf \u03c0\u03bb\u03ae\u03c1\u03b5\u03c2 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03c3\u03c4\u03b7 \u03bc\u03bd\u03ae\u03bc\u03b7.<\/p>\n<p>\u0393\u03b9\u03b1 \u03c4\u03b1 target-domain batches \u03c5\u03c0\u03bf\u03bb\u03bf\u03b3\u03af\u03b6\u03b5\u03c4\u03b1\u03b9 \u03b7 \u03c3\u03c5\u03bd\u03b7\u03b8\u03b9\u03c3\u03bc\u03ad\u03bd\u03b7 cross-entropy loss. \u0393\u03b9\u03b1 \u03ba\u03ac\u03b8\u03b5 OOD anchor batch, \u03b7 \u03af\u03b4\u03b9\u03b1 \u03b1\u03ba\u03bf\u03bb\u03bf\u03c5\u03b8\u03af\u03b1 \u03c0\u03b5\u03c1\u03bd\u03ac \u03b4\u03cd\u03bf \u03c6\u03bf\u03c1\u03ad\u03c2: \u03c0\u03c1\u03ce\u03c4\u03b1 adapter-off \u03ba\u03b1\u03b9 \u03bc\u03b5\u03c4\u03ac adapter-on. \u0397 student distribution \u03b5\u03c5\u03b8\u03c5\u03b3\u03c1\u03b1\u03bc\u03bc\u03af\u03b6\u03b5\u03c4\u03b1\u03b9 \u03bc\u03b5 \u03c4\u03b7\u03bd base distribution \u03bc\u03ad\u03c3\u03c9 reverse KL \u03bc\u03cc\u03bd\u03bf \u03c3\u03c4\u03b1 continuation tokens. \u0397 \u03b1\u03bd\u03ac token \u03c0\u03bf\u03b9\u03bd\u03ae \u03b3\u03af\u03bd\u03b5\u03c4\u03b1\u03b9 clipping, \u03ce\u03c3\u03c4\u03b5 \u03bb\u03af\u03b3\u03b5\u03c2 \u03bc\u03b5\u03b3\u03ac\u03bb\u03b5\u03c2 \u03b1\u03c0\u03bf\u03ba\u03bb\u03af\u03c3\u03b5\u03b9\u03c2 \u03bd\u03b1 \u03bc\u03b7 \u03bc\u03bf\u03bd\u03bf\u03c0\u03c9\u03bb\u03bf\u03cd\u03bd \u03c4\u03bf objective.<\/p>\n<p>\u0397 \u03ba\u03bf\u03b9\u03bd\u03ae objective \u03b5\u03af\u03bd\u03b1\u03b9 <em>L<sub>RAD<\/sub> = L<sub>SFT<\/sub> + \u03b1L<sub>KP<\/sub><\/em>. \u039f\u03b9 \u03c0\u03c1\u03bf\u03b5\u03c0\u03b9\u03bb\u03b5\u03b3\u03bc\u03ad\u03bd\u03b5\u03c2 \u03c4\u03b9\u03bc\u03ad\u03c2 \u03c4\u03b7\u03c2 \u03b5\u03c1\u03b3\u03b1\u03c3\u03af\u03b1\u03c2 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b1 = 1,5 \u03ba\u03b1\u03b9 \u03c4 = 5,0. \u03a4\u03b1 ablations \u03b4\u03b5\u03af\u03c7\u03bd\u03bf\u03c5\u03bd \u03cc\u03c4\u03b9 \u03b8\u03b5\u03c4\u03b9\u03ba\u03ae \u03b1\u03b3\u03ba\u03cd\u03c1\u03c9\u03c3\u03b7 \u03b2\u03b5\u03bb\u03c4\u03b9\u03ce\u03bd\u03b5\u03b9 \u03c4\u03bf TriviaQA \u03ba\u03b1\u03b9 \u03c4\u03bf PopQA, \u03b1\u03bb\u03bb\u03ac \u03c4\u03b1 \u03ba\u03ad\u03c1\u03b4\u03b7 \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03bc\u03bf\u03bd\u03bf\u03c4\u03bf\u03bd\u03b9\u03ba\u03ac \u03cc\u03c3\u03bf \u03b1\u03c5\u03be\u03ac\u03bd\u03b5\u03c4\u03b1\u03b9 \u03c4\u03bf \u03b1. \u0386\u03c1\u03b1 \u03c4\u03bf 1,5 \u03b5\u03af\u03bd\u03b1\u03b9 stable default \u03c4\u03bf\u03c5 \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03bf\u03c5 setup, \u03cc\u03c7\u03b9 \u03ba\u03b1\u03b8\u03bf\u03bb\u03b9\u03ba\u03ac \u03b2\u03ad\u03bb\u03c4\u03b9\u03c3\u03c4\u03b7 \u03c1\u03cd\u03b8\u03bc\u03b9\u03c3\u03b7.<\/p>\n<h2 id=\"replay-sygkrisi\">\u0393\u03b9\u03b1\u03c4\u03af \u03c4\u03bf \u03b1\u03c0\u03bb\u03cc replay \u03b4\u03b5\u03bd \u03b1\u03c1\u03ba\u03b5\u03af<\/h2>\n<p>\u039c\u03b9\u03b1 \u03c6\u03c5\u03c3\u03b9\u03ba\u03ae \u03b5\u03bd\u03b1\u03bb\u03bb\u03b1\u03ba\u03c4\u03b9\u03ba\u03ae \u03b5\u03af\u03bd\u03b1\u03b9 \u03bd\u03b1 \u03b1\u03bd\u03b1\u03bc\u03b5\u03b9\u03c7\u03b8\u03b5\u03af \u03c4\u03bf \u03af\u03b4\u03b9\u03bf \u03b3\u03b5\u03bd\u03b9\u03ba\u03cc \u03ba\u03b5\u03af\u03bc\u03b5\u03bd\u03bf \u03c3\u03c4\u03bf fine-tuning \u03bc\u03b5 hard-label language-modeling loss. \u0397 \u03b5\u03c1\u03b3\u03b1\u03c3\u03af\u03b1 \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03b5\u03af \u03b1\u03ba\u03c1\u03b9\u03b2\u03ce\u03c2 \u03b1\u03c5\u03c4\u03cc \u03c4\u03bf replay \u03c9\u03c2 baseline, \u03ce\u03c3\u03c4\u03b5 \u03bd\u03b1 \u03be\u03b5\u03c7\u03c9\u03c1\u03af\u03c3\u03b5\u03b9 \u03c4\u03b7\u03bd \u03b5\u03c0\u03af\u03b4\u03c1\u03b1\u03c3\u03b7 \u03c4\u03b7\u03c2 \u03c0\u03c1\u03cc\u03c3\u03b8\u03b5\u03c4\u03b7\u03c2 \u03ad\u03ba\u03b8\u03b5\u03c3\u03b7\u03c2 \u03c3\u03b5 \u03ba\u03b5\u03af\u03bc\u03b5\u03bd\u03bf \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03b5\u03c0\u03af\u03b4\u03c1\u03b1\u03c3\u03b7 \u03c4\u03b7\u03c2 soft base distribution.<\/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\">Standard SFT<\/p>\n<p>\u0392\u03b5\u03bb\u03c4\u03b9\u03c3\u03c4\u03bf\u03c0\u03bf\u03b9\u03b5\u03af \u03bc\u03cc\u03bd\u03bf \u03c4\u03bf MedMCQA supervision. \u03a0\u03c1\u03bf\u03c3\u03b1\u03c1\u03bc\u03cc\u03b6\u03b5\u03b9 \u03c4\u03bf target task, \u03b1\u03bb\u03bb\u03ac \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03bc\u03b5\u03c4\u03b1\u03c4\u03bf\u03c0\u03af\u03c3\u03b5\u03b9 \u03c4\u03b7\u03bd \u03b1\u03bd\u03bf\u03b9\u03ba\u03c4\u03ae OOD \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae.<\/p>\n<div class=\"td-badge-row\"><span class=\"td-badge\">Target labels<\/span><span class=\"td-badge\">1 stream<\/span><\/div>\n<\/div>\n<div class=\"td-platform-card\">\n<p class=\"td-comparison-title\">Same-text replay<\/p>\n<p>\u03a0\u03c1\u03bf\u03c3\u03b8\u03ad\u03c4\u03b5\u03b9 \u03c4\u03bf \u03af\u03b4\u03b9\u03bf OOD anchor corpus \u03c9\u03c2 hard next-token labels. \u0395\u03bb\u03ad\u03b3\u03c7\u03b5\u03b9 \u03b1\u03bd \u03b1\u03c1\u03ba\u03b5\u03af \u03b1\u03c0\u03bb\u03ce\u03c2 \u03c0\u03b5\u03c1\u03b9\u03c3\u03c3\u03cc\u03c4\u03b5\u03c1\u03b7 \u03b3\u03b5\u03bd\u03b9\u03ba\u03ae \u03ad\u03ba\u03b8\u03b5\u03c3\u03b7.<\/p>\n<div class=\"td-badge-row\"><span class=\"td-badge\">Hard labels<\/span><span class=\"td-badge\">OOD text<\/span><\/div>\n<\/div>\n<div class=\"td-platform-card td-platform-card--navy\">\n<p class=\"td-comparison-title\">RAD<\/p>\n<p>\u03a4\u03b1\u03b9\u03c1\u03b9\u03ac\u03b6\u03b5\u03b9 \u03c4\u03b7 student distribution \u03bc\u03b5 \u03c4\u03b7 soft distribution \u03c4\u03bf\u03c5 adapter-off base model \u03c0\u03ac\u03bd\u03c9 \u03c3\u03c4\u03b1 continuation tokens.<\/p>\n<div class=\"td-badge-row\"><span class=\"td-badge\">Soft anchor<\/span><span class=\"td-badge\">One backbone<\/span><\/div>\n<\/div>\n<\/div>\n<\/div>\n<p>\u03a3\u03c4\u03bf Llama-3.1-8B, \u03c4\u03bf PopQA exact match \u03ae\u03c4\u03b1\u03bd 11,60 \u03bc\u03b5\u03c4\u03ac \u03c4\u03bf \u03c4\u03c5\u03c0\u03b9\u03ba\u03cc SFT, \u03ad\u03c0\u03b5\u03c3\u03b5 \u03c3\u03c4\u03bf 3,40 \u03bc\u03b5 replay \u03ba\u03b1\u03b9 \u03b1\u03bd\u03ad\u03b2\u03b7\u03ba\u03b5 \u03c3\u03c4\u03bf 15,20 \u03bc\u03b5 RAD. \u03a3\u03c4\u03bf TriviaQA, \u03c4\u03bf RAD \u03ad\u03c6\u03c4\u03b1\u03c3\u03b5 51,62 \u03ad\u03bd\u03b1\u03bd\u03c4\u03b9 43,95 \u03c4\u03bf\u03c5 SFT \u03ba\u03b1\u03b9 32,87 \u03c4\u03bf\u03c5 replay. \u0397 \u03c3\u03cd\u03b3\u03ba\u03c1\u03b9\u03c3\u03b7 \u03c3\u03c4\u03b7\u03c1\u03af\u03b6\u03b5\u03b9 \u03cc\u03c4\u03b9 \u03c4\u03bf \u03c7\u03c1\u03ae\u03c3\u03b9\u03bc\u03bf \u03c3\u03ae\u03bc\u03b1 \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03bc\u03cc\u03bd\u03bf \u03c4\u03bf anchor text, \u03b1\u03bb\u03bb\u03ac \u03bf\u03b9 \u03c3\u03c7\u03b5\u03c4\u03b9\u03ba\u03ad\u03c2 \u03c0\u03b9\u03b8\u03b1\u03bd\u03cc\u03c4\u03b7\u03c4\u03b5\u03c2 \u03c0\u03bf\u03c5 \u03b1\u03c0\u03bf\u03b4\u03af\u03b4\u03b5\u03b9 \u03b7 \u03b2\u03ac\u03c3\u03b7 \u03c3\u03c4\u03b9\u03c2 \u03c0\u03b9\u03b8\u03b1\u03bd\u03ad\u03c2 \u03c3\u03c5\u03bd\u03ad\u03c7\u03b5\u03b9\u03b5\u03c2.<\/p>\n<p>\u03a4\u03bf \u03b1\u03c0\u03bf\u03c4\u03ad\u03bb\u03b5\u03c3\u03bc\u03b1 \u03b4\u03b5\u03bd \u03ba\u03ac\u03bd\u03b5\u03b9 \u03c4\u03bf replay \u03ac\u03c7\u03c1\u03b7\u03c3\u03c4\u03bf \u03c3\u03b5 \u03ba\u03ac\u03b8\u03b5 context. \u0394\u03b5\u03af\u03c7\u03bd\u03b5\u03b9 \u03cc\u03c4\u03b9, \u03c3\u03b5 \u03b1\u03c5\u03c4\u03cc \u03c4\u03bf controlled setup \u03ba\u03b1\u03b9 \u03bc\u03b5 \u03af\u03c3\u03b7 \u03c0\u03bf\u03c3\u03cc\u03c4\u03b7\u03c4\u03b1 OOD \u03ba\u03b5\u03b9\u03bc\u03ad\u03bd\u03bf\u03c5, \u03c4\u03bf hard-label replay \u03b4\u03b5\u03bd \u03c0\u03c1\u03bf\u03c3\u03c4\u03ac\u03c4\u03b5\u03c5\u03c3\u03b5 \u03c4\u03b7\u03bd \u03b1\u03bd\u03bf\u03b9\u03ba\u03c4\u03ae factual \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae \u03cc\u03c3\u03bf \u03b7 distributional \u03b1\u03b3\u03ba\u03cd\u03c1\u03c9\u03c3\u03b7. \u039a\u03ac\u03b8\u03b5 \u03bd\u03ad\u03b1 \u03b5\u03c6\u03b1\u03c1\u03bc\u03bf\u03b3\u03ae \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03b4\u03b9\u03ba\u03cc \u03c4\u03b7\u03c2 baseline \u03ba\u03b1\u03b9 \u03cc\u03c7\u03b9 \u03b1\u03bd\u03c4\u03b9\u03b3\u03c1\u03b1\u03c6\u03ae \u03c4\u03c9\u03bd \u03c4\u03b9\u03bc\u03ce\u03bd \u03c3\u03b1\u03bd \u03bd\u03b1 \u03ae\u03c4\u03b1\u03bd universal benchmark.<\/p>\n<h2 id=\"tria-backbones\">\u03a4\u03b1 \u03b1\u03c0\u03bf\u03c4\u03b5\u03bb\u03ad\u03c3\u03bc\u03b1\u03c4\u03b1 \u03c3\u03c4\u03b1 \u03c4\u03c1\u03af\u03b1 backbones<\/h2>\n<p>\u0397 \u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7 \u03ba\u03b1\u03bb\u03cd\u03c0\u03c4\u03b5\u03b9 Llama-3.1-8B, Qwen2.5-7B-Instruct \u03ba\u03b1\u03b9 Qwen2.5-3B-Instruct, \u03cc\u03bb\u03b1 \u03c0\u03c1\u03bf\u03c3\u03b1\u03c1\u03bc\u03bf\u03c3\u03bc\u03ad\u03bd\u03b1 \u03bc\u03b5 LoRA \u03c3\u03c4\u03bf MedMCQA. \u039f\u03b9 \u03bc\u03b5\u03c4\u03c1\u03ae\u03c3\u03b5\u03b9\u03c2 \u03c0\u03b5\u03c1\u03b9\u03bb\u03b1\u03bc\u03b2\u03ac\u03bd\u03bf\u03c5\u03bd MedMCQA accuracy, MMLU-Med \u03ba\u03b1\u03b9 MMLU-Other, TruthfulQA-MC2 \u03ba\u03b1\u03b9 \u03b1\u03bd\u03bf\u03b9\u03ba\u03c4\u03ae \u03b1\u03bd\u03ac\u03ba\u03bb\u03b7\u03c3\u03b7 \u03c3\u03b5 TriviaQA \u03ba\u03b1\u03b9 PopQA \u03bc\u03b5 exact match \u03ba\u03b1\u03b9 token-level F1.<\/p>\n<p>\u03a3\u03c4\u03bf Qwen2.5-7B-Instruct, \u03c4\u03bf MedMCQA \u03ae\u03c4\u03b1\u03bd 61,99 \u03bc\u03b5 RAD \u03ad\u03bd\u03b1\u03bd\u03c4\u03b9 61,27 \u03bc\u03b5 SFT, \u03b5\u03bd\u03ce \u03c4\u03bf PopQA exact match \u03b1\u03c5\u03be\u03ae\u03b8\u03b7\u03ba\u03b5 \u03b1\u03c0\u03cc 4,95 \u03c3\u03b5 6,81. \u0397 \u03bc\u03b5\u03b3\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03b7 \u03b1\u03c0\u03bf\u03ba\u03b1\u03c4\u03ac\u03c3\u03c4\u03b1\u03c3\u03b7 \u03b1\u03c5\u03c4\u03bf\u03cd \u03c4\u03bf\u03c5 backbone \u03b5\u03bc\u03c6\u03b1\u03bd\u03af\u03b6\u03b5\u03c4\u03b1\u03b9 \u03c3\u03c4\u03bf TruthfulQA-MC2: 58,14 \u03bc\u03b5 RAD \u03ad\u03bd\u03b1\u03bd\u03c4\u03b9 49,03 \u03bc\u03b5 SFT, \u03c0\u03b1\u03c1\u03b1\u03bc\u03ad\u03bd\u03bf\u03bd\u03c4\u03b1\u03c2 \u03c7\u03b1\u03bc\u03b7\u03bb\u03cc\u03c4\u03b5\u03c1\u03b1 \u03b1\u03c0\u03cc \u03c4\u03bf 64,75 \u03c4\u03b7\u03c2 \u03b2\u03ac\u03c3\u03b7\u03c2.<\/p>\n<p>\u03a3\u03c4\u03bf Qwen2.5-3B-Instruct, \u03c4\u03bf TriviaQA exact match \u03ba\u03b1\u03c4\u03ad\u03c1\u03c1\u03b5\u03c5\u03c3\u03b5 \u03b1\u03c0\u03cc 30,57 \u03c3\u03c4\u03b7 \u03b2\u03ac\u03c3\u03b7 \u03c3\u03b5 1,04 \u03bc\u03b5\u03c4\u03ac \u03c4\u03bf SFT \u03ba\u03b1\u03b9 \u03b1\u03bd\u03ad\u03b2\u03b7\u03ba\u03b5 \u03c3\u03b5 9,04 \u03bc\u03b5 RAD. \u03a4\u03bf MedMCQA \u03ae\u03c4\u03b1\u03bd 55,41 \u03bc\u03b5 RAD \u03ad\u03bd\u03b1\u03bd\u03c4\u03b9 55,75 \u03bc\u03b5 SFT. \u03a0\u03c1\u03cc\u03ba\u03b5\u03b9\u03c4\u03b1\u03b9 \u03b3\u03b9\u03b1 \u03bf\u03c5\u03c3\u03b9\u03b1\u03c3\u03c4\u03b9\u03ba\u03ae \u03b1\u03bb\u03bb\u03ac \u03bc\u03b5\u03c1\u03b9\u03ba\u03ae \u03b1\u03bd\u03ac\u03ba\u03c4\u03b7\u03c3\u03b7: \u03bf\u03cd\u03c4\u03b5 \u03b7 \u03b1\u03c1\u03c7\u03b9\u03ba\u03ae factual \u03b5\u03c0\u03af\u03b4\u03bf\u03c3\u03b7 \u03b1\u03c0\u03bf\u03ba\u03b1\u03c4\u03b1\u03c3\u03c4\u03ac\u03b8\u03b7\u03ba\u03b5 \u03bf\u03cd\u03c4\u03b5 \u03c4\u03bf target score \u03b4\u03b9\u03b1\u03c4\u03b7\u03c1\u03ae\u03b8\u03b7\u03ba\u03b5 \u03b1\u03c0\u03bf\u03bb\u03cd\u03c4\u03c9\u03c2 \u03af\u03b4\u03b9\u03bf.<\/p>\n<p>\u0397 \u03bc\u03b5\u03c4\u03b1\u03b2\u03bf\u03bb\u03ae \u03b4\u03b9\u03b1\u03c6\u03ad\u03c1\u03b5\u03b9 \u03b1\u03bd\u03ac \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03ba\u03b1\u03b9 metric. \u0391\u03c5\u03c4\u03cc \u03b5\u03af\u03bd\u03b1\u03b9 \u03c3\u03b7\u03bc\u03b1\u03bd\u03c4\u03b9\u03ba\u03cc \u03b3\u03b9\u03b1 \u03c4\u03bf <a href=\"https:\/\/twodots.gr\/dynamic-context-scheduling-ai-agents-metavallomenos-kosmos\/\">robust evaluation \u03c3\u03b5 \u03bc\u03b5\u03c4\u03b1\u03b2\u03b1\u03bb\u03bb\u03cc\u03bc\u03b5\u03bd\u03bf context<\/a>: \u03b7 \u03bf\u03bc\u03ac\u03b4\u03b1 \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 per-slice \u03b1\u03c0\u03bf\u03c4\u03b5\u03bb\u03ad\u03c3\u03bc\u03b1\u03c4\u03b1, checkpoints \u03ba\u03b1\u03b9 failure categories, \u03cc\u03c7\u03b9 \u03bc\u03cc\u03bd\u03bf \u03ad\u03bd\u03b1\u03bd \u03bc\u03ad\u03c3\u03bf \u03cc\u03c1\u03bf \u03c0\u03bf\u03c5 \u03ba\u03c1\u03cd\u03b2\u03b5\u03b9 \u03c0\u03bf\u03cd \u03c3\u03c5\u03bd\u03ad\u03b2\u03b7 \u03b7 \u03b2\u03bb\u03ac\u03b2\u03b7.<\/p>\n<h2 id=\"kostos-oria\">\u039a\u03cc\u03c3\u03c4\u03bf\u03c2, \u03b1\u03c0\u03bf\u03b4\u03bf\u03c4\u03b9\u03ba\u03cc\u03c4\u03b7\u03c4\u03b1 \u03ba\u03b1\u03b9 \u03cc\u03c1\u03b9\u03b1<\/h2>\n<p>\u0395\u03c0\u03b5\u03b9\u03b4\u03ae teacher \u03ba\u03b1\u03b9 student \u03b5\u03af\u03bd\u03b1\u03b9 \u03b4\u03cd\u03bf modes \u03c4\u03bf\u03c5 \u03af\u03b4\u03b9\u03bf\u03c5 backbone, \u03b7 \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03ac GPU memory \u03ad\u03bc\u03b5\u03b9\u03bd\u03b5 \u03bc\u03ad\u03c3\u03b1 \u03c3\u03c4\u03bf 1 GB \u03c3\u03c4\u03b1 \u03c4\u03c1\u03af\u03b1 backbones. \u03a5\u03c0\u03ac\u03c1\u03c7\u03b5\u03b9 \u03cc\u03bc\u03c9\u03c2 \u03c0\u03c1\u03cc\u03c3\u03b8\u03b5\u03c4\u03bf\u03c2 \u03c7\u03c1\u03cc\u03bd\u03bf\u03c2 \u03b5\u03ba\u03c0\u03b1\u03af\u03b4\u03b5\u03c5\u03c3\u03b7\u03c2 \u03b1\u03c0\u03cc \u03c4\u03bf adapter-off forward pass \u03c3\u03b5 \u03ba\u03ac\u03b8\u03b5 OOD batch. \u0397 \u03bc\u03b5\u03b3\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03b7 \u03b1\u03cd\u03be\u03b7\u03c3\u03b7 \u03c0\u03bf\u03c5 \u03b1\u03bd\u03b1\u03c6\u03ad\u03c1\u03b5\u03b9 \u03b7 \u03b5\u03c1\u03b3\u03b1\u03c3\u03af\u03b1 \u03ae\u03c4\u03b1\u03bd \u03c0\u03b5\u03c1\u03af\u03c0\u03bf\u03c5 1,4 \u03ce\u03c1\u03b5\u03c2, \u03c7\u03c9\u03c1\u03af\u03c2 \u03b1\u03bb\u03bb\u03b1\u03b3\u03ae \u03c4\u03b7\u03c2 inference-time \u03b1\u03c1\u03c7\u03b9\u03c4\u03b5\u03ba\u03c4\u03bf\u03bd\u03b9\u03ba\u03ae\u03c2 \u03c3\u03b5 \u03c3\u03c7\u03ad\u03c3\u03b7 \u03bc\u03b5 \u03c4\u03bf LoRA SFT.<\/p>\n<aside class=\"td-article-note\">\n<p><strong>\u03a4\u03bf evidence \u03ad\u03c7\u03b5\u03b9 \u03c3\u03c4\u03b5\u03bd\u03ac \u03cc\u03c1\u03b9\u03b1:<\/strong> \u03c0\u03c1\u03cc\u03ba\u03b5\u03b9\u03c4\u03b1\u03b9 \u03b3\u03b9\u03b1 \u03c0\u03c1\u03cc\u03c3\u03c6\u03b1\u03c4\u03b7 arXiv \u03b5\u03c1\u03b3\u03b1\u03c3\u03af\u03b1 \u03bc\u03b5 \u03c4\u03c1\u03af\u03b1 backbones, \u03ad\u03bd\u03b1\u03bd \u03b9\u03b1\u03c4\u03c1\u03b9\u03ba\u03cc target domain, \u03b1\u03b3\u03b3\u03bb\u03cc\u03c6\u03c9\u03bd\u03b1 factual benchmarks \u03ba\u03b1\u03b9 failure analysis 300 \u03b5\u03c0\u03b9\u03bb\u03b5\u03b3\u03bc\u03ad\u03bd\u03c9\u03bd cases. \u0394\u03b5\u03bd \u03c4\u03b5\u03ba\u03bc\u03b7\u03c1\u03b9\u03ce\u03bd\u03b5\u03b9 \u03b1\u03c5\u03c4\u03cc\u03bc\u03b1\u03c4\u03b1 \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03b9\u03ba\u03ac workloads, \u03b5\u03bb\u03bb\u03b7\u03bd\u03b9\u03ba\u03ac \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03b1, \u03ac\u03bb\u03bb\u03b5\u03c2 \u03c4\u03b5\u03c7\u03bd\u03b9\u03ba\u03ad\u03c2 fine-tuning \u03ae \u03c0\u03bb\u03ae\u03c1\u03b7 \u03b4\u03b9\u03b1\u03c4\u03ae\u03c1\u03b7\u03c3\u03b7 \u03ba\u03ac\u03b8\u03b5 \u03b9\u03ba\u03b1\u03bd\u03cc\u03c4\u03b7\u03c4\u03b1\u03c2.<\/p>\n<\/aside>\n<p>\u0397 \u03b5\u03c1\u03b3\u03b1\u03c3\u03af\u03b1 \u03b4\u03b5\u03bd \u03c0\u03b1\u03c1\u03bf\u03c5\u03c3\u03b9\u03ac\u03b6\u03b5\u03b9 deployment \u03c3\u03b5 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03cc \u03bf\u03c1\u03b3\u03b1\u03bd\u03b9\u03c3\u03bc\u03cc, SLA, security evaluation \u03ae \u03bf\u03b9\u03ba\u03bf\u03bd\u03bf\u03bc\u03b9\u03ba\u03cc ROI. \u03a4\u03bf Wikipedia-style anchor corpus \u03b5\u03af\u03bd\u03b1\u03b9 \u03c3\u03c7\u03b5\u03b4\u03b9\u03b1\u03c3\u03bc\u03ad\u03bd\u03bf \u03b3\u03b9\u03b1 factual continuation, \u03cc\u03c7\u03b9 \u03b3\u03b9\u03b1 \u03ba\u03ac\u03b8\u03b5 \u03bc\u03bf\u03c1\u03c6\u03ae \u03c3\u03c5\u03bc\u03c0\u03b5\u03c1\u03b9\u03c6\u03bf\u03c1\u03ac\u03c2 \u03c0\u03bf\u03c5 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b8\u03ad\u03bb\u03b5\u03b9 \u03bd\u03b1 \u03c0\u03c1\u03bf\u03c3\u03c4\u03b1\u03c4\u03b5\u03cd\u03c3\u03b5\u03b9 \u03bc\u03b9\u03b1 \u03b5\u03c0\u03b9\u03c7\u03b5\u03af\u03c1\u03b7\u03c3\u03b7. Tone, tool use, refusal policy, multilingual consistency \u03ba\u03b1\u03b9 domain-specific compliance \u03b1\u03c0\u03b1\u03b9\u03c4\u03bf\u03cd\u03bd \u03c7\u03c9\u03c1\u03b9\u03c3\u03c4\u03ad\u03c2 anchors \u03ba\u03b1\u03b9 tests.<\/p>\n<p>\u0395\u03c0\u03b9\u03c0\u03bb\u03ad\u03bf\u03bd, \u03b7 \u03bc\u03b5\u03b9\u03c9\u03bc\u03ad\u03bd\u03b7 exact-match \u03b5\u03c0\u03af\u03b4\u03bf\u03c3\u03b7 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03c3\u03c5\u03bd\u03b4\u03c5\u03ac\u03b6\u03b5\u03b9 \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03ad\u03c2 \u03b1\u03b9\u03c4\u03af\u03b5\u03c2. \u03a4\u03bf 77,3% \u03b1\u03c6\u03bf\u03c1\u03ac \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03bf sample, \u03cc\u03c7\u03b9 \u03cc\u03bb\u03b1 \u03c4\u03b1 failures \u03c4\u03bf\u03c5 benchmark \u03ba\u03b1\u03b9 \u03cc\u03c7\u03b9 \u03ba\u03ac\u03b8\u03b5 backbone. \u0397 \u03ce\u03c1\u03b9\u03bc\u03b7 \u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7 \u03ba\u03c1\u03b1\u03c4\u03ac \u03c4\u03bf claim boundary \u03bf\u03c1\u03b1\u03c4\u03cc, \u03cc\u03c0\u03c9\u03c2 \u03ba\u03b1\u03b9 \u03c3\u03c4\u03bf <a href=\"https:\/\/twodots.gr\/flavourbench-axiopisti-axiologisi-ai\/\">FlavourBench \u03b3\u03b9\u03b1 \u03b5\u03c0\u03b1\u03bd\u03b1\u03bb\u03ae\u03c8\u03b9\u03bc\u03b1 AI benchmarks<\/a> \u03ba\u03b1\u03b9 \u03c3\u03c4\u03bf <a href=\"https:\/\/twodots.gr\/cmb-04-ai-agent-anatheorisi-kritirion\/\">CMB-0.4 \u03b3\u03b9\u03b1 \u03b1\u03bd\u03b1\u03b8\u03b5\u03ce\u03c1\u03b7\u03c3\u03b7 \u03ba\u03c1\u03b9\u03c4\u03b7\u03c1\u03af\u03c9\u03bd<\/a>.<\/p>\n<h2 id=\"epicheirisi-diagnosi\">\u03a4\u03b9 \u03b1\u03bb\u03bb\u03ac\u03b6\u03b5\u03b9 \u03c3\u03c4\u03b7 \u03b4\u03b9\u03ac\u03b3\u03bd\u03c9\u03c3\u03b7 \u03bc\u03b9\u03b1\u03c2 \u03b5\u03c0\u03b9\u03c7\u03b5\u03af\u03c1\u03b7\u03c3\u03b7\u03c2<\/h2>\n<p>\u03a4\u03bf \u03c0\u03c1\u03ce\u03c4\u03bf \u03c0\u03c1\u03b1\u03ba\u03c4\u03b9\u03ba\u03cc \u03bc\u03ac\u03b8\u03b7\u03bc\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03cc\u03c4\u03b9 \u03ad\u03bd\u03b1 \u03bc\u03cc\u03bd\u03bf score \u03ba\u03c1\u03cd\u03b2\u03b5\u03b9 \u03c4\u03b7\u03bd \u03b1\u03b9\u03c4\u03af\u03b1 \u03c4\u03b7\u03c2 \u03c5\u03c0\u03bf\u03b2\u03ac\u03b8\u03bc\u03b9\u03c3\u03b7\u03c2. \u039c\u03b9\u03b1 \u03c3\u03bf\u03b2\u03b1\u03c1\u03ae \u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7 \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03c3\u03c5\u03b3\u03ba\u03c1\u03af\u03bd\u03b5\u03b9 \u03b1\u03bd\u03bf\u03b9\u03ba\u03c4\u03ae \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7, \u03c0\u03bf\u03bb\u03bb\u03b1\u03c0\u03bb\u03ae \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ae \u03ae ranking \u03ba\u03b1\u03b9 \u03c3\u03b7\u03bc\u03b1\u03c3\u03b9\u03bf\u03bb\u03bf\u03b3\u03b9\u03ba\u03ae \u03ba\u03c1\u03af\u03c3\u03b7 \u03c4\u03bf\u03c5 \u03af\u03b4\u03b9\u03bf\u03c5 fact. \u0391\u03bd \u03c4\u03bf \u03c3\u03cd\u03c3\u03c4\u03b7\u03bc\u03b1 \u03c7\u03ac\u03bd\u03b5\u03b9 \u03bc\u03cc\u03bd\u03bf \u03c3\u03c4\u03bf strict format, \u03af\u03c3\u03c9\u03c2 \u03b1\u03bd\u03c4\u03b9\u03bc\u03b5\u03c4\u03c9\u03c0\u03af\u03b6\u03b5\u03b9 \u03c0\u03c1\u03cc\u03b2\u03bb\u03b7\u03bc\u03b1 \u03ad\u03ba\u03c6\u03c1\u03b1\u03c3\u03b7\u03c2. \u0391\u03bd \u03b1\u03bd\u03b1\u03b3\u03bd\u03c9\u03c1\u03af\u03b6\u03b5\u03b9 \u03b1\u03bb\u03bb\u03ac \u03b4\u03b5\u03bd \u03b1\u03bd\u03b1\u03ba\u03b1\u03bb\u03b5\u03af, \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03c0\u03b1\u03c1\u03ad\u03bc\u03b2\u03b1\u03c3\u03b7 \u03c3\u03c4\u03b7\u03bd \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae \u03ae \u03c3\u03c4\u03bf training. \u0391\u03bd \u03b1\u03c0\u03bf\u03c4\u03c5\u03b3\u03c7\u03ac\u03bd\u03b5\u03b9 \u03c3\u03b5 \u03cc\u03bb\u03b5\u03c2 \u03c4\u03b9\u03c2 \u03bc\u03bf\u03c1\u03c6\u03ad\u03c2, \u03b7 \u03c5\u03c0\u03cc\u03b8\u03b5\u03c3\u03b7 \u03b2\u03b1\u03b8\u03cd\u03c4\u03b5\u03c1\u03b7\u03c2 \u03b1\u03c0\u03ce\u03bb\u03b5\u03b9\u03b1\u03c2 \u03b3\u03af\u03bd\u03b5\u03c4\u03b1\u03b9 \u03b9\u03c3\u03c7\u03c5\u03c1\u03cc\u03c4\u03b5\u03c1\u03b7.<\/p>\n<p>\u03a4\u03bf \u03b4\u03b5\u03cd\u03c4\u03b5\u03c1\u03bf \u03bc\u03ac\u03b8\u03b7\u03bc\u03b1 \u03b1\u03c6\u03bf\u03c1\u03ac \u03c4\u03b1 regression suites. \u0388\u03bd\u03b1 customer-support model \u03b4\u03b5\u03bd \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03b5\u03bb\u03ad\u03b3\u03c7\u03b5\u03c4\u03b1\u03b9 \u03bc\u03cc\u03bd\u03bf \u03c0\u03ac\u03bd\u03c9 \u03c3\u03c4\u03b1 tickets \u03c4\u03b7\u03c2 \u03b5\u03c4\u03b1\u03b9\u03c1\u03b5\u03af\u03b1\u03c2. \u03a7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 OOD \u03c3\u03cd\u03bd\u03bf\u03bb\u03bf \u03c0\u03bf\u03c5 \u03ba\u03b1\u03bb\u03cd\u03c0\u03c4\u03b5\u03b9 \u03c4\u03b9\u03c2 \u03b3\u03b5\u03bd\u03b9\u03ba\u03ad\u03c2 \u03b9\u03ba\u03b1\u03bd\u03cc\u03c4\u03b7\u03c4\u03b5\u03c2 \u03c0\u03bf\u03c5 \u03b4\u03b5\u03bd \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03b8\u03c5\u03c3\u03b9\u03b1\u03c3\u03c4\u03bf\u03cd\u03bd: \u03b2\u03b1\u03c3\u03b9\u03ba\u03ac facts, \u03b3\u03bb\u03ce\u03c3\u03c3\u03b5\u03c2, refusal boundaries, citations, structured output \u03ba\u03b1\u03b9 \u03ba\u03c1\u03af\u03c3\u03b9\u03bc\u03b1 \u03b5\u03c1\u03b3\u03b1\u03bb\u03b5\u03af\u03b1. \u0397 \u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7 \u03b1\u03bd\u03ac \u03b3\u03bb\u03ce\u03c3\u03c3\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b1\u03c0\u03b1\u03c1\u03b1\u03af\u03c4\u03b7\u03c4\u03b7, \u03b5\u03c0\u03b5\u03b9\u03b4\u03ae \u03b7 \u03b4\u03b9\u03b1\u03c4\u03ae\u03c1\u03b7\u03c3\u03b7 \u03c3\u03c4\u03b1 \u03b1\u03b3\u03b3\u03bb\u03b9\u03ba\u03ac \u03b4\u03b5\u03bd \u03c4\u03b5\u03ba\u03bc\u03b7\u03c1\u03b9\u03ce\u03bd\u03b5\u03b9 \u03b4\u03b9\u03b1\u03c4\u03ae\u03c1\u03b7\u03c3\u03b7 \u03c3\u03c4\u03b1 \u03b5\u03bb\u03bb\u03b7\u03bd\u03b9\u03ba\u03ac.<\/p>\n<p>\u0393\u03b9\u03b1 \u03c3\u03c5\u03c3\u03c4\u03ae\u03bc\u03b1\u03c4\u03b1 \u03bc\u03b5 \u03bc\u03bd\u03ae\u03bc\u03b7 \u03ae retrieval, \u03b7 \u03bb\u03b1\u03bd\u03b8\u03b1\u03c3\u03bc\u03ad\u03bd\u03b7 \u03b4\u03b9\u03ac\u03b3\u03bd\u03c9\u03c3\u03b7 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03bf\u03b4\u03b7\u03b3\u03ae\u03c3\u03b5\u03b9 \u03c3\u03b5 \u03ac\u03c3\u03ba\u03bf\u03c0\u03b7 \u03b1\u03bb\u03bb\u03b1\u03b3\u03ae vector store \u03b5\u03bd\u03ce \u03c4\u03bf \u03c0\u03c1\u03cc\u03b2\u03bb\u03b7\u03bc\u03b1 \u03b2\u03c1\u03af\u03c3\u03ba\u03b5\u03c4\u03b1\u03b9 \u03c3\u03c4\u03b7\u03bd \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae. \u0397 \u03b4\u03b9\u03ac\u03ba\u03c1\u03b9\u03c3\u03b7 \u03c3\u03c5\u03bc\u03c0\u03bb\u03b7\u03c1\u03ce\u03bd\u03b5\u03b9 \u03c4\u03bf \u03b6\u03ae\u03c4\u03b7\u03bc\u03b1 \u03c4\u03b7\u03c2 <a href=\"https:\/\/twodots.gr\/ai-mnimi-giati-anaktisi-apotygchanei-prin-xekinisei\/\">\u03b1\u03bd\u03ac\u03ba\u03c4\u03b7\u03c3\u03b7\u03c2 \u03c3\u03c4\u03b7 \u03bc\u03bd\u03ae\u03bc\u03b7 AI agents<\/a>: \u03ac\u03bb\u03bb\u03bf \u03bd\u03b1 \u03bc\u03b7 \u03c6\u03c4\u03ac\u03bd\u03b5\u03b9 \u03c4\u03bf \u03c3\u03c9\u03c3\u03c4\u03cc evidence \u03c3\u03c4\u03bf context \u03ba\u03b1\u03b9 \u03ac\u03bb\u03bb\u03bf \u03bd\u03b1 \u03c5\u03c0\u03ac\u03c1\u03c7\u03b5\u03b9 \u03b4\u03b9\u03b1\u03b8\u03ad\u03c3\u03b9\u03bc\u03bf \u03b1\u03bb\u03bb\u03ac \u03bd\u03b1 \u03bc\u03b7\u03bd \u03b5\u03ba\u03c6\u03c1\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03c3\u03c9\u03c3\u03c4\u03ac.<\/p>\n<div class=\"td-decision-band\">\n<div class=\"td-decision-band-content\">\n<p class=\"td-decision-band-kicker\">\u03a4\u03bf deployment decision<\/p>\n<p class=\"td-decision-band-title\">\u039c\u03b7\u03bd \u03b5\u03b3\u03ba\u03c1\u03af\u03bd\u03b5\u03c4\u03b5 fine-tuned LLM \u03bc\u03cc\u03bd\u03bf \u03b5\u03c0\u03b5\u03b9\u03b4\u03ae \u03ba\u03ad\u03c1\u03b4\u03b9\u03c3\u03b5 \u03c3\u03c4\u03bf target benchmark<\/p>\n<p>\u0396\u03b7\u03c4\u03ae\u03c3\u03c4\u03b5 same-fact probes \u03c3\u03b5 recall, recognition \u03ba\u03b1\u03b9 format, OOD regression suite \u03b1\u03bd\u03ac \u03b3\u03bb\u03ce\u03c3\u03c3\u03b1, \u03b9\u03c3\u03c7\u03c5\u03c1\u03cc Standard SFT \u03ba\u03b1\u03b9 replay baseline, \u03ba\u03b1\u03b8\u03ce\u03c2 \u03ba\u03b1\u03b9 rollback threshold. \u03a4\u03bf RAD \u03b5\u03af\u03bd\u03b1\u03b9 \u03c5\u03c0\u03bf\u03c8\u03ae\u03c6\u03b9\u03b1 \u03c4\u03b5\u03c7\u03bd\u03b9\u03ba\u03ae \u03cc\u03c4\u03b1\u03bd \u03b7 \u03b4\u03b9\u03ac\u03b3\u03bd\u03c9\u03c3\u03b7 \u03b4\u03b5\u03af\u03c7\u03bd\u03b5\u03b9 drift \u03c3\u03c4\u03b7\u03bd \u03b1\u03bd\u03bf\u03b9\u03ba\u03c4\u03ae \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae \u2014 \u03cc\u03c7\u03b9 \u03b3\u03b5\u03bd\u03b9\u03ba\u03ae \u03bb\u03cd\u03c3\u03b7 \u03b3\u03b9\u03b1 \u03ba\u03ac\u03b8\u03b5 \u03b1\u03c3\u03c4\u03bf\u03c7\u03af\u03b1.<\/p>\n<\/div>\n<\/div>\n<p>\u03a4\u03b1 guardrails \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03b5\u03c0\u03af\u03c3\u03b7\u03c2 \u03bd\u03b1 \u03b5\u03bb\u03ad\u03b3\u03c7\u03bf\u03c5\u03bd \u03c4\u03b7 \u03b4\u03b9\u03b1\u03b4\u03c1\u03bf\u03bc\u03ae \u03b1\u03c0\u03cc \u03c0\u03c1\u03cc\u03b8\u03b5\u03c3\u03b7 \u03c3\u03b5 \u03ad\u03be\u03bf\u03b4\u03bf, \u03cc\u03c7\u03b9 \u03bc\u03cc\u03bd\u03bf \u03c4\u03bf \u03c4\u03b5\u03bb\u03b9\u03ba\u03cc string. \u0397 \u03b1\u03c1\u03c7\u03ae \u03c3\u03c5\u03bd\u03b4\u03ad\u03b5\u03c4\u03b1\u03b9 \u03bc\u03b5 \u03c4\u03bf <a href=\"https:\/\/twodots.gr\/intent-horizon-ai-guardrails-liv\/\">Intent Horizon \u03b3\u03b9\u03b1 \u03b2\u03b1\u03b8\u03cd\u03c4\u03b5\u03c1\u03bf\u03c5\u03c2 AI guardrails<\/a>: constrained probes, traces \u03ba\u03b1\u03b9 calibrated escalation \u03bc\u03c0\u03bf\u03c1\u03bf\u03cd\u03bd \u03bd\u03b1 \u03b1\u03c0\u03bf\u03ba\u03b1\u03bb\u03cd\u03c8\u03bf\u03c5\u03bd \u03cc\u03c4\u03b9 \u03c4\u03bf \u03af\u03b4\u03b9\u03bf \u03c3\u03cd\u03c3\u03c4\u03b7\u03bc\u03b1 \u03c3\u03c5\u03bc\u03c0\u03b5\u03c1\u03b9\u03c6\u03ad\u03c1\u03b5\u03c4\u03b1\u03b9 \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03ac \u03ba\u03ac\u03c4\u03c9 \u03b1\u03c0\u03cc \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03ad\u03c2 \u03c3\u03c5\u03bd\u03b8\u03ae\u03ba\u03b5\u03c2 \u03c0\u03c1\u03cc\u03c3\u03b2\u03b1\u03c3\u03b7\u03c2.<\/p>\n<h2 id=\"regression-suite\">\u03a0\u03c1\u03b1\u03ba\u03c4\u03b9\u03ba\u03ae \u03b4\u03b9\u03b1\u03b4\u03b9\u03ba\u03b1\u03c3\u03af\u03b1 \u03c0\u03c1\u03b9\u03bd \u03b1\u03c0\u03cc \u03c4\u03bf deployment<\/h2>\n<p>\u0397 \u03b5\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03b7\u03c3\u03b9\u03b1\u03ba\u03ae \u03c5\u03bb\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7 \u03b4\u03b5\u03bd \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03bd\u03b1 \u03be\u03b5\u03ba\u03b9\u03bd\u03ae\u03c3\u03b5\u03b9 \u03bc\u03b5 RAD. \u03a0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03c0\u03c1\u03ce\u03c4\u03b1 \u03bd\u03b1 \u03b1\u03c0\u03bf\u03b4\u03b5\u03af\u03be\u03b5\u03b9 \u03c4\u03b9 \u03b5\u03af\u03b4\u03bf\u03c5\u03c2 failure \u03c5\u03c0\u03ac\u03c1\u03c7\u03b5\u03b9, \u03bd\u03b1 \u03c0\u03b1\u03b3\u03ce\u03c3\u03b5\u03b9 \u03c4\u03b1 evaluation splits \u03ba\u03b1\u03b9 \u03bd\u03b1 \u03c3\u03c5\u03b3\u03ba\u03c1\u03af\u03bd\u03b5\u03b9 \u03c4\u03b7\u03bd \u03c0\u03c1\u03bf\u03c4\u03b5\u03b9\u03bd\u03cc\u03bc\u03b5\u03bd\u03b7 \u03c0\u03b1\u03c1\u03ad\u03bc\u03b2\u03b1\u03c3\u03b7 \u03bc\u03b5 \u03b1\u03c0\u03bb\u03cc\u03c4\u03b5\u03c1\u03b5\u03c2 \u03bb\u03cd\u03c3\u03b5\u03b9\u03c2. \u0397 \u03c0\u03c1\u03bf\u03b4\u03b9\u03b1\u03b3\u03c1\u03b1\u03c6\u03ae \u03c4\u03bf\u03c5 test \u03b5\u03af\u03bd\u03b1\u03b9 \u03bc\u03ad\u03c1\u03bf\u03c2 \u03c4\u03bf\u03c5 \u03c3\u03c5\u03c3\u03c4\u03ae\u03bc\u03b1\u03c4\u03bf\u03c2, \u03cc\u03c0\u03c9\u03c2 \u03c5\u03c0\u03bf\u03b3\u03c1\u03b1\u03bc\u03bc\u03af\u03b6\u03b5\u03b9 \u03ba\u03b1\u03b9 \u03c4\u03bf <a href=\"https:\/\/twodots.gr\/sdad-prodiagrafi-ai-anaptyxi-logismikou\/\">SDAD \u03b3\u03b9\u03b1 \u03c0\u03c1\u03bf\u03b4\u03b9\u03b1\u03b3\u03c1\u03b1\u03c6\u03ae \u03ba\u03b1\u03b9 \u03b5\u03c0\u03b1\u03bb\u03ae\u03b8\u03b5\u03c5\u03c3\u03b7 AI \u03b1\u03bd\u03ac\u03c0\u03c4\u03c5\u03be\u03b7\u03c2<\/a>.<\/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 \u03b5\u03bb\u03ad\u03b3\u03be\u03b5\u03c4\u03b5 factual access failure<\/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\u03b9\u03c2 \u03b9\u03ba\u03b1\u03bd\u03cc\u03c4\u03b7\u03c4\u03b5\u03c2 \u03c0\u03bf\u03c5 \u03b4\u03b5\u03bd \u03b5\u03c0\u03b9\u03c4\u03c1\u03ad\u03c0\u03b5\u03c4\u03b1\u03b9 \u03bd\u03b1 \u03c7\u03b1\u03b8\u03bf\u03cd\u03bd<\/strong>\n<p>\u039a\u03b1\u03c4\u03b1\u03b3\u03c1\u03ac\u03c8\u03c4\u03b5 facts, \u03b3\u03bb\u03ce\u03c3\u03c3\u03b5\u03c2, refusal \u03ba\u03b1\u03bd\u03cc\u03bd\u03b5\u03c2, schemas \u03ba\u03b1\u03b9 \u03b5\u03c1\u03b3\u03b1\u03bb\u03b5\u03af\u03b1 \u03c0\u03bf\u03c5 \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03b4\u03b9\u03b1\u03c4\u03b7\u03c1\u03b7\u03b8\u03bf\u03cd\u03bd \u03bc\u03b5\u03c4\u03ac \u03c4\u03b7\u03bd \u03b5\u03be\u03b5\u03b9\u03b4\u03af\u03ba\u03b5\u03c5\u03c3\u03b7.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">\u0421\u0442\u044a\u043f\u043a\u0430 2<\/span><strong>\u03a0\u03b1\u03b3\u03ce\u03c3\u03c4\u03b5 base, Standard SFT \u03ba\u03b1\u03b9 evaluation splits<\/strong>\n<p>\u03a7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03c4\u03b5 \u03c4\u03b1 \u03af\u03b4\u03b9\u03b1 prompts, decoding settings, aliases \u03ba\u03b1\u03b9 seeds, \u03ce\u03c3\u03c4\u03b5 \u03b7 \u03c3\u03cd\u03b3\u03ba\u03c1\u03b9\u03c3\u03b7 \u03bd\u03b1 \u03bc\u03b7 \u03bc\u03b5\u03c4\u03b1\u03ba\u03b9\u03bd\u03b5\u03af\u03c4\u03b1\u03b9 \u03bc\u03b1\u03b6\u03af \u03bc\u03b5 \u03c4\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">\u0421\u0442\u044a\u043f\u043a\u0430 3<\/span><strong>\u039c\u03b5\u03c4\u03c1\u03ae\u03c3\u03c4\u03b5 \u03c4\u03bf \u03af\u03b4\u03b9\u03bf fact \u03bc\u03b5 \u03c4\u03c1\u03b5\u03b9\u03c2 \u03bc\u03bf\u03c1\u03c6\u03ad\u03c2<\/strong>\n<p>\u0394\u03bf\u03ba\u03b9\u03bc\u03ac\u03c3\u03c4\u03b5 \u03b1\u03bd\u03bf\u03b9\u03ba\u03c4\u03ae \u03b1\u03bd\u03ac\u03ba\u03bb\u03b7\u03c3\u03b7, \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ae \u03ae ranking \u03ba\u03b1\u03b9 \u03b1\u03c5\u03c3\u03c4\u03b7\u03c1\u03cc schema. \u039a\u03c1\u03b1\u03c4\u03ae\u03c3\u03c4\u03b5 exact match \u03bc\u03b1\u03b6\u03af \u03bc\u03b5 semantic review \u03ba\u03b1\u03b9 \u03cc\u03c7\u03b9 \u03c9\u03c2 \u03bc\u03bf\u03bd\u03b1\u03b4\u03b9\u03ba\u03cc \u03ba\u03c1\u03b9\u03c4\u03ae.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">\u0421\u0442\u044a\u043f\u043a\u0430 4<\/span><strong>\u03a4\u03b1\u03be\u03b9\u03bd\u03bf\u03bc\u03ae\u03c3\u03c4\u03b5 \u03c4\u03b1 failures \u03c0\u03c1\u03b9\u03bd \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03b5\u03c0\u03b9\u03c3\u03ba\u03b5\u03c5\u03ae<\/strong>\n<p>\u039e\u03b5\u03c7\u03c9\u03c1\u03af\u03c3\u03c4\u03b5 \u03bb\u03ac\u03b8\u03bf\u03c2 \u03bf\u03bd\u03c4\u03cc\u03c4\u03b7\u03c4\u03b1, format \u03ae verbosity, \u03c3\u03b7\u03bc\u03b1\u03c3\u03b9\u03bf\u03bb\u03bf\u03b3\u03b9\u03ba\u03ac \u03c3\u03c9\u03c3\u03c4\u03ae \u03c0\u03b1\u03c1\u03b1\u03bb\u03bb\u03b1\u03b3\u03ae \u03ba\u03b1\u03b9 refusal. \u0397 \u03ba\u03b1\u03c4\u03b7\u03b3\u03bf\u03c1\u03af\u03b1 \u03ba\u03b1\u03b8\u03bf\u03c1\u03af\u03b6\u03b5\u03b9 prompt, data \u03ae training intervention.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">\u0421\u0442\u044a\u043f\u043a\u0430 5<\/span><strong>\u03a3\u03c5\u03b3\u03ba\u03c1\u03af\u03bd\u03b5\u03c4\u03b5 RAD \u03bc\u03b5 \u03b1\u03c0\u03bb\u03cc replay<\/strong>\n<p>\u039a\u03c1\u03b1\u03c4\u03ae\u03c3\u03c4\u03b5 \u03af\u03b4\u03b9\u03bf OOD corpus \u03ba\u03b1\u03b9 training budget \u03cc\u03c0\u03bf\u03c5 \u03b3\u03af\u03bd\u03b5\u03c4\u03b1\u03b9. \u0388\u03c4\u03c3\u03b9 \u03b5\u03bb\u03ad\u03b3\u03c7\u03b5\u03c4\u03b5 \u03b1\u03bd \u03b2\u03bf\u03b7\u03b8\u03ac \u03b7 soft distribution \u03ae \u03b1\u03c0\u03bb\u03ce\u03c2 \u03b7 \u03c0\u03c1\u03cc\u03c3\u03b8\u03b5\u03c4\u03b7 \u03ad\u03ba\u03b8\u03b5\u03c3\u03b7.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">\u0421\u0442\u044a\u043f\u043a\u0430 6<\/span><strong>\u0395\u03bb\u03ad\u03b3\u03be\u03c4\u03b5 per-slice trade-offs<\/strong>\n<p>\u0391\u03bd\u03b1\u03bb\u03cd\u03c3\u03c4\u03b5 target score, OOD recall, recognition, \u03b3\u03bb\u03ce\u03c3\u03c3\u03b1, latency, training memory \u03ba\u03b1\u03b9 \u03ba\u03cc\u03c3\u03c4\u03bf\u03c2. \u039c\u03b7\u03bd \u03b5\u03b3\u03ba\u03c1\u03af\u03bd\u03b5\u03c4\u03b5 \u03b2\u03b5\u03bb\u03c4\u03af\u03c9\u03c3\u03b7 \u03c0\u03bf\u03c5 \u03ba\u03c1\u03cd\u03b2\u03b5\u03b9 \u03ba\u03c1\u03af\u03c3\u03b9\u03bc\u03b7 \u03c5\u03c0\u03bf\u03b2\u03ac\u03b8\u03bc\u03b9\u03c3\u03b7.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">\u0421\u0442\u044a\u043f\u043a\u0430 7<\/span><strong>\u0398\u03ad\u03c3\u03c4\u03b5 release gate \u03ba\u03b1\u03b9 rollback<\/strong>\n<p>\u0394\u03b7\u03bc\u03bf\u03c3\u03b9\u03b5\u03cd\u03c3\u03c4\u03b5 \u03bc\u03cc\u03bd\u03bf \u03cc\u03c4\u03b1\u03bd \u03c0\u03b5\u03c1\u03bd\u03bf\u03cd\u03bd \u03bf\u03b9 \u03ba\u03c1\u03af\u03c3\u03b9\u03bc\u03b5\u03c2 regression \u03ba\u03b1\u03c4\u03b7\u03b3\u03bf\u03c1\u03af\u03b5\u03c2. \u03a3\u03b5 drift, \u03b5\u03c0\u03b9\u03c3\u03c4\u03c1\u03ad\u03c8\u03c4\u03b5 \u03c3\u03c4\u03b7\u03bd \u03c0\u03c1\u03bf\u03b7\u03b3\u03bf\u03cd\u03bc\u03b5\u03bd\u03b7 \u03ad\u03ba\u03b4\u03bf\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03ba\u03c1\u03b1\u03c4\u03ae\u03c3\u03c4\u03b5 \u03c4\u03b1 failed cases \u03c9\u03c2 \u03bd\u03ad\u03b1 tests.<\/p>\n<\/li>\n<\/ol>\n<\/div>\n<p>\u03a4\u03bf monitoring \u03bc\u03b5\u03c4\u03ac \u03c4\u03bf release \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03b4\u03b9\u03b1\u03c4\u03b7\u03c1\u03b5\u03af \u03c4\u03bf \u03af\u03b4\u03b9\u03bf taxonomy. \u0388\u03bd\u03b1 verbose answer, \u03bc\u03b9\u03b1 \u03bb\u03ac\u03b8\u03bf\u03c2 \u03bf\u03bd\u03c4\u03cc\u03c4\u03b7\u03c4\u03b1 \u03ba\u03b1\u03b9 \u03bc\u03b9\u03b1 \u03ac\u03c1\u03bd\u03b7\u03c3\u03b7 \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03bc\u03af\u03b1 \u03b5\u03bd\u03b9\u03b1\u03af\u03b1 \u03ba\u03b1\u03c4\u03b7\u03b3\u03bf\u03c1\u03af\u03b1 \u00abhallucination\u00bb. \u0397 \u03b1\u03ba\u03c1\u03b9\u03b2\u03ae\u03c2 \u03b5\u03c4\u03b9\u03ba\u03ad\u03c4\u03b1 \u03bc\u03b5\u03b9\u03ce\u03bd\u03b5\u03b9 \u03c4\u03bf\u03bd \u03c7\u03c1\u03cc\u03bd\u03bf \u03b4\u03b9\u03ac\u03b3\u03bd\u03c9\u03c3\u03b7\u03c2 \u03ba\u03b1\u03b9 \u03b2\u03bf\u03b7\u03b8\u03ac \u03c4\u03b7\u03bd \u03bf\u03bc\u03ac\u03b4\u03b1 \u03bd\u03b1 \u03b1\u03c0\u03bf\u03c6\u03b1\u03c3\u03af\u03c3\u03b5\u03b9 \u03b1\u03bd \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 prompt repair, data repair, \u03bd\u03ad\u03b1 anchor examples \u03ae \u03b5\u03ba \u03bd\u03ad\u03bf\u03c5 fine-tuning.<\/p>\n<h2 id=\"sosto-symperasma\">\u03a4\u03bf \u03c3\u03c9\u03c3\u03c4\u03cc \u03c3\u03c5\u03bc\u03c0\u03ad\u03c1\u03b1\u03c3\u03bc\u03b1 \u03b3\u03b9\u03b1 \u03c4\u03bf RAD \u03c3\u03c4\u03b7\u03bd AI<\/h2>\n<p>\u03a4\u03bf RAD \u03bc\u03b5\u03c4\u03b1\u03c6\u03ad\u03c1\u03b5\u03b9 \u03c4\u03b7 \u03c3\u03c5\u03b6\u03ae\u03c4\u03b7\u03c3\u03b7 \u03b1\u03c0\u03cc \u03c4\u03bf \u03b1\u03c3\u03b1\u03c6\u03ad\u03c2 \u00ab\u03c4\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03be\u03ad\u03c7\u03b1\u03c3\u03b5\u00bb \u03c3\u03c4\u03b7 \u03bc\u03b5\u03c4\u03c1\u03ae\u03c3\u03b9\u03bc\u03b7 \u03b5\u03c1\u03ce\u03c4\u03b7\u03c3\u03b7 \u00ab\u03c4\u03b9 \u03c7\u03ac\u03bb\u03b1\u03c3\u03b5 \u03b1\u03bd\u03ac\u03bc\u03b5\u03c3\u03b1 \u03c3\u03c4\u03b7 \u03b3\u03bd\u03ce\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03c3\u03c4\u03b7\u03bd \u03c4\u03b5\u03bb\u03b9\u03ba\u03ae \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7;\u00bb. \u0397 \u03b5\u03c1\u03b3\u03b1\u03c3\u03af\u03b1 \u03b4\u03b5\u03af\u03c7\u03bd\u03b5\u03b9 \u03cc\u03c4\u03b9 domain SFT \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b4\u03b9\u03b1\u03c4\u03b7\u03c1\u03b5\u03af constrained recognition \u03b5\u03bd\u03ce \u03c5\u03c0\u03bf\u03b2\u03b1\u03b8\u03bc\u03af\u03b6\u03b5\u03b9 \u03c4\u03b7\u03bd \u03b1\u03bd\u03bf\u03b9\u03ba\u03c4\u03ae \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae \u03ba\u03b1\u03b9 \u03cc\u03c4\u03b9 \u03b7 soft distribution \u03c4\u03bf\u03c5 base model \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03c0\u03b5\u03c1\u03b9\u03bf\u03c1\u03af\u03c3\u03b5\u03b9 \u03bc\u03ad\u03c1\u03bf\u03c2 \u03b1\u03c5\u03c4\u03ae\u03c2 \u03c4\u03b7\u03c2 \u03bc\u03b5\u03c4\u03b1\u03c4\u03cc\u03c0\u03b9\u03c3\u03b7\u03c2.<\/p>\n<p>\u0393\u03b9\u03b1 \u03bc\u03b9\u03b1 \u03b5\u03c0\u03b9\u03c7\u03b5\u03af\u03c1\u03b7\u03c3\u03b7, \u03c4\u03bf \u03c3\u03b7\u03bc\u03b1\u03bd\u03c4\u03b9\u03ba\u03cc\u03c4\u03b5\u03c1\u03bf \u03b1\u03c0\u03bf\u03c4\u03ad\u03bb\u03b5\u03c3\u03bc\u03b1 \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03bf \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03bf\u03c2 \u03b1\u03bb\u03b3\u03cc\u03c1\u03b9\u03b8\u03bc\u03bf\u03c2 \u03b1\u03bb\u03bb\u03ac \u03b7 \u03b4\u03b9\u03b1\u03b3\u03bd\u03c9\u03c3\u03c4\u03b9\u03ba\u03ae \u03c0\u03b5\u03b9\u03b8\u03b1\u03c1\u03c7\u03af\u03b1: same-fact tests, \u03c0\u03bf\u03bb\u03bb\u03b1\u03c0\u03bb\u03ac evaluation formats, baseline \u03bc\u03b5 \u03af\u03b4\u03b9\u03b1 \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03b1, \u03b1\u03ba\u03c1\u03b9\u03b2\u03ae claim boundaries \u03ba\u03b1\u03b9 release gates. \u0397 \u03b1\u03be\u03b9\u03cc\u03c0\u03b9\u03c3\u03c4\u03b7 <a href=\"https:\/\/twodots.gr\/aftomatismoi-epicheiriseon-ai\/\">\u03b1\u03c5\u03c4\u03bf\u03bc\u03b1\u03c4\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7 \u03b5\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03ae\u03c3\u03b5\u03c9\u03bd \u03bc\u03b5 AI<\/a> \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03bd\u03b1 \u03b3\u03bd\u03c9\u03c1\u03af\u03b6\u03b5\u03b9 \u03cc\u03c7\u03b9 \u03bc\u03cc\u03bd\u03bf \u03b1\u03bd \u03bc\u03b9\u03b1 \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7 \u03ae\u03c4\u03b1\u03bd \u03bb\u03ac\u03b8\u03bf\u03c2, \u03b1\u03bb\u03bb\u03ac \u03ba\u03b1\u03b9 \u03c0\u03bf\u03b9\u03bf \u03c3\u03c4\u03ac\u03b4\u03b9\u03bf \u03c0\u03c1\u03cc\u03c3\u03b2\u03b1\u03c3\u03b7\u03c2, \u03b1\u03bd\u03ac\u03ba\u03bb\u03b7\u03c3\u03b7\u03c2 \u03ae \u03ad\u03ba\u03c6\u03c1\u03b1\u03c3\u03b7\u03c2 \u03b1\u03c0\u03ad\u03c4\u03c5\u03c7\u03b5.<\/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 fine-tuning \u03c3\u03c4\u03bf \u03b5\u03bb\u03b5\u03b3\u03c7\u03cc\u03bc\u03b5\u03bd\u03bf release<\/p>\n<p class=\"td-service-cta-title\">\u03a3\u03c7\u03b5\u03b4\u03b9\u03ac\u03c3\u03c4\u03b5 AI workflows \u03bc\u03b5 regression gates \u03ba\u03b1\u03b9 \u03c3\u03b1\u03c6\u03ae \u03b4\u03b9\u03ac\u03b3\u03bd\u03c9\u03c3\u03b7 \u03b1\u03c0\u03bf\u03c4\u03c5\u03c7\u03af\u03b1\u03c2<\/p>\n<p>\u0397 TWO DOTS \u03c3\u03c5\u03bd\u03b4\u03ad\u03b5\u03b9 \u03b5\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03b7\u03c3\u03b9\u03b1\u03ba\u03ac \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03b1, \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03b1, deterministic validation \u03ba\u03b1\u03b9 \u03b1\u03bd\u03b8\u03c1\u03ce\u03c0\u03b9\u03bd\u03b7 \u03ad\u03b3\u03ba\u03c1\u03b9\u03c3\u03b7, \u03ce\u03c3\u03c4\u03b5 \u03b7 \u03b5\u03be\u03b5\u03b9\u03b4\u03af\u03ba\u03b5\u03c5\u03c3\u03b7 \u03bd\u03b1 \u03bc\u03b5\u03c4\u03c1\u03b9\u03ad\u03c4\u03b1\u03b9 \u03b1\u03c0\u03ad\u03bd\u03b1\u03bd\u03c4\u03b9 \u03c3\u03c4\u03b9\u03c2 \u03b9\u03ba\u03b1\u03bd\u03cc\u03c4\u03b7\u03c4\u03b5\u03c2 \u03c0\u03bf\u03c5 \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03b4\u03b9\u03b1\u03c4\u03b7\u03c1\u03b7\u03b8\u03bf\u03cd\u03bd.<\/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 \u03c4\u03bf AI workflow \u03c3\u03b1\u03c2<\/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 factual access failure;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u0395\u03af\u03bd\u03b1\u03b9 \u03b7 \u03c3\u03c5\u03bc\u03c0\u03b5\u03c1\u03b9\u03c6\u03bf\u03c1\u03b9\u03ba\u03ae \u03c0\u03b5\u03c1\u03af\u03c0\u03c4\u03c9\u03c3\u03b7 \u03cc\u03c0\u03bf\u03c5 \u03ad\u03bd\u03b1 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03b5\u03be\u03b1\u03ba\u03bf\u03bb\u03bf\u03c5\u03b8\u03b5\u03af \u03bd\u03b1 \u03b1\u03bd\u03b1\u03b3\u03bd\u03c9\u03c1\u03af\u03b6\u03b5\u03b9 \u03ae \u03bd\u03b1 \u03ba\u03b1\u03c4\u03b1\u03c4\u03ac\u03c3\u03c3\u03b5\u03b9 \u03c3\u03c9\u03c3\u03c4\u03ac \u03ad\u03bd\u03b1 fact \u03c5\u03c0\u03cc constrained evaluation, \u03b1\u03bb\u03bb\u03ac \u03b1\u03c0\u03bf\u03c4\u03c5\u03b3\u03c7\u03ac\u03bd\u03b5\u03b9 \u03bd\u03b1 \u03c4\u03bf \u03c0\u03b1\u03c1\u03b1\u03b3\u03ac\u03b3\u03b5\u03b9 \u03c3\u03b5 \u03b1\u03bd\u03bf\u03b9\u03ba\u03c4\u03ae \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u0395\u03af\u03bd\u03b1\u03b9 \u03ba\u03ac\u03b8\u03b5 \u03c0\u03c4\u03ce\u03c3\u03b7 \u03bc\u03b5\u03c4\u03ac \u03c4\u03bf SFT \u03ba\u03b1\u03c4\u03b1\u03c3\u03c4\u03c1\u03bf\u03c6\u03b9\u03ba\u03ae \u03bb\u03ae\u03b8\u03b7;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u038c\u03c7\u03b9. \u0397 \u03b5\u03c1\u03b3\u03b1\u03c3\u03af\u03b1 \u03b2\u03c1\u03af\u03c3\u03ba\u03b5\u03b9 genuine wrong-entity errors, \u03b1\u03bb\u03bb\u03ac \u03ba\u03b1\u03b9 format, verbosity \u03ba\u03b1\u03b9 exact-match failures. \u03a7\u03c1\u03b5\u03b9\u03ac\u03b6\u03bf\u03bd\u03c4\u03b1\u03b9 same-fact probes \u03c0\u03c1\u03b9\u03bd \u03b1\u03c0\u03bf\u03b4\u03bf\u03b8\u03b5\u03af \u03b7 \u03c0\u03c4\u03ce\u03c3\u03b7 \u03c3\u03b5 \u03b4\u03b9\u03b1\u03b3\u03c1\u03b1\u03c6\u03ae \u03b3\u03bd\u03ce\u03c3\u03b7\u03c2.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u03a4\u03b9 \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03b1 \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03c4\u03bf RAD;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u03a7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03c4\u03bf supervised dataset \u03c4\u03bf\u03c5 target domain \u03ba\u03b1\u03b9 \u03bc\u03b7 \u03b5\u03c0\u03b9\u03c3\u03b7\u03bc\u03b1\u03c3\u03bc\u03ad\u03bd\u03bf OOD \u03ba\u03b5\u03af\u03bc\u03b5\u03bd\u03bf \u03c3\u03b5 \u03b6\u03b5\u03cd\u03b3\u03b7 prefix\u2013continuation. \u0394\u03b5\u03bd \u03b1\u03c0\u03b1\u03b9\u03c4\u03b5\u03af gold OOD \u03b1\u03c0\u03b1\u03bd\u03c4\u03ae\u03c3\u03b5\u03b9\u03c2 \u03ae \u03b5\u03be\u03c9\u03c4\u03b5\u03c1\u03b9\u03ba\u03cc judge.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u0393\u03b9\u03b1\u03c4\u03af \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03b5\u03af\u03c4\u03b1\u03b9 \u03c4\u03bf base model \u03c9\u03c2 teacher;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u0397 soft next-token distribution \u03c4\u03b7\u03c2 \u03b2\u03ac\u03c3\u03b7\u03c2 \u03b1\u03c0\u03bf\u03c4\u03c5\u03c0\u03ce\u03bd\u03b5\u03b9 \u03c4\u03b9\u03c2 \u03c3\u03c7\u03b5\u03c4\u03b9\u03ba\u03ad\u03c2 \u03c0\u03c1\u03bf\u03c4\u03b9\u03bc\u03ae\u03c3\u03b5\u03b9\u03c2 \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae\u03c2 \u03c0\u03c1\u03b9\u03bd \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03c0\u03c1\u03bf\u03c3\u03b1\u03c1\u03bc\u03bf\u03b3\u03ae \u03ba\u03b1\u03b9 \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03b5\u03af \u03c9\u03c2 \u03b1\u03b3\u03ba\u03cd\u03c1\u03c9\u03c3\u03b7 \u03b3\u03b9\u03b1 \u03c4\u03bf\u03bd LoRA student.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u03a4\u03bf RAD \u03b5\u03c0\u03b1\u03bd\u03b1\u03c6\u03ad\u03c1\u03b5\u03b9 \u03c0\u03bb\u03ae\u03c1\u03c9\u03c2 \u03c4\u03b7\u03bd \u03b1\u03c1\u03c7\u03b9\u03ba\u03ae \u03b1\u03c0\u03cc\u03b4\u03bf\u03c3\u03b7;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u038c\u03c7\u03b9. \u03a3\u03c4\u03b1 \u03c4\u03c1\u03af\u03b1 backbones \u03b1\u03bd\u03b1\u03ba\u03c4\u03ac \u03bc\u03ad\u03c1\u03bf\u03c2 \u03c4\u03b7\u03c2 \u03c7\u03b1\u03bc\u03ad\u03bd\u03b7\u03c2 OOD factual \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae\u03c2, \u03b1\u03bb\u03bb\u03ac \u03b4\u03b5\u03bd \u03b5\u03c0\u03b9\u03c3\u03c4\u03c1\u03ad\u03c6\u03b5\u03b9 \u03c3\u03c4\u03b1\u03b8\u03b5\u03c1\u03ac \u03c3\u03c4\u03bf base score \u03ba\u03b1\u03b9 \u03b4\u03b5\u03bd \u03b5\u03b3\u03b3\u03c5\u03ac\u03c4\u03b1\u03b9 \u03b4\u03b9\u03b1\u03c4\u03ae\u03c1\u03b7\u03c3\u03b7 \u03ba\u03ac\u03b8\u03b5 \u03b9\u03ba\u03b1\u03bd\u03cc\u03c4\u03b7\u03c4\u03b1\u03c2.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u0391\u03c5\u03be\u03ac\u03bd\u03b5\u03b9 \u03c4\u03bf \u03ba\u03cc\u03c3\u03c4\u03bf\u03c2 inference;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u0397 inference-time \u03b1\u03c1\u03c7\u03b9\u03c4\u03b5\u03ba\u03c4\u03bf\u03bd\u03b9\u03ba\u03ae \u03c0\u03b1\u03c1\u03b1\u03bc\u03ad\u03bd\u03b5\u03b9 \u03af\u03b4\u03b9\u03b1 \u03bc\u03b5 \u03c4\u03bf LoRA SFT. \u03a4\u03bf \u03c0\u03c1\u03cc\u03c3\u03b8\u03b5\u03c4\u03bf \u03ba\u03cc\u03c3\u03c4\u03bf\u03c2 \u03b2\u03c1\u03af\u03c3\u03ba\u03b5\u03c4\u03b1\u03b9 \u03c3\u03c4\u03b7\u03bd \u03b5\u03ba\u03c0\u03b1\u03af\u03b4\u03b5\u03c5\u03c3\u03b7, \u03b5\u03c0\u03b5\u03b9\u03b4\u03ae \u03ba\u03ac\u03b8\u03b5 OOD batch \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03ad\u03bd\u03b1 \u03b5\u03c0\u03b9\u03c0\u03bb\u03ad\u03bf\u03bd adapter-off forward pass.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u0393\u03b9\u03b1\u03c4\u03af \u03c4\u03bf replay \u03b4\u03b5\u03bd \u03ad\u03b4\u03c9\u03c3\u03b5 \u03c4\u03bf \u03af\u03b4\u03b9\u03bf \u03b1\u03c0\u03bf\u03c4\u03ad\u03bb\u03b5\u03c3\u03bc\u03b1;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u03a4\u03bf replay \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b5 \u03c4\u03bf \u03af\u03b4\u03b9\u03bf OOD \u03ba\u03b5\u03af\u03bc\u03b5\u03bd\u03bf \u03c9\u03c2 hard next-token labels, \u03b5\u03bd\u03ce \u03c4\u03bf RAD \u03b4\u03b9\u03b1\u03c4\u03ae\u03c1\u03b7\u03c3\u03b5 \u03c4\u03b7 soft distribution \u03c4\u03b7\u03c2 \u03b2\u03ac\u03c3\u03b7\u03c2. \u03a3\u03c4\u03bf \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03bf setup, \u03c4\u03bf \u03b4\u03b5\u03cd\u03c4\u03b5\u03c1\u03bf \u03c0\u03c1\u03bf\u03c3\u03c4\u03ac\u03c4\u03b5\u03c8\u03b5 \u03ba\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03b1 \u03c4\u03b7\u03bd \u03b1\u03bd\u03bf\u03b9\u03ba\u03c4\u03ae \u03b1\u03bd\u03ac\u03ba\u03bb\u03b7\u03c3\u03b7.<\/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 \u03b2\u03b1\u03c3\u03b9\u03ba\u03cc \u03bc\u03ac\u03b8\u03b7\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 \u03b1\u03be\u03b9\u03bf\u03bb\u03bf\u03b3\u03b5\u03af \u03c7\u03c9\u03c1\u03b9\u03c3\u03c4\u03ac \u03b1\u03bd\u03bf\u03b9\u03ba\u03c4\u03ae \u03b1\u03bd\u03ac\u03ba\u03bb\u03b7\u03c3\u03b7, recognition \u03ba\u03b1\u03b9 format \u03c4\u03bf\u03c5 \u03af\u03b4\u03b9\u03bf\u03c5 fact, \u03bc\u03b5 OOD regression suite, per-language slices, baselines \u03ba\u03b1\u03b9 rollback threshold \u03c0\u03c1\u03b9\u03bd \u03b1\u03c0\u03cc \u03c4\u03bf release.<\/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\/2608.20794\" target=\"_blank\" rel=\"noopener\">Chen et al. \u2014 Knowing but Not Saying: Preventing Factual Access Failures in LLM SFT via Recall-Anchored Distillation, arXiv metadata<\/a><\/li>\n<li><a href=\"https:\/\/arxiv.org\/html\/2608.20794v1\" target=\"_blank\" rel=\"noopener\">Chen et al. \u2014 \u03a0\u03bb\u03ae\u03c1\u03b5\u03c2 HTML paper \u03bc\u03b5 methodology, main results \u03ba\u03b1\u03b9 ablations \u03c4\u03bf\u03c5 RAD<\/a><\/li>\n<li><a href=\"https:\/\/arxiv.org\/abs\/2203.14371\" target=\"_blank\" rel=\"noopener\">Pal, Umapathi \u03ba\u03b1\u03b9 Sankarasubbu \u2014 MedMCQA: A Large-scale Multi-Subject Multi-Choice Dataset for Medical domain Question Answering<\/a><\/li>\n<li><a href=\"https:\/\/arxiv.org\/abs\/2106.09685\" target=\"_blank\" rel=\"noopener\">Hu et al. \u2014 LoRA: Low-Rank Adaptation of Large Language Models<\/a><\/li>\n<li><a href=\"https:\/\/www.nist.gov\/publications\/artificial-intelligence-risk-management-framework-ai-rmf-10\" target=\"_blank\" rel=\"noopener\">NIST \u2014 Artificial Intelligence Risk Management Framework 1.0<\/a><\/li>\n<\/ul>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>\u03a4\u03bf Recall-Anchored Distillation \u03be\u03b5\u03c7\u03c9\u03c1\u03af\u03b6\u03b5\u03b9 \u03c4\u03b7\u03bd \u03b1\u03c0\u03ce\u03bb\u03b5\u03b9\u03b1 \u03b3\u03bd\u03ce\u03c3\u03b7\u03c2 \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03b1\u03c0\u03bf\u03c4\u03c5\u03c7\u03af\u03b1 \u03c0\u03c1\u03cc\u03c3\u03b2\u03b1\u03c3\u03b7\u03c2 \u03bc\u03b5\u03c4\u03ac \u03c4\u03bf fine-tuning \u03ba\u03b1\u03b9 \u03b4\u03b5\u03af\u03c7\u03bd\u03b5\u03b9 \u03c0\u03ce\u03c2 \u03b5\u03bb\u03ad\u03b3\u03c7\u03b5\u03c4\u03b1\u03b9 \u03b7 \u03b1\u03bd\u03bf\u03b9\u03ba\u03c4\u03ae \u03b1\u03bd\u03ac\u03ba\u03bb\u03b7\u03c3\u03b7.<\/p>","protected":false},"author":1,"featured_media":97676,"comment_status":"open","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_gspb_post_css":"","content-type":"","footnotes":""},"categories":[199],"tags":[20383,20381,19275,20382,18285],"class_list":["post-97127","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-techniti-noimosyni","tag-factual-access-failure","tag-fine-tuning-llm","tag-lora","tag-recall-anchored-distillation","tag-axiologisi-ai"],"blocksy_meta":{"styles_descriptor":{"styles":{"desktop":"","tablet":"","mobile":""},"google_fonts":[],"version":8}},"_links":{"self":[{"href":"https:\/\/twodots.gr\/bg\/wp-json\/wp\/v2\/posts\/97127","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=97127"}],"version-history":[{"count":1,"href":"https:\/\/twodots.gr\/bg\/wp-json\/wp\/v2\/posts\/97127\/revisions"}],"predecessor-version":[{"id":97677,"href":"https:\/\/twodots.gr\/bg\/wp-json\/wp\/v2\/posts\/97127\/revisions\/97677"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/twodots.gr\/bg\/wp-json\/wp\/v2\/media\/97676"}],"wp:attachment":[{"href":"https:\/\/twodots.gr\/bg\/wp-json\/wp\/v2\/media?parent=97127"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/twodots.gr\/bg\/wp-json\/wp\/v2\/categories?post=97127"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/twodots.gr\/bg\/wp-json\/wp\/v2\/tags?post=97127"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}