{"id":88349,"date":"2026-08-08T11:40:55","date_gmt":"2026-08-08T08:40:55","guid":{"rendered":"https:\/\/twodots.gr\/?p=88349"},"modified":"2026-08-08T11:40:57","modified_gmt":"2026-08-08T08:40:57","slug":"self-distillation-llms-pi-bias-reasoning","status":"publish","type":"post","link":"https:\/\/twodots.gr\/en\/self-distillation-llms-pi-bias-reasoning\/","title":{"rendered":"Self-distillation \u03c3\u03c4\u03b1 LLMs: \u03cc\u03c4\u03b1\u03bd \u03b7 \u03bc\u03af\u03bc\u03b7\u03c3\u03b7 \u03bc\u03b9\u03b1\u03c2 \u03c3\u03c9\u03c3\u03c4\u03ae\u03c2 \u03bb\u03cd\u03c3\u03b7\u03c2 \u03b2\u03bb\u03ac\u03c0\u03c4\u03b5\u03b9 \u03c4\u03bf reasoning"},"content":{"rendered":"<div class=\"td-article-lede\">\n<p><strong>\u03a4\u03bf self-distillation \u03c3\u03c4\u03b1 LLMs \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03c1\u03af\u03c7\u03bd\u03b5\u03b9 \u03c3\u03c4\u03b1\u03b8\u03b5\u03c1\u03ac \u03c4\u03bf training loss \u03c7\u03c9\u03c1\u03af\u03c2 \u03bd\u03b1 \u03b2\u03b5\u03bb\u03c4\u03b9\u03ce\u03bd\u03b5\u03b9 \u03c4\u03bf reasoning.<\/strong> \u03a3\u03c4\u03b7 \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03b7 \u03bc\u03b5\u03bb\u03ad\u03c4\u03b7, \u03cc\u03c4\u03b1\u03bd \u03ad\u03bd\u03b1\u03c2 self-teacher \u03ad\u03b2\u03bb\u03b5\u03c0\u03b5 \u03bc\u03af\u03b1 \u03c3\u03c9\u03c3\u03c4\u03ae \u03bb\u03cd\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03bf student \u03b5\u03ba\u03c0\u03b1\u03b9\u03b4\u03b5\u03c5\u03cc\u03c4\u03b1\u03bd \u03bc\u03cc\u03bd\u03bf \u03bd\u03b1 \u03bc\u03b9\u03bc\u03b7\u03b8\u03b5\u03af \u03c4\u03b9\u03c2 token-level \u03c0\u03c1\u03bf\u03b2\u03bb\u03ad\u03c8\u03b5\u03b9\u03c2 \u03c4\u03bf\u03c5, \u03b7 validation accuracy \u03ad\u03bc\u03b5\u03bd\u03b5 \u03c3\u03c4\u03ac\u03c3\u03b9\u03bc\u03b7 \u03ae \u03c3\u03c5\u03bd\u03ae\u03b8\u03c9\u03c2 \u03c7\u03b5\u03b9\u03c1\u03bf\u03c4\u03ad\u03c1\u03b5\u03c5\u03b5. \u03a4\u03bf \u03c0\u03c1\u03b1\u03ba\u03c4\u03b9\u03ba\u03cc \u03bc\u03ac\u03b8\u03b7\u03bc\u03b1 \u03b3\u03b9\u03b1 AI \u03c0\u03c1\u03bf\u03ca\u03cc\u03bd\u03c4\u03b1 \u03ba\u03b1\u03b9 agents \u03b5\u03af\u03bd\u03b1\u03b9 \u03c3\u03b1\u03c6\u03ad\u03c2: \u03b7 \u03bf\u03c1\u03b8\u03cc\u03c4\u03b7\u03c4\u03b1 \u03c4\u03bf\u03c5 task \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03b1\u03bd\u03b5\u03be\u03ac\u03c1\u03c4\u03b7\u03c4\u03b7 \u03bc\u03ad\u03c4\u03c1\u03b7\u03c3\u03b7\u00b7 \u03c4\u03bf \u03c7\u03b1\u03bc\u03b7\u03bb\u03cc\u03c4\u03b5\u03c1\u03bf loss \u03b4\u03b5\u03bd \u03b1\u03c1\u03ba\u03b5\u03af.<\/p>\n<\/div>\n<div class=\"td-article-toc\">\n<div class=\"td-toc-title\">Contents<\/div>\n<ul>\n<li><a href=\"#ti-einai-self-distillation\">\u03a4\u03b9 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c4\u03bf self-distillation \u03ba\u03b1\u03b9 \u03c0\u03bf\u03cd \u03b2\u03c1\u03af\u03c3\u03ba\u03b5\u03c4\u03b1\u03b9 \u03bf \u03ba\u03af\u03bd\u03b4\u03c5\u03bd\u03bf\u03c2<\/a><\/li>\n<li><a href=\"#pos-elegchthike\">\u03a0\u03ce\u03c2 \u03b5\u03bb\u03ad\u03b3\u03c7\u03b8\u03b7\u03ba\u03b5 \u03b7 \u03c5\u03c0\u03cc\u03b8\u03b5\u03c3\u03b7 \u03c3\u03b5 \u03c4\u03ad\u03c3\u03c3\u03b5\u03c1\u03b1 domains<\/a><\/li>\n<li><a href=\"#training-signature\">\u03a4\u03bf training signature: \u03ba\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03bf loss, \u03cc\u03c7\u03b9 \u03ba\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03b7 \u03b9\u03ba\u03b1\u03bd\u03cc\u03c4\u03b7\u03c4\u03b1<\/a><\/li>\n<li><a href=\"#pi-bias\">PI bias: \u03bc\u03af\u03b1 \u03b4\u03b9\u03b1\u03b4\u03c1\u03bf\u03bc\u03ae \u03b1\u03bd\u03c4\u03af \u03b3\u03b9\u03b1 \u03c4\u03b7\u03bd \u03ad\u03bd\u03bd\u03bf\u03b9\u03b1 \u03c4\u03bf\u03c5 \u03c3\u03c9\u03c3\u03c4\u03bf\u03cd<\/a><\/li>\n<li><a href=\"#loss-sosta-lathos\">\u0393\u03b9\u03b1\u03c4\u03af \u03c4\u03bf loss \u03b4\u03b5\u03bd \u03be\u03b5\u03c7\u03c9\u03c1\u03af\u03b6\u03b5\u03b9 \u03c3\u03c9\u03c3\u03c4\u03ac \u03ba\u03b1\u03b9 \u03bb\u03b1\u03bd\u03b8\u03b1\u03c3\u03bc\u03ad\u03bd\u03b1 rollouts<\/a><\/li>\n<li><a href=\"#tokens-xamilis-pliroforias\">\u038c\u03c4\u03b1\u03bd \u03c4\u03bf loss \u03c0\u03b7\u03b3\u03b1\u03af\u03bd\u03b5\u03b9 \u03c3\u03b5 tokens \u03c7\u03b1\u03bc\u03b7\u03bb\u03ae\u03c2 \u03c0\u03bb\u03b7\u03c1\u03bf\u03c6\u03bf\u03c1\u03af\u03b1\u03c2<\/a><\/li>\n<li><a href=\"#penalty-exploration\">\u03a0\u03ce\u03c2 \u03b7 \u03bc\u03af\u03bc\u03b7\u03c3\u03b7 \u03c4\u03b9\u03bc\u03c9\u03c1\u03b5\u03af \u03c4\u03b7\u03bd \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03b9\u03ba\u03ae \u03b5\u03be\u03b5\u03c1\u03b5\u03cd\u03bd\u03b7\u03c3\u03b7<\/a><\/li>\n<li><a href=\"#robustness-weaker-pi\">Robustness tests \u03ba\u03b1\u03b9 \u03b1\u03c3\u03b8\u03b5\u03bd\u03ad\u03c3\u03c4\u03b5\u03c1\u03b7 privileged information<\/a><\/li>\n<li><a href=\"#ti-simainei-ai-products\">\u03a4\u03b9 \u03c3\u03b7\u03bc\u03b1\u03af\u03bd\u03b5\u03b9 \u03b3\u03b9\u03b1 AI \u03c0\u03c1\u03bf\u03ca\u03cc\u03bd\u03c4\u03b1, agents \u03ba\u03b1\u03b9 \u03b5\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03ae\u03c3\u03b5\u03b9\u03c2<\/a><\/li>\n<li><a href=\"#ti-den-apodeiknyei\">\u03a4\u03b9 \u03b4\u03b5\u03bd \u03b1\u03c0\u03bf\u03b4\u03b5\u03b9\u03ba\u03bd\u03cd\u03b5\u03b9 \u03b7 \u03bc\u03b5\u03bb\u03ad\u03c4\u03b7<\/a><\/li>\n<li><a href=\"#symperasma\">\u0391\u03c0\u03cc \u03c4\u03b7 \u03bc\u03af\u03bc\u03b7\u03c3\u03b7 \u03bc\u03b9\u03b1\u03c2 \u03bb\u03cd\u03c3\u03b7\u03c2 \u03c3\u03c4\u03b7 \u03bc\u03ad\u03c4\u03c1\u03b7\u03c3\u03b7 \u03c4\u03b7\u03c2 \u03bf\u03c1\u03b8\u03cc\u03c4\u03b7\u03c4\u03b1\u03c2<\/a><\/li>\n<\/ul>\n<\/div>\n<p>\u039c\u03c0\u03bf\u03c1\u03b5\u03af \u03ad\u03bd\u03b1 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03c4\u03b5\u03c7\u03bd\u03b7\u03c4\u03ae\u03c2 \u03bd\u03bf\u03b7\u03bc\u03bf\u03c3\u03cd\u03bd\u03b7\u03c2 \u03bd\u03b1 \u03bc\u03b5\u03b9\u03ce\u03bd\u03b5\u03b9 \u03c3\u03c4\u03b1\u03b8\u03b5\u03c1\u03ac \u03c4\u03bf training loss \u03ba\u03b1\u03b9 \u03c0\u03b1\u03c1\u2019 \u03cc\u03bb\u03b1 \u03b1\u03c5\u03c4\u03ac \u03bd\u03b1 \u03b3\u03af\u03bd\u03b5\u03c4\u03b1\u03b9 \u03c7\u03b5\u03b9\u03c1\u03cc\u03c4\u03b5\u03c1\u03bf \u03c3\u03c4\u03b7 \u03b4\u03bf\u03c5\u03bb\u03b5\u03b9\u03ac \u03b3\u03b9\u03b1 \u03c4\u03b7\u03bd \u03bf\u03c0\u03bf\u03af\u03b1 \u03b5\u03ba\u03c0\u03b1\u03b9\u03b4\u03b5\u03cd\u03b5\u03c4\u03b1\u03b9; \u0397 \u03bc\u03b5\u03bb\u03ad\u03c4\u03b7 <em>Privileged, but Biased: How PI-Conditioned Teachers Break Self-Distillation<\/em>, \u03c0\u03bf\u03c5 \u03c5\u03c0\u03bf\u03b2\u03bb\u03ae\u03b8\u03b7\u03ba\u03b5 \u03c3\u03c4\u03bf arXiv \u03c3\u03c4\u03b9\u03c2 5 \u0391\u03c5\u03b3\u03bf\u03cd\u03c3\u03c4\u03bf\u03c5 2026, \u03b1\u03c0\u03b1\u03bd\u03c4\u03ac \u00ab\u03bd\u03b1\u03b9\u00bb \u03b3\u03b9\u03b1 \u03ad\u03bd\u03b1 \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03bf \u03ba\u03b1\u03b9 \u03c3\u03b7\u03bc\u03b1\u03bd\u03c4\u03b9\u03ba\u03cc \u03c3\u03b5\u03bd\u03ac\u03c1\u03b9\u03bf: PI-conditioned self-distillation \u03c9\u03c2 \u03bc\u03bf\u03bd\u03b1\u03b4\u03b9\u03ba\u03cc training objective \u03c3\u03b5 \u03c3\u03cd\u03bd\u03b8\u03b5\u03c4\u03b5\u03c2 \u03b5\u03c1\u03b3\u03b1\u03c3\u03af\u03b5\u03c2 reasoning.<\/p>\n<p>\u039f\u03b9 Sarthak Harne, Chinmay Karkar, Yash Pandya, Ahmed Awadallah \u03ba\u03b1\u03b9 Akshay Nambi \u03b5\u03be\u03ad\u03c4\u03b1\u03c3\u03b1\u03bd \u03ad\u03bd\u03b1 \u03b5\u03bb\u03ba\u03c5\u03c3\u03c4\u03b9\u03ba\u03cc \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03b5\u03ba\u03c0\u03b1\u03af\u03b4\u03b5\u03c5\u03c3\u03b7\u03c2. \u03a4\u03bf \u03af\u03b4\u03b9\u03bf LLM \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03b5\u03af \u03c9\u03c2 teacher \u03ba\u03b1\u03b9 student. \u039f teacher \u03b2\u03bb\u03ad\u03c0\u03b5\u03b9 privileged information, \u03cc\u03c0\u03c9\u03c2 \u03bc\u03b9\u03b1 \u03ad\u03c4\u03bf\u03b9\u03bc\u03b7 \u03c3\u03c9\u03c3\u03c4\u03ae \u03bb\u03cd\u03c3\u03b7, \u03b5\u03bd\u03ce \u03bf student \u03b2\u03bb\u03ad\u03c0\u03b5\u03b9 \u03bc\u03cc\u03bd\u03bf \u03c4\u03bf \u03b1\u03c1\u03c7\u03b9\u03ba\u03cc \u03c0\u03c1\u03cc\u03b2\u03bb\u03b7\u03bc\u03b1. \u039f student \u03b5\u03ba\u03c0\u03b1\u03b9\u03b4\u03b5\u03cd\u03b5\u03c4\u03b1\u03b9 token \u03c0\u03c1\u03bf\u03c2 token \u03bd\u03b1 \u03c0\u03bb\u03b7\u03c3\u03b9\u03ac\u03c3\u03b5\u03b9 \u03c4\u03b7\u03bd \u03ba\u03b1\u03c4\u03b1\u03bd\u03bf\u03bc\u03ae \u03c4\u03bf\u03c5 teacher.<\/p>\n<p>\u0397 \u03c5\u03c0\u03cc\u03c3\u03c7\u03b5\u03c3\u03b7 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c0\u03c5\u03ba\u03bd\u03cc supervision \u03c7\u03c9\u03c1\u03af\u03c2 \u03be\u03b5\u03c7\u03c9\u03c1\u03b9\u03c3\u03c4\u03cc \u03bc\u03b5\u03b3\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03bf teacher \u03ba\u03b1\u03b9 \u03c7\u03c9\u03c1\u03af\u03c2 \u03bd\u03b1 \u03c3\u03c4\u03b7\u03c1\u03af\u03b6\u03b5\u03c4\u03b1\u03b9 \u03cc\u03bb\u03b7 \u03b7 \u03bc\u03ac\u03b8\u03b7\u03c3\u03b7 \u03c3\u03b5 \u03ad\u03bd\u03b1 \u03b1\u03c1\u03b1\u03b9\u03cc scalar reward. \u03a4\u03bf \u03ba\u03c1\u03af\u03c3\u03b9\u03bc\u03bf \u03b5\u03cd\u03c1\u03b7\u03bc\u03b1, \u03cc\u03bc\u03c9\u03c2, \u03b5\u03af\u03bd\u03b1\u03b9 \u03cc\u03c4\u03b9 \u03b7 \u03c5\u03c0\u03cc\u03c3\u03c7\u03b5\u03c3\u03b7 \u03b4\u03b5\u03bd \u03bc\u03b5\u03c4\u03b1\u03c6\u03ad\u03c1\u03b5\u03c4\u03b1\u03b9 \u03b1\u03c5\u03c4\u03cc\u03bc\u03b1\u03c4\u03b1 \u03b1\u03c0\u03cc \u03c3\u03cd\u03bd\u03c4\u03bf\u03bc\u03b5\u03c2, \u03ba\u03bb\u03b5\u03b9\u03c3\u03c4\u03ad\u03c2 \u03b5\u03c1\u03b3\u03b1\u03c3\u03af\u03b5\u03c2 \u03c3\u03b5 \u03b1\u03bd\u03bf\u03b9\u03c7\u03c4\u03ac \u03c0\u03c1\u03bf\u03b2\u03bb\u03ae\u03bc\u03b1\u03c4\u03b1 \u03bc\u03b5 \u03c0\u03bf\u03bb\u03bb\u03ad\u03c2 \u03bd\u03cc\u03bc\u03b9\u03bc\u03b5\u03c2 \u03b4\u03b9\u03b1\u03b4\u03c1\u03bf\u03bc\u03ad\u03c2. \u0393\u03b9\u03b1 \u03bf\u03bc\u03ac\u03b4\u03b5\u03c2 \u03c0\u03bf\u03c5 \u03b1\u03bd\u03b1\u03c0\u03c4\u03cd\u03c3\u03c3\u03bf\u03c5\u03bd AI assistants, agents \u03ae domain-specific \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03b1, \u03ad\u03bd\u03b1 \u03ba\u03b1\u03b8\u03b1\u03c1\u03cc training dashboard \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03ba\u03c1\u03cd\u03b2\u03b5\u03b9 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03c0\u03bf\u03c5 \u03bc\u03b9\u03bc\u03b5\u03af\u03c4\u03b1\u03b9 \u03ba\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03b1 \u03c4\u03bf \u03cd\u03c6\u03bf\u03c2 \u03bc\u03b9\u03b1\u03c2 \u03bb\u03cd\u03c3\u03b7\u03c2, \u03cc\u03c7\u03b9 \u03c4\u03b7 \u03bb\u03bf\u03b3\u03b9\u03ba\u03ae \u03c0\u03bf\u03c5 \u03c4\u03b7\u03bd \u03ad\u03ba\u03b1\u03bd\u03b5 \u03c3\u03c9\u03c3\u03c4\u03ae.<\/p>\n<h2 id=\"ti-einai-self-distillation\">\u03a4\u03b9 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c4\u03bf self-distillation \u03ba\u03b1\u03b9 \u03c0\u03bf\u03cd \u03b2\u03c1\u03af\u03c3\u03ba\u03b5\u03c4\u03b1\u03b9 \u03bf \u03ba\u03af\u03bd\u03b4\u03c5\u03bd\u03bf\u03c2<\/h2>\n<p>\u03a3\u03c4\u03bf reinforcement learning with verifiable rewards, \u03c4\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03c0\u03b1\u03c1\u03ac\u03b3\u03b5\u03b9 rollouts \u03ba\u03b1\u03b9 \u03bb\u03b1\u03bc\u03b2\u03ac\u03bd\u03b5\u03b9 \u03c3\u03ae\u03bc\u03b1 \u03b5\u03c0\u03b9\u03c4\u03c5\u03c7\u03af\u03b1\u03c2 \u03ae \u03b1\u03c0\u03bf\u03c4\u03c5\u03c7\u03af\u03b1\u03c2. \u0391\u03c5\u03c4\u03cc \u03c4\u03bf reward \u03c3\u03c5\u03bd\u03b4\u03ad\u03b5\u03c4\u03b1\u03b9 \u03bc\u03b5 \u03c4\u03b7\u03bd \u03bf\u03c1\u03b8\u03cc\u03c4\u03b7\u03c4\u03b1, \u03b1\u03bb\u03bb\u03ac \u03b5\u03af\u03bd\u03b1\u03b9 \u03b1\u03c1\u03b1\u03b9\u03cc: \u03ad\u03bd\u03b1 \u03b1\u03c0\u03bf\u03c4\u03ad\u03bb\u03b5\u03c3\u03bc\u03b1 \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03b1\u03c0\u03bf\u03b4\u03ce\u03c3\u03b5\u03b9 credit \u03c3\u03b5 \u03c0\u03bf\u03bb\u03bb\u03ac tokens, \u03b5\u03bd\u03ce \u03b1\u03c0\u03b1\u03b9\u03c4\u03bf\u03cd\u03bd\u03c4\u03b1\u03b9 verifier \u03ba\u03b1\u03b9 \u03b1\u03c1\u03ba\u03b5\u03c4\u03ac samples. \u0397 \u03ba\u03bb\u03b1\u03c3\u03b9\u03ba\u03ae distillation \u03c0\u03c1\u03bf\u03c3\u03c6\u03ad\u03c1\u03b5\u03b9 \u03c0\u03c5\u03ba\u03bd\u03cc\u03c4\u03b5\u03c1\u03bf \u03c3\u03ae\u03bc\u03b1, \u03b1\u03bb\u03bb\u03ac \u03c3\u03c5\u03bd\u03ae\u03b8\u03c9\u03c2 \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03b5\u03be\u03c9\u03c4\u03b5\u03c1\u03b9\u03ba\u03cc teacher, \u03c3\u03c5\u03c7\u03bd\u03ac \u03bc\u03b5\u03b3\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03bf \u03ba\u03b1\u03b9 \u03b1\u03ba\u03c1\u03b9\u03b2\u03cc\u03c4\u03b5\u03c1\u03bf.<\/p>\n<p>\u03a4\u03bf self-distillation \u03b5\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03b5\u03af \u03bd\u03b1 \u03c3\u03c5\u03bd\u03b4\u03c5\u03ac\u03c3\u03b5\u03b9 \u03c4\u03b1 \u03c0\u03bb\u03b5\u03bf\u03bd\u03b5\u03ba\u03c4\u03ae\u03bc\u03b1\u03c4\u03b1. \u039f self-teacher \u03b5\u03af\u03bd\u03b1\u03b9 \u03c4\u03bf \u03af\u03b4\u03b9\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf, \u03c0\u03c1\u03bf\u03c3\u03c9\u03c1\u03b9\u03bd\u03ac \u03b5\u03bd\u03b9\u03c3\u03c7\u03c5\u03bc\u03ad\u03bd\u03bf \u03bc\u03b5 privileged information (PI): \u03bc\u03b9\u03b1 reference solution, \u03ad\u03bd\u03b1 hint, \u03bc\u03b9\u03b1 \u03b4\u03b5\u03be\u03b9\u03cc\u03c4\u03b7\u03c4\u03b1 \u03ae feedback \u03b1\u03c0\u03cc \u03c4\u03bf \u03c0\u03b5\u03c1\u03b9\u03b2\u03ac\u03bb\u03bb\u03bf\u03bd. \u0395\u03c0\u03b5\u03b9\u03b4\u03ae \u03bf teacher \u03b3\u03bd\u03c9\u03c1\u03af\u03b6\u03b5\u03b9 \u03c0\u03b5\u03c1\u03b9\u03c3\u03c3\u03cc\u03c4\u03b5\u03c1\u03b1, \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03c0\u03c1\u03bf\u03c3\u03c6\u03ad\u03c1\u03b5\u03b9 \u03c3\u03c4\u03bf\u03bd student \u03bc\u03b9\u03b1 \u03ba\u03b1\u03c4\u03b1\u03bd\u03bf\u03bc\u03ae \u03c0\u03b9\u03b8\u03b1\u03bd\u03cc\u03c4\u03b7\u03c4\u03b1\u03c2 \u03b3\u03b9\u03b1 \u03ba\u03ac\u03b8\u03b5 \u03b5\u03c0\u03cc\u03bc\u03b5\u03bd\u03bf token. \u039c\u03ad\u03b8\u03bf\u03b4\u03bf\u03b9 \u03cc\u03c0\u03c9\u03c2 SDPO \u03ba\u03b1\u03b9 OPSD \u03b1\u03be\u03b9\u03bf\u03c0\u03bf\u03b9\u03bf\u03cd\u03bd \u03b1\u03c5\u03c4\u03ae \u03c4\u03b7\u03bd \u03c0\u03c5\u03ba\u03bd\u03ae \u03ba\u03b1\u03b8\u03bf\u03b4\u03ae\u03b3\u03b7\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03ad\u03c7\u03bf\u03c5\u03bd \u03b1\u03bd\u03b1\u03c6\u03ad\u03c1\u03b5\u03b9 \u03b8\u03b5\u03c4\u03b9\u03ba\u03ac \u03b1\u03c0\u03bf\u03c4\u03b5\u03bb\u03ad\u03c3\u03bc\u03b1\u03c4\u03b1 \u03c3\u03b5 \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03b1 settings.<\/p>\n<p>\u0397 \u03bd\u03ad\u03b1 \u03bc\u03b5\u03bb\u03ad\u03c4\u03b7 \u03b4\u03b5\u03bd \u03c5\u03c0\u03bf\u03c3\u03c4\u03b7\u03c1\u03af\u03b6\u03b5\u03b9 \u03cc\u03c4\u03b9 \u03ba\u03ac\u03b8\u03b5 self-distillation \u03b5\u03af\u03bd\u03b1\u03b9 \u03ac\u03c7\u03c1\u03b7\u03c3\u03c4\u03bf. \u03a1\u03c9\u03c4\u03ac \u03ba\u03ac\u03c4\u03b9 \u03c3\u03c4\u03b5\u03bd\u03cc\u03c4\u03b5\u03c1\u03bf: \u03b1\u03bd \u03ad\u03bd\u03b1 PI-conditioned, per-token objective \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03b7\u03b8\u03b5\u03af \u03bc\u03cc\u03bd\u03bf \u03c4\u03bf\u03c5, \u03c7\u03c9\u03c1\u03af\u03c2 reward term \u03c0\u03bf\u03c5 \u03bd\u03b1 \u03b4\u03b7\u03bb\u03ce\u03bd\u03b5\u03b9 \u03c0\u03bf\u03b9\u03bf \u03b1\u03c0\u03bf\u03c4\u03ad\u03bb\u03b5\u03c3\u03bc\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c3\u03c9\u03c3\u03c4\u03cc, \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b4\u03b9\u03b4\u03ac\u03be\u03b5\u03b9 \u03b4\u03cd\u03c3\u03ba\u03bf\u03bb\u03bf reasoning; \u0391\u03c5\u03c4\u03cc\u03c2 \u03bf \u03c0\u03b5\u03c1\u03b9\u03bf\u03c1\u03b9\u03c3\u03bc\u03cc\u03c2 \u03b5\u03af\u03bd\u03b1\u03b9 \u03bf\u03c5\u03c3\u03b9\u03ce\u03b4\u03b7\u03c2. \u03a4\u03bf \u03c3\u03c5\u03bc\u03c0\u03ad\u03c1\u03b1\u03c3\u03bc\u03b1 \u03b1\u03c6\u03bf\u03c1\u03ac \u03c4\u03bf\u03bd \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03bf \u03bc\u03b7\u03c7\u03b1\u03bd\u03b9\u03c3\u03bc\u03cc \u03ba\u03b1\u03b9 \u03c4\u03b9\u03c2 \u03b5\u03be\u03b5\u03c4\u03b1\u03b6\u03cc\u03bc\u03b5\u03bd\u03b5\u03c2 \u03c3\u03c5\u03bd\u03b8\u03ae\u03ba\u03b5\u03c2, \u03cc\u03c7\u03b9 \u03ba\u03ac\u03b8\u03b5 \u03bc\u03bf\u03c1\u03c6\u03ae knowledge distillation.<\/p>\n<div class=\"td-comparison\">\n<p class=\"td-comparison-title\">\u03a4\u03ad\u03c3\u03c3\u03b5\u03c1\u03b9\u03c2 \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03ad\u03c2 \u03ad\u03bd\u03bd\u03bf\u03b9\u03b5\u03c2 \u03c0\u03bf\u03c5 \u03b4\u03b5\u03bd \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03c3\u03c5\u03b3\u03c7\u03ad\u03bf\u03bd\u03c4\u03b1\u03b9<\/p>\n<div class=\"td-comparison-cards td-comparison-cards--horizontal\">\n<div class=\"td-comparison-grid td-comparison-grid--two\">\n<div class=\"td-platform-card\">\n<h3>\u03a7\u03b1\u03bc\u03b7\u03bb\u03cc\u03c4\u03b5\u03c1\u03bf SD loss<\/h3>\n<p>\u039f student \u03c0\u03bb\u03b7\u03c3\u03b9\u03ac\u03b6\u03b5\u03b9 \u03ba\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03b1 \u03c4\u03b7\u03bd token-level \u03ba\u03b1\u03c4\u03b1\u03bd\u03bf\u03bc\u03ae \u03c4\u03bf\u03c5 PI-conditioned teacher \u03c3\u03c4\u03bf objective \u03c0\u03bf\u03c5 \u03b2\u03b5\u03bb\u03c4\u03b9\u03c3\u03c4\u03bf\u03c0\u03bf\u03b9\u03b5\u03af\u03c4\u03b1\u03b9.<\/p>\n<div class=\"td-badge-row\"><span class=\"td-badge\">Proxy metric<\/span><span class=\"td-badge\">\u039c\u03af\u03bc\u03b7\u03c3\u03b7<\/span><\/div>\n<\/div>\n<div class=\"td-platform-card td-platform-card--navy\">\n<h3>\u03a5\u03c8\u03b7\u03bb\u03cc\u03c4\u03b5\u03c1\u03b7 task accuracy<\/h3>\n<p>\u03a4\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03bb\u03cd\u03bd\u03b5\u03b9 \u03c0\u03b5\u03c1\u03b9\u03c3\u03c3\u03cc\u03c4\u03b5\u03c1\u03b1 \u03c0\u03c1\u03bf\u03b2\u03bb\u03ae\u03bc\u03b1\u03c4\u03b1, \u03c0\u03b5\u03c1\u03bd\u03ac \u03c0\u03b5\u03c1\u03b9\u03c3\u03c3\u03cc\u03c4\u03b5\u03c1\u03b1 tests \u03ae \u03bf\u03bb\u03bf\u03ba\u03bb\u03b7\u03c1\u03ce\u03bd\u03b5\u03b9 \u03c3\u03c9\u03c3\u03c4\u03ac \u03c0\u03b5\u03c1\u03b9\u03c3\u03c3\u03cc\u03c4\u03b5\u03c1\u03b5\u03c2 \u03ba\u03bb\u03ae\u03c3\u03b5\u03b9\u03c2 \u03b5\u03c1\u03b3\u03b1\u03bb\u03b5\u03af\u03c9\u03bd.<\/p>\n<div class=\"td-badge-row\"><span class=\"td-badge\">Outcome<\/span><span class=\"td-badge\">\u039f\u03c1\u03b8\u03cc\u03c4\u03b7\u03c4\u03b1<\/span><\/div>\n<\/div>\n<div class=\"td-platform-card\">\n<h3>\u03a3\u03c5\u03bd\u03c4\u03bf\u03bc\u03cc\u03c4\u03b5\u03c1\u03b7 \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7<\/h3>\n<p>\u039c\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03c3\u03b7\u03bc\u03b1\u03af\u03bd\u03b5\u03b9 \u03b1\u03c0\u03bf\u03b4\u03bf\u03c4\u03b9\u03ba\u03cc\u03c4\u03b7\u03c4\u03b1, \u03b1\u03bb\u03bb\u03ac \u03bc\u03b1\u03b6\u03af \u03bc\u03b5 flat accuracy \u03ba\u03b1\u03b9 \u03b1\u03c5\u03be\u03b7\u03bc\u03ad\u03bd\u03b7 entropy \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b4\u03b5\u03af\u03c7\u03bd\u03b5\u03b9 \u03c0\u03c1\u03cc\u03c9\u03c1\u03b7 \u03b4\u03ad\u03c3\u03bc\u03b5\u03c5\u03c3\u03b7.<\/p>\n<div class=\"td-badge-row\"><span class=\"td-badge\">\u03a3\u03ae\u03bc\u03b1<\/span><span class=\"td-badge\">\u0398\u03ad\u03bb\u03b5\u03b9 context<\/span><\/div>\n<\/div>\n<div class=\"td-platform-card td-platform-card--navy\">\n<h3>\u0399\u03ba\u03b1\u03bd\u03cc\u03c4\u03b7\u03c4\u03b1 reasoning<\/h3>\n<p>\u03a7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03bc\u03b5\u03c4\u03b1\u03c6\u03bf\u03c1\u03ac \u03c3\u03b5 \u03bd\u03ad\u03b1 \u03c0\u03c1\u03bf\u03b2\u03bb\u03ae\u03bc\u03b1\u03c4\u03b1, \u03b1\u03bd\u03b8\u03b5\u03ba\u03c4\u03b9\u03ba\u03cc\u03c4\u03b7\u03c4\u03b1 \u03c3\u03b5 \u03b5\u03bd\u03b1\u03bb\u03bb\u03b1\u03ba\u03c4\u03b9\u03ba\u03ad\u03c2 \u03c3\u03c9\u03c3\u03c4\u03ad\u03c2 \u03b4\u03b9\u03b1\u03b4\u03c1\u03bf\u03bc\u03ad\u03c2 \u03ba\u03b1\u03b9 \u03b5\u03c0\u03b9\u03c4\u03c5\u03c7\u03af\u03b1 \u03c3\u03c4\u03bf \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03cc use case.<\/p>\n<div class=\"td-badge-row\"><span class=\"td-badge\">Capability<\/span><span class=\"td-badge\">Transfer<\/span><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<h2 id=\"pos-elegchthike\">\u03a0\u03ce\u03c2 \u03b5\u03bb\u03ad\u03b3\u03c7\u03b8\u03b7\u03ba\u03b5 \u03b7 \u03c5\u03c0\u03cc\u03b8\u03b5\u03c3\u03b7 \u03c3\u03b5 \u03c4\u03ad\u03c3\u03c3\u03b5\u03c1\u03b1 domains<\/h2>\n<p>\u039f\u03b9 \u03b5\u03c1\u03b5\u03c5\u03bd\u03b7\u03c4\u03ad\u03c2 \u03b5\u03c1\u03b3\u03ac\u03c3\u03c4\u03b7\u03ba\u03b1\u03bd \u03ba\u03c5\u03c1\u03af\u03c9\u03c2 \u03bc\u03b5 Qwen3-8B, \u03c4\u03cc\u03c3\u03bf \u03c3\u03b5 think \u03cc\u03c3\u03bf \u03ba\u03b1\u03b9 \u03c3\u03b5 instruct mode, \u03ba\u03b1\u03b9 \u03c0\u03c1\u03cc\u03c3\u03b8\u03b5\u03c3\u03b1\u03bd Qwen3-32B \u03b3\u03b9\u03b1 \u03ad\u03bb\u03b5\u03b3\u03c7\u03bf \u03ba\u03bb\u03af\u03bc\u03b1\u03ba\u03b1\u03c2. \u03a4\u03b1 \u03c4\u03ad\u03c3\u03c3\u03b5\u03c1\u03b1 domains \u03ae\u03c4\u03b1\u03bd general QA \u03bc\u03b5 MMLU-Pro, \u03bc\u03b1\u03b8\u03b7\u03bc\u03b1\u03c4\u03b9\u03ba\u03ac \u03bc\u03b5 DAPO-Math-17k, coding \u03bc\u03b5 CodeForces \u03ba\u03b1\u03b9 agentic tool use \u03bc\u03b5 \u03c4\u03bf BFCL. \u0393\u03b9\u03b1 QA, math \u03ba\u03b1\u03b9 coding \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03ae\u03b8\u03b7\u03ba\u03b1\u03bd 2.000 training examples, \u03b5\u03bd\u03ce \u03c3\u03c4\u03bf agentic \u03c3\u03ba\u03ad\u03bb\u03bf\u03c2 \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03ae\u03b8\u03b7\u03ba\u03b5 \u03c4\u03bf multiturn split \u03c4\u03bf\u03c5 BFCL.<\/p>\n<p>\u0397 \u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7 \u03b4\u03b5\u03bd \u03c0\u03b5\u03c1\u03b9\u03bf\u03c1\u03af\u03c3\u03c4\u03b7\u03ba\u03b5 \u03c3\u03c4\u03b1 training distributions. \u03a0\u03b5\u03c1\u03b9\u03bb\u03ac\u03bc\u03b2\u03b1\u03bd\u03b5 held-out transfer benchmarks: GPQA-D \u03ba\u03b1\u03b9 SciKnowEval \u03b3\u03b9\u03b1 \u03b3\u03bd\u03ce\u03c3\u03b7 \u03ba\u03b1\u03b9 reasoning, AIME \u03ba\u03b1\u03b9 OlympiadBench \u03b3\u03b9\u03b1 \u03bc\u03b1\u03b8\u03b7\u03bc\u03b1\u03c4\u03b9\u03ba\u03ac, MBPP+, HumanEval+, CodeElo \u03ba\u03b1\u03b9 LiveCodeBench \u03b3\u03b9\u03b1 coding, \u03ba\u03b1\u03b8\u03ce\u03c2 \u03ba\u03b1\u03b9 BFCLv4 multiturn \u03b3\u03b9\u03b1 agents. \u0388\u03c4\u03c3\u03b9 \u03ad\u03bd\u03b1 \u03c0\u03b9\u03b8\u03b1\u03bd\u03cc \u03b8\u03b5\u03c4\u03b9\u03ba\u03cc \u03b1\u03c0\u03bf\u03c4\u03ad\u03bb\u03b5\u03c3\u03bc\u03b1 \u03b4\u03b5\u03bd \u03b8\u03b1 \u03bc\u03c0\u03bf\u03c1\u03bf\u03cd\u03c3\u03b5 \u03b5\u03cd\u03ba\u03bf\u03bb\u03b1 \u03bd\u03b1 \u03b1\u03c0\u03bf\u03b4\u03bf\u03b8\u03b5\u03af \u03bc\u03cc\u03bd\u03bf \u03c3\u03b5 \u03c0\u03c1\u03bf\u03c3\u03b1\u03c1\u03bc\u03bf\u03b3\u03ae \u03c0\u03ac\u03bd\u03c9 \u03c3\u03c4\u03bf dataset \u03b5\u03ba\u03c0\u03b1\u03af\u03b4\u03b5\u03c5\u03c3\u03b7\u03c2.<\/p>\n<p>\u0397 \u03b2\u03b1\u03c3\u03b9\u03ba\u03ae \u03b5\u03ba\u03b4\u03bf\u03c7\u03ae \u03ad\u03b4\u03b9\u03bd\u03b5 \u03c3\u03c4\u03bf\u03bd teacher \u03bc\u03b9\u03b1 \u03bf\u03bb\u03cc\u03ba\u03bb\u03b7\u03c1\u03b7 \u03c3\u03c9\u03c3\u03c4\u03ae \u03bb\u03cd\u03c3\u03b7. \u0397 \u03b5\u03ba\u03c0\u03b1\u03af\u03b4\u03b5\u03c5\u03c3\u03b7 \u03b3\u03b9\u03bd\u03cc\u03c4\u03b1\u03bd \u03bc\u03b5 \u03bc\u03bf\u03bd\u03b1\u03b4\u03b9\u03ba\u03cc \u03c3\u03c4\u03cc\u03c7\u03bf \u03c4\u03bf self-distillation, \u03c7\u03c9\u03c1\u03af\u03c2 reward \u03ae verifier \u03bc\u03ad\u03c3\u03b1 \u03c3\u03c4\u03bf loss. \u039f\u03b9 \u03c3\u03c5\u03b3\u03b3\u03c1\u03b1\u03c6\u03b5\u03af\u03c2 \u03c0\u03b1\u03c1\u03b1\u03ba\u03bf\u03bb\u03bf\u03cd\u03b8\u03b7\u03c3\u03b1\u03bd task accuracy, test cases passed, agentic success, per-token loss, entropy \u03c4\u03bf\u03c5 student, \u03bc\u03ae\u03ba\u03bf\u03c2 \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7\u03c2, teacher\u2013student KL \u03ba\u03b1\u03b9 perplexity.<\/p>\n<p>\u03a0\u03c1\u03b9\u03bd \u03b5\u03c0\u03b5\u03ba\u03c4\u03b5\u03af\u03bd\u03bf\u03c5\u03bd \u03c4\u03bf \u03c0\u03b5\u03af\u03c1\u03b1\u03bc\u03b1, \u03b1\u03bd\u03b1\u03c0\u03b1\u03c1\u03ae\u03b3\u03b1\u03b3\u03b1\u03bd \u03c4\u03bf \u03b8\u03b5\u03c4\u03b9\u03ba\u03cc pattern \u03c4\u03bf\u03c5 SDPO \u03c3\u03c4\u03bf \u03b5\u03c5\u03ba\u03bf\u03bb\u03cc\u03c4\u03b5\u03c1\u03bf SciKnowEval. \u0397 \u03ba\u03af\u03bd\u03b7\u03c3\u03b7 \u03b1\u03c5\u03c4\u03ae \u03b5\u03bb\u03ad\u03b3\u03c7\u03b5\u03b9 \u03cc\u03c4\u03b9 \u03b7 \u03c5\u03bb\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b1\u03bd\u03b1\u03ba\u03c4\u03ae\u03c3\u03b5\u03b9 \u03c4\u03bf \u03c0\u03c1\u03bf\u03b7\u03b3\u03bf\u03cd\u03bc\u03b5\u03bd\u03bf \u03b1\u03c0\u03bf\u03c4\u03ad\u03bb\u03b5\u03c3\u03bc\u03b1 \u03c3\u03c4\u03bf \u03b1\u03c1\u03c7\u03b9\u03ba\u03cc \u03c4\u03bf\u03c5 \u03ba\u03b1\u03b8\u03b5\u03c3\u03c4\u03ce\u03c2, \u03b1\u03bd\u03c4\u03af \u03bd\u03b1 \u03b1\u03c0\u03bf\u03b4\u03af\u03b4\u03b5\u03b9 \u03ba\u03ac\u03b8\u03b5 \u03b1\u03c0\u03bf\u03c4\u03c5\u03c7\u03af\u03b1 \u03c3\u03b5 \u03bb\u03ac\u03b8\u03bf\u03c2 \u03ba\u03ce\u03b4\u03b9\u03ba\u03b1 \u03ae \u03b1\u03ba\u03b1\u03c4\u03ac\u03bb\u03bb\u03b7\u03bb\u03b5\u03c2 \u03c5\u03c0\u03b5\u03c1\u03c0\u03b1\u03c1\u03b1\u03bc\u03ad\u03c4\u03c1\u03bf\u03c5\u03c2.<\/p>\n<h2 id=\"training-signature\">\u03a4\u03bf training signature: \u03ba\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03bf loss, \u03cc\u03c7\u03b9 \u03ba\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03b7 \u03b9\u03ba\u03b1\u03bd\u03cc\u03c4\u03b7\u03c4\u03b1<\/h2>\n<p>\u03a3\u03c4\u03b1 \u03b4\u03c5\u03c3\u03ba\u03bf\u03bb\u03cc\u03c4\u03b5\u03c1\u03b1 domains \u03b5\u03bc\u03c6\u03b1\u03bd\u03af\u03c3\u03c4\u03b7\u03ba\u03b5 \u03ad\u03bd\u03b1 \u03c3\u03c5\u03bd\u03b5\u03c0\u03ad\u03c2 \u03c3\u03cd\u03bd\u03bf\u03bb\u03bf \u03b5\u03bd\u03b4\u03b5\u03af\u03be\u03b5\u03c9\u03bd. \u0397 per-token \u03b1\u03c0\u03cc\u03ba\u03bb\u03b9\u03c3\u03b7 \u03bc\u03b5\u03b9\u03c9\u03bd\u03cc\u03c4\u03b1\u03bd, \u03ac\u03c1\u03b1 \u03bf student \u03c0\u03bb\u03b7\u03c3\u03af\u03b1\u03b6\u03b5 \u03c4\u03bf\u03bd teacher \u03c3\u03cd\u03bc\u03c6\u03c9\u03bd\u03b1 \u03bc\u03b5 \u03c4\u03bf\u03bd \u03b2\u03b5\u03bb\u03c4\u03b9\u03c3\u03c4\u03bf\u03c0\u03bf\u03b9\u03bf\u03cd\u03bc\u03b5\u03bd\u03bf \u03c3\u03c4\u03cc\u03c7\u03bf. \u0397 validation accuracy, \u03cc\u03bc\u03c9\u03c2, \u03b4\u03b5\u03bd \u03b1\u03ba\u03bf\u03bb\u03bf\u03c5\u03b8\u03bf\u03cd\u03c3\u03b5: \u03ad\u03bc\u03b5\u03bd\u03b5 \u03b5\u03c0\u03af\u03c0\u03b5\u03b4\u03b7 \u03ae \u03c3\u03c5\u03bd\u03ae\u03b8\u03c9\u03c2 \u03c5\u03c0\u03bf\u03c7\u03c9\u03c1\u03bf\u03cd\u03c3\u03b5. \u03a0\u03b1\u03c1\u03ac\u03bb\u03bb\u03b7\u03bb\u03b1, \u03b7 entropy \u03c4\u03bf\u03c5 student \u03b1\u03c5\u03be\u03b1\u03bd\u03cc\u03c4\u03b1\u03bd \u03ba\u03b1\u03b9 \u03bf\u03b9 \u03b1\u03c0\u03b1\u03bd\u03c4\u03ae\u03c3\u03b5\u03b9\u03c2 \u03b3\u03af\u03bd\u03bf\u03bd\u03c4\u03b1\u03bd \u03bc\u03b9\u03ba\u03c1\u03cc\u03c4\u03b5\u03c1\u03b5\u03c2.<\/p>\n<p>\u039c\u03b5\u03bc\u03bf\u03bd\u03c9\u03bc\u03ad\u03bd\u03b1, \u03bc\u03b9\u03b1 \u03c3\u03c5\u03bd\u03c4\u03bf\u03bc\u03cc\u03c4\u03b5\u03c1\u03b7 \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b8\u03b5\u03c4\u03b9\u03ba\u03ae. \u039c\u03b1\u03b6\u03af \u03bc\u03b5 flat accuracy \u03ba\u03b1\u03b9 \u03b1\u03c5\u03be\u03b7\u03bc\u03ad\u03bd\u03b7 \u03b1\u03b2\u03b5\u03b2\u03b1\u03b9\u03cc\u03c4\u03b7\u03c4\u03b1, \u03cc\u03bc\u03c9\u03c2, \u03b5\u03af\u03bd\u03b1\u03b9 \u03c3\u03c5\u03bc\u03b2\u03b1\u03c4\u03ae \u03bc\u03b5 \u03c0\u03c1\u03cc\u03c9\u03c1\u03b7 \u03b4\u03ad\u03c3\u03bc\u03b5\u03c5\u03c3\u03b7 \u03b1\u03bd\u03c4\u03af \u03b3\u03b9\u03b1 \u03b1\u03c0\u03bf\u03c4\u03b5\u03bb\u03b5\u03c3\u03bc\u03b1\u03c4\u03b9\u03ba\u03cc reasoning. \u03a3\u03c4\u03bf think mode, \u03bf \u03bc\u03ad\u03c3\u03bf\u03c2 \u03cc\u03c1\u03bf\u03c2 \u03c4\u03bf\u03c5 general QA \u03bc\u03b5\u03b9\u03ce\u03b8\u03b7\u03ba\u03b5 \u03c0\u03b5\u03c1\u03af\u03c0\u03bf\u03c5 1,56 \u03bc\u03bf\u03bd\u03ac\u03b4\u03b5\u03c2 \u03ba\u03b1\u03b9 \u03c4\u03bf agentic domain 3,51 \u03bc\u03bf\u03bd\u03ac\u03b4\u03b5\u03c2, \u03bc\u03b5 \u03c0\u03c4\u03ce\u03c3\u03b7 7 \u03bc\u03bf\u03bd\u03ac\u03b4\u03c9\u03bd \u03c3\u03b5 \u03ad\u03bd\u03b1 \u03b5\u03c0\u03b9\u03bc\u03ad\u03c1\u03bf\u03c5\u03c2 BFCL benchmark.<\/p>\n<p>\u03a5\u03c0\u03ae\u03c1\u03c7\u03b1\u03bd \u03bc\u03b5\u03bc\u03bf\u03bd\u03c9\u03bc\u03ad\u03bd\u03b5\u03c2 \u03b8\u03b5\u03c4\u03b9\u03ba\u03ad\u03c2 \u03b1\u03c0\u03bf\u03ba\u03bb\u03af\u03c3\u03b5\u03b9\u03c2, \u03b3\u03b9\u03b1 \u03c0\u03b1\u03c1\u03ac\u03b4\u03b5\u03b9\u03b3\u03bc\u03b1 \u03c3\u03b5 \u03bf\u03c1\u03b9\u03c3\u03bc\u03ad\u03bd\u03b1 coding tests \u03ae \u03c3\u03c4\u03bf \u03c3\u03cd\u03bd\u03c4\u03bf\u03bc\u03bf instruct agentic setting. \u039f\u03b9 \u03c3\u03c5\u03b3\u03b3\u03c1\u03b1\u03c6\u03b5\u03af\u03c2 \u03b4\u03b5\u03bd \u03c4\u03b9\u03c2 \u03c0\u03b1\u03c1\u03bf\u03c5\u03c3\u03b9\u03ac\u03b6\u03bf\u03c5\u03bd \u03c9\u03c2 \u03c3\u03c4\u03b1\u03b8\u03b5\u03c1\u03ae \u03b5\u03b3\u03ba\u03b1\u03c4\u03ac\u03c3\u03c4\u03b1\u03c3\u03b7 \u03bd\u03ad\u03b1\u03c2 \u03b9\u03ba\u03b1\u03bd\u03cc\u03c4\u03b7\u03c4\u03b1\u03c2, \u03b5\u03c0\u03b5\u03b9\u03b4\u03ae \u03c4\u03b1 gains \u03b4\u03b5\u03bd \u03b5\u03c0\u03b1\u03bd\u03b1\u03bb\u03b1\u03bc\u03b2\u03ac\u03bd\u03bf\u03bd\u03c4\u03b1\u03bd \u03bf\u03bc\u03bf\u03b9\u03cc\u03bc\u03bf\u03c1\u03c6\u03b1 \u03b1\u03bd\u03ac benchmark \u03ba\u03b1\u03b9 reasoning mode.<\/p>\n<div class=\"td-chart td-chart--metrics\">\n<p class=\"td-chart-title\">\u03a4\u03ad\u03c3\u03c3\u03b5\u03c1\u03b9\u03c2 \u03bc\u03b5\u03c4\u03c1\u03ae\u03c3\u03b5\u03b9\u03c2 \u03c0\u03bf\u03c5 \u03b5\u03be\u03b7\u03b3\u03bf\u03cd\u03bd \u03c4\u03b7\u03bd \u03b1\u03c0\u03bf\u03c3\u03cd\u03bd\u03b4\u03b5\u03c3\u03b7<\/p>\n<p class=\"td-chart-intro\">\u039f\u03b9 \u03c4\u03b9\u03bc\u03ad\u03c2 \u03c0\u03c1\u03bf\u03ad\u03c1\u03c7\u03bf\u03bd\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc \u03c4\u03b9\u03c2 \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03b5\u03c2 \u03b1\u03bd\u03b1\u03bb\u03cd\u03c3\u03b5\u03b9\u03c2 \u03c4\u03bf\u03c5 paper \u03ba\u03b1\u03b9 \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03ba\u03b1\u03b8\u03bf\u03bb\u03b9\u03ba\u03ac benchmarks \u03b3\u03b9\u03b1 \u03cc\u03bb\u03b1 \u03c4\u03b1 LLMs \u03ae \u03ba\u03ac\u03b8\u03b5 \u03c4\u03b5\u03c7\u03bd\u03b9\u03ba\u03ae distillation.<\/p>\n<div class=\"td-metric-grid\">\n<div class=\"td-metric-card\">\n<div class=\"td-metric-value\">98,5%<\/div>\n<div class=\"td-metric-label\">\u03c4\u03bf\u03c5 unclipped loss<\/div>\n<p>\u0391\u03c0\u03bf\u03c1\u03c1\u03bf\u03c6\u03ae\u03b8\u03b7\u03ba\u03b5 \u03b1\u03c0\u03cc \u03c4\u03bf \u03ba\u03bf\u03c1\u03c5\u03c6\u03b1\u03af\u03bf 50% \u03c4\u03c9\u03bd tokens \u03c3\u03c4\u03bf MMLU-Pro.<\/p>\n<\/div>\n<div class=\"td-metric-card\">\n<div class=\"td-metric-value\">0,52<\/div>\n<div class=\"td-metric-label\">PI Bias Score<\/div>\n<p>\u0393\u03b9\u03b1 \u03c4\u03b7 \u03bb\u03cd\u03c3\u03b7 \u03c0\u03bf\u03c5 \u03b5\u03af\u03c7\u03b5 \u03b4\u03b5\u03b9 \u03bf teacher, \u03ad\u03bd\u03b1\u03bd\u03c4\u03b9 \u03ad\u03c9\u03c2 0,02 \u03b3\u03b9\u03b1 \u03ac\u03bb\u03bb\u03b7 \u03c3\u03c9\u03c3\u03c4\u03ae \u03bb\u03cd\u03c3\u03b7.<\/p>\n<\/div>\n<div class=\"td-metric-card\">\n<div class=\"td-metric-value\">55,38%<\/div>\n<div class=\"td-metric-label\">loss \u03c7\u03b1\u03bc\u03b7\u03bb\u03ae\u03c2 \u03c0\u03bb\u03b7\u03c1\u03bf\u03c6\u03bf\u03c1\u03af\u03b1\u03c2<\/div>\n<p>\u03a0\u03ae\u03b3\u03b5 \u03c3\u03b5 stopwords, uncertainty markers, punctuation \u03ba\u03b1\u03b9 whitespace \u03c3\u03b5 \u03b1\u03bd\u03c4\u03b9\u03c0\u03c1\u03bf\u03c3\u03c9\u03c0\u03b5\u03c5\u03c4\u03b9\u03ba\u03cc step.<\/p>\n<\/div>\n<div class=\"td-metric-card\">\n<div class=\"td-metric-value\">\u22484\u00d7<\/div>\n<div class=\"td-metric-label\">\u03c5\u03c8\u03b7\u03bb\u03cc\u03c4\u03b5\u03c1\u03bf KL<\/div>\n<p>\u03a3\u03c4\u03b9\u03c2 off-path \u03b8\u03ad\u03c3\u03b5\u03b9\u03c2 \u03c3\u03c9\u03c3\u03c4\u03ce\u03bd rollouts: \u03c0\u03b5\u03c1\u03af\u03c0\u03bf\u03c5 0,31 \u03ad\u03bd\u03b1\u03bd\u03c4\u03b9 0,08 on-path.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<h2 id=\"pi-bias\">PI bias: \u03bc\u03af\u03b1 \u03b4\u03b9\u03b1\u03b4\u03c1\u03bf\u03bc\u03ae \u03b1\u03bd\u03c4\u03af \u03b3\u03b9\u03b1 \u03c4\u03b7\u03bd \u03ad\u03bd\u03bd\u03bf\u03b9\u03b1 \u03c4\u03bf\u03c5 \u03c3\u03c9\u03c3\u03c4\u03bf\u03cd<\/h2>\n<p>\u039f \u03c0\u03c5\u03c1\u03ae\u03bd\u03b1\u03c2 \u03c4\u03b7\u03c2 \u03b5\u03be\u03ae\u03b3\u03b7\u03c3\u03b7\u03c2 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c4\u03bf <strong>PI bias<\/strong>. \u038c\u03c4\u03b1\u03bd \u03bf teacher \u03b2\u03bb\u03ad\u03c0\u03b5\u03b9 \u03bc\u03af\u03b1 \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03b7 reference solution, \u03b7 \u03ba\u03b1\u03c4\u03b1\u03bd\u03bf\u03bc\u03ae \u03c4\u03bf\u03c5 \u03b5\u03c0\u03b7\u03c1\u03b5\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc \u03c4\u03b7 \u03c3\u03b5\u03b9\u03c1\u03ac, \u03c4\u03b7 \u03b4\u03b9\u03b1\u03c4\u03cd\u03c0\u03c9\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03c4\u03b7 \u03bc\u03bf\u03c1\u03c6\u03ae \u03b1\u03c5\u03c4\u03ae\u03c2 \u03c4\u03b7\u03c2 \u03bb\u03cd\u03c3\u03b7\u03c2. \u03a5\u03c0\u03ac\u03c1\u03c7\u03bf\u03c5\u03bd \u03cc\u03bc\u03c9\u03c2 \u03c3\u03c5\u03c7\u03bd\u03ac \u03c0\u03bf\u03bb\u03bb\u03ad\u03c2 \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03ad\u03c2 \u03c3\u03c9\u03c3\u03c4\u03ad\u03c2 \u03b4\u03b9\u03b1\u03b4\u03c1\u03bf\u03bc\u03ad\u03c2. Teacher \u03c0\u03bf\u03c5 \u03ad\u03c7\u03b5\u03b9 \u03bc\u03ac\u03b8\u03b5\u03b9 \u03c4\u03b7\u03bd \u03bf\u03c1\u03b8\u03cc\u03c4\u03b7\u03c4\u03b1 \u03b8\u03b1 \u03ad\u03c0\u03c1\u03b5\u03c0\u03b5 \u03bd\u03b1 \u03b5\u03c5\u03bd\u03bf\u03b5\u03af \u03ba\u03b1\u03b9 \u03bc\u03b9\u03b1 \u03b4\u03b5\u03cd\u03c4\u03b5\u03c1\u03b7 \u03c3\u03c9\u03c3\u03c4\u03ae \u03bb\u03cd\u03c3\u03b7. Teacher \u03b1\u03b3\u03ba\u03c5\u03c1\u03c9\u03bc\u03ad\u03bd\u03bf\u03c2 \u03c3\u03c4\u03bf \u03c0\u03b1\u03c1\u03ac\u03b4\u03b5\u03b9\u03b3\u03bc\u03b1 \u03b8\u03b1 \u03b5\u03c5\u03bd\u03bf\u03b5\u03af \u03ba\u03c5\u03c1\u03af\u03c9\u03c2 \u03c4\u03b7 \u03bb\u03cd\u03c3\u03b7 \u03c0\u03bf\u03c5 \u03b5\u03af\u03b4\u03b5.<\/p>\n<p>\u0393\u03b9\u03b1 \u03bd\u03b1 \u03bc\u03b5\u03c4\u03c1\u03ae\u03c3\u03bf\u03c5\u03bd \u03c4\u03b7 \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03ac, \u03bf\u03b9 \u03c3\u03c5\u03b3\u03b3\u03c1\u03b1\u03c6\u03b5\u03af\u03c2 \u03b5\u03b9\u03c3\u03ac\u03b3\u03bf\u03c5\u03bd \u03c4\u03bf PI Bias Score. \u03a3\u03c5\u03b3\u03ba\u03c1\u03af\u03bd\u03bf\u03c5\u03bd \u03c0\u03cc\u03c3\u03bf \u03c0\u03b5\u03c1\u03b9\u03c3\u03c3\u03cc\u03c4\u03b5\u03c1\u03bf probability mass \u03b4\u03af\u03bd\u03b5\u03b9 \u03bf PI-conditioned teacher, \u03c3\u03b5 \u03c3\u03c7\u03ad\u03c3\u03b7 \u03bc\u03b5 \u03c4\u03bf\u03bd student, \u03c3\u03b5 \u03c4\u03ad\u03c3\u03c3\u03b5\u03c1\u03b9\u03c2 \u03c3\u03c4\u03cc\u03c7\u03bf\u03c5\u03c2: \u03c4\u03b7\u03bd in-context \u03bb\u03cd\u03c3\u03b7, \u03bc\u03b9\u03b1 \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03ae \u03c3\u03c9\u03c3\u03c4\u03ae \u03bb\u03cd\u03c3\u03b7 \u03c3\u03c4\u03bf \u03af\u03b4\u03b9\u03bf \u03c0\u03c1\u03cc\u03b2\u03bb\u03b7\u03bc\u03b1, \u03bc\u03b9\u03b1 \u03bb\u03cd\u03c3\u03b7 \u03ac\u03c3\u03c7\u03b5\u03c4\u03bf\u03c5 \u03c0\u03c1\u03bf\u03b2\u03bb\u03ae\u03bc\u03b1\u03c4\u03bf\u03c2 \u03ba\u03b1\u03b9 \u03bc\u03b9\u03b1 \u03bb\u03b1\u03bd\u03b8\u03b1\u03c3\u03bc\u03ad\u03bd\u03b7 \u03bb\u03cd\u03c3\u03b7.<\/p>\n<p>\u03a3\u03c4\u03b1 \u03c0\u03b5\u03b9\u03c1\u03ac\u03bc\u03b1\u03c4\u03b1, \u03c4\u03bf score \u03ad\u03c6\u03c4\u03b1\u03c3\u03b5 0,52 \u03b3\u03b9\u03b1 \u03c4\u03b7 \u03bb\u03cd\u03c3\u03b7 \u03c0\u03bf\u03c5 \u03b5\u03af\u03c7\u03b5 \u03b4\u03b5\u03b9 \u03bf teacher, \u03b1\u03bb\u03bb\u03ac \u03ae\u03c4\u03b1\u03bd \u03ad\u03c9\u03c2 0,02 \u03b3\u03b9\u03b1 \u03bc\u03b9\u03b1 \u03ac\u03bb\u03bb\u03b7 \u03c3\u03c9\u03c3\u03c4\u03ae \u03bb\u03cd\u03c3\u03b7, \u03c3\u03c7\u03b5\u03b4\u03cc\u03bd \u03c3\u03c4\u03bf \u03b5\u03c0\u03af\u03c0\u03b5\u03b4\u03bf \u03bc\u03b9\u03b1\u03c2 \u03ac\u03c3\u03c7\u03b5\u03c4\u03b7\u03c2 \u03bb\u03cd\u03c3\u03b7\u03c2. \u0391\u03c5\u03c4\u03cc \u03b4\u03b5\u03bd \u03b1\u03c0\u03bf\u03b4\u03b5\u03b9\u03ba\u03bd\u03cd\u03b5\u03b9 \u03cc\u03c4\u03b9 \u03bf teacher \u03b4\u03b5\u03bd \u03b3\u03bd\u03c9\u03c1\u03af\u03b6\u03b5\u03b9 \u03c4\u03b7 \u03c3\u03c9\u03c3\u03c4\u03ae \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7. \u0394\u03b5\u03af\u03c7\u03bd\u03b5\u03b9 \u03cc\u03c4\u03b9 \u03c4\u03bf \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03bf training target \u03bc\u03b5\u03c4\u03b1\u03c6\u03ad\u03c1\u03b5\u03b9 \u03ba\u03c5\u03c1\u03af\u03c9\u03c2 \u03c4\u03b7 \u03bc\u03af\u03b1 \u03c0\u03b1\u03c1\u03b1\u03c4\u03b7\u03c1\u03b7\u03bc\u03ad\u03bd\u03b7 trajectory.<\/p>\n<p>\u0393\u03b9\u03b1 \u03bf\u03bc\u03ac\u03b4\u03b5\u03c2 AI, \u03b7 \u03b4\u03b9\u03ac\u03ba\u03c1\u03b9\u03c3\u03b7 \u03b5\u03af\u03bd\u03b1\u03b9 \u03ba\u03c1\u03af\u03c3\u03b9\u03bc\u03b7. Trajectory imitation \u03ba\u03b1\u03b9 capability learning \u03bc\u03c0\u03bf\u03c1\u03bf\u03cd\u03bd \u03bd\u03b1 \u03c3\u03c5\u03bc\u03c0\u03af\u03c0\u03c4\u03bf\u03c5\u03bd \u03c3\u03b5 \u03bc\u03b9\u03ba\u03c1\u03ac \u03ba\u03bb\u03b5\u03b9\u03c3\u03c4\u03ac \u03c0\u03c1\u03bf\u03b2\u03bb\u03ae\u03bc\u03b1\u03c4\u03b1, \u03b1\u03bb\u03bb\u03ac \u03b1\u03c0\u03bf\u03ba\u03bb\u03af\u03bd\u03bf\u03c5\u03bd \u03c3\u03b5 \u03b1\u03bd\u03bf\u03b9\u03c7\u03c4\u03ad\u03c2 \u03b5\u03c1\u03b3\u03b1\u03c3\u03af\u03b5\u03c2 \u03bc\u03b5 \u03c0\u03bf\u03bb\u03bb\u03ad\u03c2 \u03bd\u03cc\u03bc\u03b9\u03bc\u03b5\u03c2 \u03c3\u03c4\u03c1\u03b1\u03c4\u03b7\u03b3\u03b9\u03ba\u03ad\u03c2. \u0397 \u03af\u03b4\u03b9\u03b1 \u03bb\u03bf\u03b3\u03b9\u03ba\u03ae \u03b5\u03be\u03b7\u03b3\u03b5\u03af \u03b3\u03b9\u03b1\u03c4\u03af \u03b7 \u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7 \u03b5\u03bd\u03cc\u03c2 production \u03c3\u03c5\u03c3\u03c4\u03ae\u03bc\u03b1\u03c4\u03bf\u03c2 \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03b1\u03c6\u03bf\u03c1\u03ac \u03bf\u03bb\u03cc\u03ba\u03bb\u03b7\u03c1\u03b7 \u03c4\u03b7\u03bd \u03b1\u03c1\u03c7\u03b9\u03c4\u03b5\u03ba\u03c4\u03bf\u03bd\u03b9\u03ba\u03ae, \u03cc\u03c0\u03c9\u03c2 \u03b1\u03bd\u03b1\u03bb\u03cd\u03b5\u03c4\u03b1\u03b9 \u03c3\u03c4\u03bf \u03c0\u03bb\u03b1\u03af\u03c3\u03b9\u03bf <a href=\"https:\/\/twodots.gr\/rail-ai-4-erotimata-prin-tin-paragogi\/\">RAIL \u03b3\u03b9\u03b1 AI \u03c0\u03c1\u03b9\u03bd \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae<\/a>.<\/p>\n<div class=\"td-article-note\">\n<p><strong>\u03a4\u03bf PI Bias Score \u03b5\u03af\u03bd\u03b1\u03b9 diagnostic, \u03cc\u03c7\u03b9 \u03b3\u03b5\u03bd\u03b9\u03ba\u03ae \u03b2\u03b1\u03b8\u03bc\u03bf\u03bb\u03bf\u03b3\u03af\u03b1 \u03c0\u03bf\u03b9\u03cc\u03c4\u03b7\u03c4\u03b1\u03c2.<\/strong> \u0388\u03bd\u03b1 \u03bc\u03b5\u03b3\u03ac\u03bb\u03bf \u03c7\u03ac\u03c3\u03bc\u03b1 \u03b1\u03bd\u03ac\u03bc\u03b5\u03c3\u03b1 \u03c3\u03c4\u03b7\u03bd in-context \u03bb\u03cd\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03c3\u03b5 \u03bc\u03b9\u03b1 \u03b5\u03bd\u03b1\u03bb\u03bb\u03b1\u03ba\u03c4\u03b9\u03ba\u03ae \u03c3\u03c9\u03c3\u03c4\u03ae \u03bb\u03cd\u03c3\u03b7 \u03b4\u03b5\u03af\u03c7\u03bd\u03b5\u03b9 \u03c0\u03b9\u03b8\u03b1\u03bd\u03ae \u03b1\u03b3\u03ba\u03cd\u03c1\u03c9\u03c3\u03b7 \u03c3\u03c4\u03b7 \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03b7 trajectory. \u039f\u03bc\u03bf\u03b9\u03cc\u03bc\u03bf\u03c1\u03c6\u03b1 \u03bc\u03b9\u03ba\u03c1\u03ac scores \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03b1\u03bd\u03c4\u03af\u03b8\u03b5\u03c4\u03b1 \u03bd\u03b1 \u03c3\u03b7\u03bc\u03b1\u03af\u03bd\u03bf\u03c5\u03bd \u03cc\u03c4\u03b9 \u03c4\u03bf PI \u03b4\u03b5\u03bd \u03ba\u03b9\u03bd\u03b5\u03af \u03b1\u03c1\u03ba\u03b5\u03c4\u03ac \u03c4\u03bf\u03bd teacher \u03c0\u03c1\u03bf\u03c2 \u03ba\u03b1\u03bd\u03ad\u03bd\u03b1\u03bd \u03c7\u03c1\u03ae\u03c3\u03b9\u03bc\u03bf \u03c3\u03c4\u03cc\u03c7\u03bf.<\/p>\n<\/div>\n<h2 id=\"loss-sosta-lathos\">\u0393\u03b9\u03b1\u03c4\u03af \u03c4\u03bf loss \u03b4\u03b5\u03bd \u03be\u03b5\u03c7\u03c9\u03c1\u03af\u03b6\u03b5\u03b9 \u03c3\u03c9\u03c3\u03c4\u03ac \u03ba\u03b1\u03b9 \u03bb\u03b1\u03bd\u03b8\u03b1\u03c3\u03bc\u03ad\u03bd\u03b1 rollouts<\/h2>\n<p>\u0391\u03bd \u03ad\u03bd\u03b1 objective \u03b5\u03ba\u03c0\u03b1\u03b9\u03b4\u03b5\u03cd\u03b5\u03b9 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ac \u03c4\u03b7 \u03bb\u03cd\u03c3\u03b7 \u03c0\u03c1\u03bf\u03b2\u03bb\u03b7\u03bc\u03ac\u03c4\u03c9\u03bd, \u03b8\u03b1 \u03c0\u03b5\u03c1\u03b9\u03bc\u03ad\u03bd\u03b1\u03bc\u03b5 \u03bd\u03b1 \u03b5\u03c0\u03b9\u03b2\u03ac\u03bb\u03bb\u03b5\u03b9 \u03bc\u03b5\u03b3\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03b7 \u03b4\u03b9\u03cc\u03c1\u03b8\u03c9\u03c3\u03b7 \u03c3\u03c4\u03b1 \u03b1\u03c0\u03bf\u03c4\u03c5\u03c7\u03b7\u03bc\u03ad\u03bd\u03b1 rollouts. \u03a3\u03c4\u03b7 \u03bc\u03b5\u03bb\u03ad\u03c4\u03b7, \u03c4\u03bf \u03bc\u03ad\u03c3\u03bf per-token loss \u03c3\u03c4\u03b1\u03b8\u03b5\u03c1\u03bf\u03c0\u03bf\u03b9\u03ae\u03b8\u03b7\u03ba\u03b5 \u03ba\u03bf\u03bd\u03c4\u03ac \u03c3\u03c4\u03bf 3,5 \u00d7 10<sup>\u22124<\/sup> \u03ba\u03b1\u03b9 \u03c4\u03bf \u03bc\u03ad\u03c3\u03bf KL \u03ba\u03bf\u03bd\u03c4\u03ac \u03c3\u03c4\u03bf 0,03 \u03c4\u03cc\u03c3\u03bf \u03b3\u03b9\u03b1 \u03c3\u03c9\u03c3\u03c4\u03ac \u03cc\u03c3\u03bf \u03ba\u03b1\u03b9 \u03b3\u03b9\u03b1 \u03bb\u03b1\u03bd\u03b8\u03b1\u03c3\u03bc\u03ad\u03bd\u03b1 rollouts. \u039f\u03b9 \u03ba\u03b1\u03bc\u03c0\u03cd\u03bb\u03b5\u03c2 \u03b5\u03c0\u03b9\u03ba\u03b1\u03bb\u03cd\u03c0\u03c4\u03bf\u03bd\u03c4\u03b1\u03bd \u03c3\u03c4\u03b7 \u03b4\u03b9\u03ac\u03c1\u03ba\u03b5\u03b9\u03b1 \u03c4\u03b7\u03c2 \u03b5\u03ba\u03c0\u03b1\u03af\u03b4\u03b5\u03c5\u03c3\u03b7\u03c2.<\/p>\n<p>\u038c\u03c0\u03bf\u03c5 \u03b5\u03bc\u03c6\u03b1\u03bd\u03af\u03c3\u03c4\u03b7\u03ba\u03b5 \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03ac, \u03ae\u03c4\u03b1\u03bd \u03c0\u03c1\u03bf\u03c2 \u03c4\u03b7\u03bd \u03b1\u03bd\u03c4\u03af\u03b8\u03b5\u03c4\u03b7 \u03ba\u03b1\u03c4\u03b5\u03cd\u03b8\u03c5\u03bd\u03c3\u03b7 \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03b5\u03c0\u03b9\u03b8\u03c5\u03bc\u03b7\u03c4\u03ae. \u03a4\u03bf \u03b1\u03c0\u03cc\u03bb\u03c5\u03c4\u03bf teacher\u2013student log-probability gap \u03c3\u03c4\u03b1\u03b8\u03b5\u03c1\u03bf\u03c0\u03bf\u03b9\u03ae\u03b8\u03b7\u03ba\u03b5 \u03c0\u03b5\u03c1\u03af\u03c0\u03bf\u03c5 \u03c3\u03c4\u03bf 0,7 \u03c3\u03c4\u03b1 \u03c3\u03c9\u03c3\u03c4\u03ac rollouts \u03ba\u03b1\u03b9 \u03c3\u03c4\u03bf 0,45 \u03c3\u03c4\u03b1 \u03bb\u03b1\u03bd\u03b8\u03b1\u03c3\u03bc\u03ad\u03bd\u03b1. \u0397 \u03bc\u03b5\u03b3\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03b7 \u03bc\u03b1\u03b8\u03b7\u03c3\u03b9\u03b1\u03ba\u03ae \u03c0\u03af\u03b5\u03c3\u03b7 \u03ad\u03c0\u03b5\u03c6\u03c4\u03b5 \u03c3\u03c5\u03c7\u03bd\u03ac \u03b5\u03ba\u03b5\u03af \u03cc\u03c0\u03bf\u03c5 \u03bf student \u03b5\u03af\u03c7\u03b5 \u03ae\u03b4\u03b7 \u03b2\u03c1\u03b5\u03b9 \u03c3\u03c9\u03c3\u03c4\u03ae \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7.<\/p>\n<p>\u0388\u03bd\u03b1 \u03c4\u03ad\u03c4\u03bf\u03b9\u03bf objective \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b2\u03b5\u03bb\u03c4\u03b9\u03c3\u03c4\u03bf\u03c0\u03bf\u03b9\u03b5\u03af\u03c4\u03b1\u03b9 \u03b5\u03c0\u03b9\u03c4\u03c5\u03c7\u03ce\u03c2 \u03ba\u03b1\u03b9 \u03c4\u03b1\u03c5\u03c4\u03cc\u03c7\u03c1\u03bf\u03bd\u03b1 \u03bd\u03b1 \u03bc\u03b7 \u03bc\u03b1\u03b8\u03b1\u03af\u03bd\u03b5\u03b9 \u03b1\u03c0\u03cc \u03c4\u03b1 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ac \u03bb\u03ac\u03b8\u03b7. \u0393\u03b9\u03b1 \u03ad\u03bd\u03b1 production AI workflow, \u03b1\u03c5\u03c4\u03ae \u03b5\u03af\u03bd\u03b1\u03b9 \u03c0\u03c1\u03bf\u03b5\u03b9\u03b4\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7 \u03ba\u03b1\u03c4\u03ac \u03c4\u03c9\u03bd proxy metrics. \u0394\u03b5\u03bd \u03b1\u03c1\u03ba\u03b5\u03af \u03b7 \u03c0\u03c4\u03ce\u03c3\u03b7 \u03c4\u03bf\u03c5 training loss. \u0391\u03c0\u03b1\u03b9\u03c4\u03b5\u03af\u03c4\u03b1\u03b9 \u03b1\u03bd\u03b5\u03be\u03ac\u03c1\u03c4\u03b7\u03c4\u03b7 \u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7 task success \u03bc\u03b5 test sets \u03c0\u03bf\u03c5 \u03b1\u03bd\u03c4\u03b1\u03bd\u03b1\u03ba\u03bb\u03bf\u03cd\u03bd \u03c4\u03bf \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03cc use case, \u03b9\u03b4\u03b1\u03bd\u03b9\u03ba\u03ac \u03ba\u03b1\u03b9 \u03c3\u03b5 transfer \u03ae out-of-distribution \u03c3\u03c5\u03bd\u03b8\u03ae\u03ba\u03b5\u03c2.<\/p>\n<div class=\"td-decision-band\">\n<p class=\"td-decision-label\">\u03a4\u03bf gate \u03c0\u03c1\u03b9\u03bd \u03b5\u03bc\u03c0\u03b9\u03c3\u03c4\u03b5\u03c5\u03c4\u03b5\u03af\u03c4\u03b5 \u03ad\u03bd\u03b1 \u03ba\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03bf training curve<\/p>\n<p><strong>\u039c\u03b7\u03bd \u03c1\u03c9\u03c4\u03ac\u03c4\u03b5 \u03bc\u03cc\u03bd\u03bf \u03b1\u03bd \u03bc\u03b5\u03b9\u03ce\u03b8\u03b7\u03ba\u03b5 \u03c4\u03bf loss\u00b7 \u03b5\u03bb\u03ad\u03b3\u03be\u03c4\u03b5 \u03b1\u03bd \u03b1\u03c5\u03be\u03ae\u03b8\u03b7\u03ba\u03b5 \u03b7 \u03b5\u03c0\u03b1\u03bb\u03b7\u03b8\u03b5\u03cd\u03c3\u03b9\u03bc\u03b7 \u03b5\u03c0\u03b9\u03c4\u03c5\u03c7\u03af\u03b1 \u03c3\u03c4\u03b1 \u03bb\u03ac\u03b8\u03b7 \u03c0\u03bf\u03c5 \u03ba\u03bf\u03c3\u03c4\u03af\u03b6\u03bf\u03c5\u03bd.<\/strong><\/p>\n<p>\u0393\u03b9\u03b1 AI assistants \u03ba\u03b1\u03b9 agents, \u03c7\u03c9\u03c1\u03af\u03c3\u03c4\u03b5 \u03c4\u03b1 metrics \u03c3\u03b5 \u03bf\u03c1\u03b8\u03cc\u03c4\u03b7\u03c4\u03b1 \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7\u03c2, \u03b5\u03c0\u03b9\u03c4\u03c5\u03c7\u03af\u03b1 tool call, \u03c4\u03ae\u03c1\u03b7\u03c3\u03b7 \u03c0\u03bf\u03bb\u03b9\u03c4\u03b9\u03ba\u03ae\u03c2, \u03b1\u03bd\u03ac\u03ba\u03b1\u03bc\u03c8\u03b7 \u03b1\u03c0\u03cc failure, transfer \u03c3\u03b5 \u03bd\u03ad\u03b1 inputs \u03ba\u03b1\u03b9 \u03b1\u03bd\u03ac\u03b3\u03ba\u03b7 \u03b1\u03bd\u03b8\u03c1\u03ce\u03c0\u03b9\u03bd\u03b7\u03c2 \u03b4\u03b9\u03cc\u03c1\u03b8\u03c9\u03c3\u03b7\u03c2. \u0397 \u03b3\u03bb\u03c9\u03c3\u03c3\u03b9\u03ba\u03ae \u03b5\u03c5\u03c7\u03ad\u03c1\u03b5\u03b9\u03b1 \u03ba\u03b1\u03b9 \u03c4\u03bf \u03bc\u03b9\u03ba\u03c1\u03cc\u03c4\u03b5\u03c1\u03bf response length \u03b4\u03b5\u03bd \u03b1\u03bd\u03c4\u03b9\u03ba\u03b1\u03b8\u03b9\u03c3\u03c4\u03bf\u03cd\u03bd \u03b1\u03c5\u03c4\u03ac \u03c4\u03b1 outcomes.<\/p>\n<\/div>\n<h2 id=\"tokens-xamilis-pliroforias\">\u038c\u03c4\u03b1\u03bd \u03c4\u03bf loss \u03c0\u03b7\u03b3\u03b1\u03af\u03bd\u03b5\u03b9 \u03c3\u03b5 tokens \u03c7\u03b1\u03bc\u03b7\u03bb\u03ae\u03c2 \u03c0\u03bb\u03b7\u03c1\u03bf\u03c6\u03bf\u03c1\u03af\u03b1\u03c2<\/h2>\n<p>\u0397 per-token \u03c0\u03c5\u03ba\u03bd\u03cc\u03c4\u03b7\u03c4\u03b1 \u03b8\u03b5\u03c9\u03c1\u03b5\u03af\u03c4\u03b1\u03b9 \u03b2\u03b1\u03c3\u03b9\u03ba\u03cc \u03c0\u03bb\u03b5\u03bf\u03bd\u03ad\u03ba\u03c4\u03b7\u03bc\u03b1 \u03c4\u03bf\u03c5 self-distillation, \u03b1\u03bb\u03bb\u03ac \u03c4\u03bf \u03c0\u03b5\u03af\u03c1\u03b1\u03bc\u03b1 \u03b4\u03b5\u03af\u03c7\u03bd\u03b5\u03b9 \u03ba\u03b1\u03b9 \u03c4\u03bf \u03ba\u03cc\u03c3\u03c4\u03bf\u03c2 \u03c4\u03b7\u03c2. \u039f\u03b9 \u03b5\u03c1\u03b5\u03c5\u03bd\u03b7\u03c4\u03ad\u03c2 \u03ba\u03b1\u03c4\u03b7\u03b3\u03bf\u03c1\u03b9\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b1\u03bd \u03c4\u03b1 tokens \u03c3\u03b5 \u03b5\u03bd\u03bd\u03ad\u03b1 \u03c4\u03cd\u03c0\u03bf\u03c5\u03c2: special tokens, whitespace, punctuation, uncertainty markers, stopwords, \u03b1\u03c1\u03b9\u03b8\u03bc\u03bf\u03cd\u03c2, \u03bc\u03b1\u03b8\u03b7\u03bc\u03b1\u03c4\u03b9\u03ba\u03ac \u03c3\u03cd\u03bc\u03b2\u03bf\u03bb\u03b1, content words \u03ba\u03b1\u03b9 \u03ac\u03bb\u03bb\u03b1.<\/p>\n<p>\u03a3\u03b5 \u03b1\u03bd\u03c4\u03b9\u03c0\u03c1\u03bf\u03c3\u03c9\u03c0\u03b5\u03c5\u03c4\u03b9\u03ba\u03cc training step, stopwords, \u03b4\u03b5\u03af\u03ba\u03c4\u03b5\u03c2 \u03b1\u03b2\u03b5\u03b2\u03b1\u03b9\u03cc\u03c4\u03b7\u03c4\u03b1\u03c2 \u03cc\u03c0\u03c9\u03c2 \u00abwait\u00bb \u03ae \u00abmaybe\u00bb, \u03c3\u03b7\u03bc\u03b5\u03af\u03b1 \u03c3\u03c4\u03af\u03be\u03b7\u03c2 \u03ba\u03b1\u03b9 \u03ba\u03b5\u03bd\u03ac \u03b1\u03c0\u03bf\u03c1\u03c1\u03cc\u03c6\u03b7\u03c3\u03b1\u03bd \u03c3\u03c5\u03bd\u03bf\u03bb\u03b9\u03ba\u03ac \u03c4\u03bf 55,38% \u03c4\u03bf\u03c5 per-token loss. \u03a4\u03b1 content words, \u03bf\u03b9 \u03b1\u03c1\u03b9\u03b8\u03bc\u03bf\u03af \u03ba\u03b1\u03b9 \u03c4\u03b1 \u03bc\u03b1\u03b8\u03b7\u03bc\u03b1\u03c4\u03b9\u03ba\u03ac \u03c3\u03cd\u03bc\u03b2\u03bf\u03bb\u03b1 \u03c0\u03bf\u03c5 \u03ba\u03b1\u03b8\u03bf\u03c1\u03af\u03b6\u03bf\u03c5\u03bd \u03c4\u03b7\u03bd \u03bf\u03c5\u03c3\u03af\u03b1 \u03c4\u03b7\u03c2 \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7\u03c2 \u03ad\u03bb\u03b1\u03b2\u03b1\u03bd \u03c3\u03c5\u03b3\u03ba\u03c1\u03b9\u03c4\u03b9\u03ba\u03ac \u03bb\u03b9\u03b3\u03cc\u03c4\u03b5\u03c1\u03b7 \u03c0\u03af\u03b5\u03c3\u03b7. \u0397 \u03c3\u03b5\u03b9\u03c1\u03ac \u03c0\u03b1\u03c1\u03ad\u03bc\u03b5\u03bd\u03b5 \u03c3\u03c4\u03b1\u03b8\u03b5\u03c1\u03ae \u03c3\u03c4\u03b7 \u03b4\u03b9\u03ac\u03c1\u03ba\u03b5\u03b9\u03b1 \u03c4\u03bf\u03c5 training.<\/p>\n<p>\u0388\u03bd\u03b1 \u03b1\u03ba\u03cc\u03bc\u03b7 \u03b5\u03cd\u03c1\u03b7\u03bc\u03b1 \u03b4\u03b5\u03af\u03c7\u03bd\u03b5\u03b9 \u03b3\u03b9\u03b1\u03c4\u03af \u03bf \u03bc\u03ad\u03c3\u03bf\u03c2 \u03cc\u03c1\u03bf\u03c2 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03c0\u03b1\u03c1\u03b1\u03c0\u03bb\u03b1\u03bd\u03ac: \u03c3\u03c4\u03bf MMLU-Pro, \u03c4\u03bf \u03ba\u03bf\u03c1\u03c5\u03c6\u03b1\u03af\u03bf 50% \u03c4\u03c9\u03bd tokens \u03b1\u03c0\u03bf\u03c1\u03c1\u03bf\u03c6\u03bf\u03cd\u03c3\u03b5 \u03c4\u03bf 98,5% \u03c4\u03bf\u03c5 unclipped loss. \u039b\u03af\u03b3\u03b1 tokens \u03c5\u03c8\u03b7\u03bb\u03ae\u03c2 \u03b1\u03c0\u03cc\u03ba\u03bb\u03b9\u03c3\u03b7\u03c2 \u03ba\u03c5\u03c1\u03b9\u03b1\u03c1\u03c7\u03bf\u03cd\u03c3\u03b1\u03bd \u03c3\u03c4\u03bf gradient. \u0397 \u03b2\u03b5\u03bb\u03c4\u03b9\u03c3\u03c4\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7 \u03bc\u03c0\u03bf\u03c1\u03bf\u03cd\u03c3\u03b5 \u03bd\u03b1 \u03ba\u03ac\u03bd\u03b5\u03b9 \u03c4\u03bf\u03bd \u03c3\u03c5\u03bd\u03bf\u03bb\u03b9\u03ba\u03cc \u03b1\u03c1\u03b9\u03b8\u03bc\u03cc \u03bd\u03b1 \u03c0\u03ad\u03c3\u03b5\u03b9 \u03c7\u03c9\u03c1\u03af\u03c2 \u03bd\u03b1 \u03b4\u03b9\u03bf\u03c7\u03b5\u03c4\u03b5\u03cd\u03b5\u03b9 \u03b1\u03bd\u03ac\u03bb\u03bf\u03b3\u03bf \u03c3\u03ae\u03bc\u03b1 \u03c3\u03c4\u03b1 tokens \u03c0\u03bf\u03c5 \u03ba\u03b1\u03b8\u03bf\u03c1\u03af\u03b6\u03bf\u03c5\u03bd \u03c4\u03b7\u03bd \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7.<\/p>\n<p>\u0391\u03c5\u03c4\u03cc \u03b4\u03b5\u03bd \u03c3\u03b7\u03bc\u03b1\u03af\u03bd\u03b5\u03b9 \u03cc\u03c4\u03b9 \u03c4\u03bf \u03cd\u03c6\u03bf\u03c2 \u03ba\u03b1\u03b9 \u03b7 \u03b3\u03bb\u03c9\u03c3\u03c3\u03b9\u03ba\u03ae \u03c3\u03c5\u03bd\u03ad\u03c0\u03b5\u03b9\u03b1 \u03b4\u03b5\u03bd \u03ad\u03c7\u03bf\u03c5\u03bd \u03b1\u03be\u03af\u03b1. \u03a3\u03b5 customer-facing assistants, \u03b7 \u03bf\u03bc\u03b1\u03bb\u03ae \u03b3\u03bb\u03ce\u03c3\u03c3\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c7\u03c1\u03ae\u03c3\u03b9\u03bc\u03b7. \u0394\u03b5\u03bd \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03cc\u03bc\u03c9\u03c2 \u03bd\u03b1 \u03b1\u03bd\u03c4\u03b9\u03ba\u03b1\u03c4\u03b1\u03c3\u03c4\u03ae\u03c3\u03b5\u03b9 \u03c4\u03b7\u03bd \u03b1\u03ba\u03c1\u03af\u03b2\u03b5\u03b9\u03b1, \u03c4\u03b7 \u03c3\u03c9\u03c3\u03c4\u03ae \u03c7\u03c1\u03ae\u03c3\u03b7 \u03b5\u03c1\u03b3\u03b1\u03bb\u03b5\u03af\u03c9\u03bd \u03ae \u03c4\u03b7\u03bd \u03c4\u03ae\u03c1\u03b7\u03c3\u03b7 \u03b5\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03b7\u03c3\u03b9\u03b1\u03ba\u03ce\u03bd \u03ba\u03b1\u03bd\u03cc\u03bd\u03c9\u03bd. \u0397 \u03b4\u03b9\u03ac\u03ba\u03c1\u03b9\u03c3\u03b7 \u03bc\u03b5\u03c4\u03b1\u03be\u03cd \u03c9\u03c1\u03b1\u03af\u03bf\u03c5 output \u03ba\u03b1\u03b9 \u03bc\u03b5\u03c4\u03c1\u03ae\u03c3\u03b9\u03bc\u03b7\u03c2 \u03b1\u03be\u03af\u03b1\u03c2 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b5\u03c0\u03af\u03c3\u03b7\u03c2 \u03ba\u03b5\u03bd\u03c4\u03c1\u03b9\u03ba\u03ae \u03c3\u03c4\u03b7\u03bd <a href=\"https:\/\/twodots.gr\/claude-vs-chatgpt-sygkrisi-dynatotiton-diaforon\/\">\u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ae \u03b1\u03bd\u03ac\u03bc\u03b5\u03c3\u03b1 \u03c3\u03b5 ChatGPT \u03ba\u03b1\u03b9 Claude \u03bc\u03b5 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03cc test brief<\/a>.<\/p>\n<h2 id=\"penalty-exploration\">\u03a0\u03ce\u03c2 \u03b7 \u03bc\u03af\u03bc\u03b7\u03c3\u03b7 \u03c4\u03b9\u03bc\u03c9\u03c1\u03b5\u03af \u03c4\u03b7\u03bd \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03b9\u03ba\u03ae \u03b5\u03be\u03b5\u03c1\u03b5\u03cd\u03bd\u03b7\u03c3\u03b7<\/h2>\n<p>\u0388\u03bd\u03b1 reasoning \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b5\u03be\u03b5\u03c4\u03ac\u03c3\u03b5\u03b9 \u03b5\u03bd\u03b4\u03b9\u03ac\u03bc\u03b5\u03c3\u03b5\u03c2 \u03ba\u03b1\u03c4\u03b5\u03c5\u03b8\u03cd\u03bd\u03c3\u03b5\u03b9\u03c2 \u03c0\u03c1\u03b9\u03bd \u03ba\u03b1\u03c4\u03b1\u03bb\u03ae\u03be\u03b5\u03b9. \u0391\u03ba\u03cc\u03bc\u03b7 \u03ba\u03b1\u03b9 \u03c3\u03b5 \u03ad\u03bd\u03b1 \u03c3\u03c9\u03c3\u03c4\u03cc rollout, \u03ba\u03ac\u03c0\u03bf\u03b9\u03b1 tokens \u03b8\u03b1 \u03b1\u03c0\u03bf\u03ba\u03bb\u03af\u03bd\u03bf\u03c5\u03bd \u03b1\u03c0\u03cc \u03c4\u03b7 reference path \u03c7\u03c9\u03c1\u03af\u03c2 \u03bd\u03b1 \u03bf\u03b4\u03b7\u03b3\u03bf\u03cd\u03bd \u03c3\u03b5 \u03bb\u03ac\u03b8\u03bf\u03c2 \u03b1\u03c0\u03bf\u03c4\u03ad\u03bb\u03b5\u03c3\u03bc\u03b1. \u039f teacher \u03c0\u03bf\u03c5 \u03ad\u03c7\u03b5\u03b9 \u03ae\u03b4\u03b7 \u03b4\u03b9\u03b1\u03b2\u03ac\u03c3\u03b5\u03b9 \u03c4\u03b7 \u03bb\u03cd\u03c3\u03b7 \u03b4\u03b5\u03bd \u03b4\u03b9\u03b1\u03b8\u03ad\u03c4\u03b5\u03b9 \u03bc\u03ad\u03c3\u03b1 \u03c3\u03b5 \u03b1\u03c5\u03c4\u03cc \u03c4\u03bf objective \u03bc\u03b7\u03c7\u03b1\u03bd\u03b9\u03c3\u03bc\u03cc \u03c0\u03bf\u03c5 \u03bd\u03b1 \u03be\u03b5\u03c7\u03c9\u03c1\u03af\u03b6\u03b5\u03b9 \u03c4\u03b7\u03bd \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03b9\u03ba\u03ae \u03c0\u03b1\u03c1\u03ac\u03ba\u03b1\u03bc\u03c8\u03b7 \u03b1\u03c0\u03cc \u03c4\u03bf \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03cc \u03c3\u03c6\u03ac\u03bb\u03bc\u03b1.<\/p>\n<p>\u039c\u03ad\u03c3\u03b1 \u03c3\u03c4\u03b1 \u03c3\u03c9\u03c3\u03c4\u03ac rollouts, \u03c4\u03bf KL \u03b3\u03b9\u03b1 off-path \u03b8\u03ad\u03c3\u03b5\u03b9\u03c2 \u03ad\u03c6\u03c4\u03b1\u03bd\u03b5 \u03c0\u03b5\u03c1\u03af\u03c0\u03bf\u03c5 0,31, \u03ad\u03bd\u03b1\u03bd\u03c4\u03b9 \u03c0\u03b5\u03c1\u03af\u03c0\u03bf\u03c5 0,08 \u03b3\u03b9\u03b1 on-path \u03b8\u03ad\u03c3\u03b5\u03b9\u03c2, \u03c3\u03c7\u03b5\u03b4\u03cc\u03bd \u03c4\u03b5\u03c4\u03c1\u03b1\u03c0\u03bb\u03ac\u03c3\u03b9\u03b1 \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03ac. \u03a3\u03c4\u03b1 \u03bb\u03b1\u03bd\u03b8\u03b1\u03c3\u03bc\u03ad\u03bd\u03b1 rollouts \u03b7 \u03b1\u03c3\u03c5\u03bc\u03bc\u03b5\u03c4\u03c1\u03af\u03b1 \u03ae\u03c4\u03b1\u03bd \u03b1\u03ba\u03cc\u03bc\u03b7 \u03bc\u03b5\u03b3\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03b7, \u03c0\u03b5\u03c1\u03af\u03c0\u03bf\u03c5 0,47 \u03ad\u03bd\u03b1\u03bd\u03c4\u03b9 0,10. \u03a4\u03bf objective \u03b1\u03c3\u03ba\u03bf\u03cd\u03c3\u03b5 \u03c4\u03b7 \u03bc\u03b5\u03b3\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03b7 \u03c0\u03af\u03b5\u03c3\u03b7 \u03b1\u03ba\u03c1\u03b9\u03b2\u03ce\u03c2 \u03c3\u03c4\u03b1 \u03c3\u03b7\u03bc\u03b5\u03af\u03b1 \u03c4\u03b7\u03c2 \u03b4\u03b9\u03b5\u03c1\u03b5\u03cd\u03bd\u03b7\u03c3\u03b7\u03c2.<\/p>\n<p>\u039f\u03b9 \u03c3\u03c5\u03b3\u03b3\u03c1\u03b1\u03c6\u03b5\u03af\u03c2 \u03c3\u03c5\u03bd\u03b4\u03ad\u03bf\u03c5\u03bd \u03b1\u03c5\u03c4\u03cc \u03c4\u03bf pattern \u03bc\u03b5 \u03c4\u03b7 \u03bc\u03b5\u03af\u03c9\u03c3\u03b7 \u03c4\u03bf\u03c5 \u03bc\u03ae\u03ba\u03bf\u03c5\u03c2 \u03c4\u03c9\u03bd \u03b1\u03c0\u03b1\u03bd\u03c4\u03ae\u03c3\u03b5\u03c9\u03bd \u03ba\u03b1\u03b9 \u03c4\u03b7\u03bd \u03c0\u03c1\u03cc\u03c9\u03c1\u03b7 \u03b4\u03ad\u03c3\u03bc\u03b5\u03c5\u03c3\u03b7. \u039f student \u03b4\u03b5\u03bd \u03b3\u03b9\u03bd\u03cc\u03c4\u03b1\u03bd \u03c0\u03b9\u03bf \u00ab\u03ba\u03bf\u03c6\u03c4\u03b5\u03c1\u03cc\u03c2\u00bb: \u03c4\u03bf \u03bc\u03ad\u03c3\u03bf gap \u03c0\u03bb\u03b7\u03c3\u03af\u03b1\u03b6\u03b5 \u03c4\u03bf \u03bc\u03b7\u03b4\u03ad\u03bd, \u03b1\u03bb\u03bb\u03ac \u03b7 \u03b4\u03b9\u03b1\u03c3\u03c0\u03bf\u03c1\u03ac \u03c4\u03bf\u03c5 \u03c0\u03b1\u03c1\u03ad\u03bc\u03b5\u03bd\u03b5 \u03ba\u03b1\u03b9 \u03b7 entropy \u03b1\u03c5\u03be\u03b1\u03bd\u03cc\u03c4\u03b1\u03bd. \u0397 \u03bc\u03ad\u03c3\u03b7 \u03c3\u03c5\u03bc\u03c6\u03c9\u03bd\u03af\u03b1 \u03bc\u03c0\u03bf\u03c1\u03bf\u03cd\u03c3\u03b5 \u03bd\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b1\u03c0\u03bf\u03c4\u03ad\u03bb\u03b5\u03c3\u03bc\u03b1 \u03b1\u03bb\u03bb\u03b7\u03bb\u03bf\u03b1\u03ba\u03cd\u03c1\u03c9\u03c3\u03b7\u03c2, \u03cc\u03c7\u03b9 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ae\u03c2 \u03c3\u03cd\u03b3\u03ba\u03bb\u03b9\u03c3\u03b7\u03c2 token \u03c0\u03c1\u03bf\u03c2 token.<\/p>\n<p>\u0397 \u03c0\u03b1\u03c1\u03b1\u03c4\u03ae\u03c1\u03b7\u03c3\u03b7 \u03ad\u03c7\u03b5\u03b9 \u03c0\u03c1\u03b1\u03ba\u03c4\u03b9\u03ba\u03ae \u03c3\u03c5\u03b3\u03b3\u03ad\u03bd\u03b5\u03b9\u03b1 \u03bc\u03b5 \u03c4\u03b7 \u03b4\u03b9\u03b1\u03c7\u03b5\u03af\u03c1\u03b9\u03c3\u03b7 \u03b1\u03b2\u03b5\u03b2\u03b1\u03b9\u03cc\u03c4\u03b7\u03c4\u03b1\u03c2 \u03c3\u03b5 \u03b5\u03c6\u03b1\u03c1\u03bc\u03bf\u03b3\u03ad\u03c2 AI. \u038c\u03c0\u03c9\u03c2 \u03b4\u03b5\u03af\u03c7\u03bd\u03b5\u03b9 \u03b7 \u03b1\u03bd\u03ac\u03bb\u03c5\u03c3\u03b7 \u03b3\u03b9\u03b1 <a href=\"https:\/\/twodots.gr\/discoformer-ai-analytics-density-score-estimation\/\">AI analytics, \u03b1\u03b2\u03b5\u03b2\u03b1\u03b9\u03cc\u03c4\u03b7\u03c4\u03b1 \u03ba\u03b1\u03b9 out-of-distribution \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03b1<\/a>, \u03ce\u03c1\u03b9\u03bc\u03b7 \u03c1\u03bf\u03ae \u03b4\u03b5\u03bd \u03ba\u03c1\u03cd\u03b2\u03b5\u03b9 \u03c4\u03b1 \u03b1\u03b4\u03cd\u03bd\u03b1\u03bc\u03b1 \u03c3\u03ae\u03bc\u03b1\u03c4\u03b1\u00b7 \u03c4\u03b1 \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03b5\u03af \u03b3\u03b9\u03b1 \u03bd\u03b1 \u03b6\u03b7\u03c4\u03ae\u03c3\u03b5\u03b9 \u03c0\u03b5\u03c1\u03b9\u03c3\u03c3\u03cc\u03c4\u03b5\u03c1\u03bf \u03ad\u03bb\u03b5\u03b3\u03c7\u03bf \u03c0\u03c1\u03b9\u03bd \u03b1\u03c0\u03cc \u03bc\u03b9\u03b1 \u03b5\u03bd\u03ad\u03c1\u03b3\u03b5\u03b9\u03b1.<\/p>\n<h2 id=\"robustness-weaker-pi\">Robustness tests \u03ba\u03b1\u03b9 \u03b1\u03c3\u03b8\u03b5\u03bd\u03ad\u03c3\u03c4\u03b5\u03c1\u03b7 privileged information<\/h2>\n<p>\u0397 \u03b1\u03c0\u03bf\u03c4\u03c5\u03c7\u03af\u03b1 \u03b8\u03b1 \u03bc\u03c0\u03bf\u03c1\u03bf\u03cd\u03c3\u03b5 \u03bd\u03b1 \u03b1\u03c0\u03bf\u03b4\u03bf\u03b8\u03b5\u03af \u03b1\u03c0\u03bb\u03ce\u03c2 \u03c3\u03b5 \u03c0\u03bf\u03bb\u03cd \u03bc\u03b5\u03b3\u03ac\u03bb\u03b5\u03c2 \u03b1\u03c0\u03b1\u03bd\u03c4\u03ae\u03c3\u03b5\u03b9\u03c2. \u0397 \u03bf\u03bc\u03ac\u03b4\u03b1 \u03c7\u03ce\u03c1\u03b9\u03c3\u03b5 \u03c4\u03bf DAPO-Math \u03c3\u03b5 short, medium \u03ba\u03b1\u03b9 long trajectories. \u039a\u03b1\u03b9 \u03bf\u03b9 \u03c4\u03c1\u03b5\u03b9\u03c2 \u03bf\u03bc\u03ac\u03b4\u03b5\u03c2 \u03ad\u03bc\u03b5\u03b9\u03bd\u03b1\u03bd \u03ba\u03ac\u03c4\u03c9 \u03b1\u03c0\u03cc \u03c4\u03bf baseline average, \u03ba\u03b1\u03c4\u03ac \u03c0\u03b5\u03c1\u03af\u03c0\u03bf\u03c5 1,1, 0,8 \u03ba\u03b1\u03b9 1,6 \u03bc\u03bf\u03bd\u03ac\u03b4\u03b5\u03c2 \u03b1\u03bd\u03c4\u03af\u03c3\u03c4\u03bf\u03b9\u03c7\u03b1. \u03a4\u03bf \u03c3\u03cd\u03bd\u03c4\u03bf\u03bc\u03bf split, \u03cc\u03c0\u03bf\u03c5 \u03c4\u03bf supervision \u03b5\u03af\u03c7\u03b5 \u03bb\u03b9\u03b3\u03cc\u03c4\u03b5\u03c1\u03b5\u03c2 \u03b8\u03ad\u03c3\u03b5\u03b9\u03c2 \u03b3\u03b9\u03b1 \u03bd\u03b1 \u03b1\u03c1\u03b1\u03b9\u03ce\u03c3\u03b5\u03b9, \u03b4\u03b5\u03bd \u03ae\u03c4\u03b1\u03bd \u03ba\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03bf \u03b1\u03c0\u03cc \u03c4\u03bf \u03bc\u03b5\u03b3\u03ac\u03bb\u03bf.<\/p>\n<p>\u0398\u03b1 \u03bc\u03c0\u03bf\u03c1\u03bf\u03cd\u03c3\u03b5 \u03b5\u03c0\u03af\u03c3\u03b7\u03c2 \u03bd\u03b1 \u03c6\u03c4\u03b1\u03af\u03b5\u03b9 \u03cc\u03c4\u03b9 \u03c4\u03b1 \u03c0\u03c1\u03bf\u03b2\u03bb\u03ae\u03bc\u03b1\u03c4\u03b1 \u03ae\u03c4\u03b1\u03bd \u03b1\u03b4\u03cd\u03bd\u03b1\u03c4\u03b1 \u03b3\u03b9\u03b1 \u03c4\u03bf base model. \u038c\u03c4\u03b1\u03bd \u03c4\u03bf MMLU-Pro \u03c7\u03c9\u03c1\u03af\u03c3\u03c4\u03b7\u03ba\u03b5 \u03c3\u03b5 easy, medium \u03ba\u03b1\u03b9 hard subsets, \u03cc\u03bb\u03b1 \u03c5\u03c0\u03bf\u03c7\u03ce\u03c1\u03b7\u03c3\u03b1\u03bd \u03c3\u03b5 \u03c3\u03c7\u03ad\u03c3\u03b7 \u03bc\u03b5 \u03c4\u03bf baseline average. \u039f\u03cd\u03c4\u03b5 \u03b7 \u03b1\u03cd\u03be\u03b7\u03c3\u03b7 \u03c4\u03bf\u03c5 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf\u03c5 \u03c3\u03b5 Qwen3-32B \u03ac\u03bb\u03bb\u03b1\u03be\u03b5 \u03c4\u03b7\u03bd \u03c5\u03c0\u03bf\u03b3\u03c1\u03b1\u03c6\u03ae: \u03bf\u03b9 \u03bc\u03ad\u03c3\u03bf\u03b9 \u03cc\u03c1\u03bf\u03b9 \u03bc\u03b5\u03b9\u03ce\u03b8\u03b7\u03ba\u03b1\u03bd \u03ba\u03b1\u03c4\u03ac 0,6 \u03bc\u03bf\u03bd\u03ac\u03b4\u03b5\u03c2 \u03c3\u03c4\u03bf think \u03ba\u03b1\u03b9 1,4 \u03c3\u03c4\u03bf instruct.<\/p>\n<p>\u039c\u03b9\u03b1 \u03c6\u03c5\u03c3\u03b9\u03ba\u03ae \u03b9\u03b4\u03ad\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03bd\u03b1 \u03b1\u03bd\u03c4\u03b9\u03ba\u03b1\u03c4\u03b1\u03c3\u03c4\u03b1\u03b8\u03b5\u03af \u03b7 \u03c0\u03bb\u03ae\u03c1\u03b7\u03c2 \u03bb\u03cd\u03c3\u03b7 \u03bc\u03b5 \u03c0\u03b9\u03bf \u03b3\u03b5\u03bd\u03b9\u03ba\u03cc PI, \u03ce\u03c3\u03c4\u03b5 \u03bf teacher \u03bd\u03b1 \u03bc\u03b7\u03bd \u03b1\u03b3\u03ba\u03b9\u03c3\u03c4\u03c1\u03ce\u03bd\u03b5\u03c4\u03b1\u03b9 \u03c3\u03b5 \u03bc\u03af\u03b1 trajectory. \u03a3\u03c4\u03bf DAPO-Math \u03b4\u03bf\u03ba\u03b9\u03bc\u03ac\u03c3\u03c4\u03b7\u03ba\u03b1\u03bd \u03c3\u03cd\u03bd\u03c4\u03bf\u03bc\u03b1 hints \u03ba\u03b1\u03b9 structured skill guides \u03c0\u03b5\u03c1\u03af\u03c0\u03bf\u03c5 500 tokens. \u03a4\u03bf PI bias \u03bc\u03b5\u03b9\u03ce\u03b8\u03b7\u03ba\u03b5, \u03b1\u03bb\u03bb\u03ac \u03bc\u03b1\u03b6\u03af \u03c4\u03bf\u03c5 \u03b5\u03be\u03b1\u03c3\u03b8\u03ad\u03bd\u03b7\u03c3\u03b5 \u03ba\u03b1\u03b9 \u03c4\u03bf \u03c3\u03c5\u03bd\u03bf\u03bb\u03b9\u03ba\u03cc training signal.<\/p>\n<p>\u039c\u03b5 baseline average 63,4, \u03c4\u03b1 hints \u03ad\u03c7\u03b1\u03c3\u03b1\u03bd \u03c0\u03b5\u03c1\u03af\u03c0\u03bf\u03c5 5,1 \u03bc\u03bf\u03bd\u03ac\u03b4\u03b5\u03c2 \u03ba\u03b1\u03b9 \u03c4\u03b1 skills \u03c0\u03b5\u03c1\u03af\u03c0\u03bf\u03c5 3,5, \u03b5\u03bd\u03ce \u03b7 \u03c0\u03bb\u03ae\u03c1\u03b7\u03c2 \u03bb\u03cd\u03c3\u03b7 \u03ad\u03bc\u03b5\u03b9\u03bd\u03b5 \u03bc\u03ad\u03c3\u03b1 \u03c3\u03b5 \u03bc\u03b9\u03c3\u03ae \u03bc\u03bf\u03bd\u03ac\u03b4\u03b1 \u03b1\u03c0\u03cc \u03c4\u03bf baseline. \u039f\u03b9 \u03b4\u03cd\u03bf \u03ac\u03ba\u03c1\u03b5\u03c2 \u03b1\u03c0\u03ad\u03c4\u03c5\u03c7\u03b1\u03bd \u03b3\u03b9\u03b1 \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03bf\u03cd\u03c2 \u03bb\u03cc\u03b3\u03bf\u03c5\u03c2: \u03b7 \u03c0\u03bb\u03ae\u03c1\u03b7\u03c2 \u03bb\u03cd\u03c3\u03b7 \u03ae\u03c4\u03b1\u03bd \u03c5\u03c0\u03b5\u03c1\u03b2\u03bf\u03bb\u03b9\u03ba\u03ac \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03b7 \u03ba\u03b1\u03b9 \u03b7 \u03b1\u03c3\u03b8\u03b5\u03bd\u03ad\u03c3\u03c4\u03b5\u03c1\u03b7 \u03c0\u03bb\u03b7\u03c1\u03bf\u03c6\u03bf\u03c1\u03af\u03b1 \u03b4\u03b5\u03bd \u03ba\u03b9\u03bd\u03bf\u03cd\u03c3\u03b5 \u03b1\u03c1\u03ba\u03b5\u03c4\u03ac \u03c4\u03b7\u03bd \u03ba\u03b1\u03c4\u03b1\u03bd\u03bf\u03bc\u03ae \u03c4\u03bf\u03c5 teacher \u03c0\u03c1\u03bf\u03c2 \u03bf\u03c0\u03bf\u03b9\u03bf\u03bd\u03b4\u03ae\u03c0\u03bf\u03c4\u03b5 \u03c7\u03c1\u03ae\u03c3\u03b9\u03bc\u03bf \u03c3\u03c4\u03cc\u03c7\u03bf.<\/p>\n<p>\u039f\u03b9 \u03ad\u03bb\u03b5\u03b3\u03c7\u03bf\u03b9 \u03ba\u03ac\u03bb\u03c5\u03c8\u03b1\u03bd response length, task difficulty, model scale, reasoning mode \u03ba\u03b1\u03b9 \u03bc\u03bf\u03c1\u03c6\u03ae PI. \u0391\u03c5\u03c4\u03cc \u03b5\u03bd\u03b9\u03c3\u03c7\u03cd\u03b5\u03b9 \u03c4\u03b7\u03bd \u03b5\u03c1\u03bc\u03b7\u03bd\u03b5\u03af\u03b1 \u03cc\u03c4\u03b9 \u03c4\u03bf \u03c0\u03c1\u03cc\u03b2\u03bb\u03b7\u03bc\u03b1 \u03b2\u03c1\u03af\u03c3\u03ba\u03b5\u03c4\u03b1\u03b9 \u03c3\u03c4\u03bf target. \u0394\u03b5\u03bd \u03b1\u03c0\u03bf\u03c4\u03b5\u03bb\u03b5\u03af \u03b1\u03c0\u03cc\u03b4\u03b5\u03b9\u03be\u03b7 \u03b3\u03b9\u03b1 \u03ba\u03ac\u03b8\u03b5 \u03b1\u03c1\u03c7\u03b9\u03c4\u03b5\u03ba\u03c4\u03bf\u03bd\u03b9\u03ba\u03ae \u03ae \u03ba\u03ac\u03b8\u03b5 \u03c4\u03b5\u03c7\u03bd\u03b9\u03ba\u03ae distillation, \u03cc\u03c0\u03c9\u03c2 \u03b1\u03bd\u03b1\u03b3\u03bd\u03c9\u03c1\u03af\u03b6\u03bf\u03c5\u03bd \u03bf\u03b9 \u03af\u03b4\u03b9\u03bf\u03b9 \u03bf\u03b9 \u03b5\u03c1\u03b5\u03c5\u03bd\u03b7\u03c4\u03ad\u03c2.<\/p>\n<h2 id=\"ti-simainei-ai-products\">\u03a4\u03b9 \u03c3\u03b7\u03bc\u03b1\u03af\u03bd\u03b5\u03b9 \u03b3\u03b9\u03b1 AI \u03c0\u03c1\u03bf\u03ca\u03cc\u03bd\u03c4\u03b1, agents \u03ba\u03b1\u03b9 \u03b5\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03ae\u03c3\u03b5\u03b9\u03c2<\/h2>\n<p>\u0397 \u03ac\u03bc\u03b5\u03c3\u03b7 \u03c0\u03c1\u03b1\u03ba\u03c4\u03b9\u03ba\u03ae \u03bf\u03b4\u03b7\u03b3\u03af\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03bd\u03b1 \u03bc\u03b7\u03bd \u03b5\u03c1\u03bc\u03b7\u03bd\u03b5\u03cd\u03b5\u03c4\u03b1\u03b9 \u03b7 \u03c0\u03c4\u03ce\u03c3\u03b7 \u03c4\u03bf\u03c5 SD loss \u03c9\u03c2 \u03b1\u03c0\u03cc\u03b4\u03b5\u03b9\u03be\u03b7 learning. \u039f\u03b9 \u03bf\u03bc\u03ac\u03b4\u03b5\u03c2 \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03bf\u03bd\u03c4\u03b1\u03b9 validation accuracy \u03ba\u03b1\u03b9 task-level metrics \u03c0\u03bf\u03c5 \u03bc\u03b5\u03c4\u03c1\u03bf\u03cd\u03bd \u03b1\u03ba\u03c1\u03b9\u03b2\u03ce\u03c2 \u03c4\u03bf \u03b1\u03c0\u03bf\u03c4\u03ad\u03bb\u03b5\u03c3\u03bc\u03b1 \u03c0\u03bf\u03c5 \u03c4\u03bf\u03c5\u03c2 \u03b5\u03bd\u03b4\u03b9\u03b1\u03c6\u03ad\u03c1\u03b5\u03b9: \u03c3\u03c9\u03c3\u03c4\u03ae \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7, \u03b5\u03c0\u03b9\u03c4\u03c5\u03c7\u03ae\u03c2 \u03ba\u03bb\u03ae\u03c3\u03b7 \u03b5\u03c1\u03b3\u03b1\u03bb\u03b5\u03af\u03bf\u03c5, \u03c4\u03ae\u03c1\u03b7\u03c3\u03b7 \u03c0\u03bf\u03bb\u03b9\u03c4\u03b9\u03ba\u03ae\u03c2, \u03bf\u03bb\u03bf\u03ba\u03bb\u03ae\u03c1\u03c9\u03c3\u03b7 workflow \u03ae \u03ac\u03bb\u03bb\u03bf \u03b5\u03c0\u03b1\u03bb\u03b7\u03b8\u03b5\u03cd\u03c3\u03b9\u03bc\u03bf outcome.<\/p>\n<p>\u03a4\u03bf PI Bias Score \u03c0\u03c1\u03bf\u03c4\u03b5\u03af\u03bd\u03b5\u03c4\u03b1\u03b9 \u03c9\u03c2 \u03c3\u03c7\u03b5\u03c4\u03b9\u03ba\u03ac \u03c6\u03b8\u03b7\u03bd\u03cc diagnostic \u03c0\u03c1\u03b9\u03bd \u03b1\u03c0\u03cc \u03b1\u03ba\u03c1\u03b9\u03b2\u03cc training. \u039c\u03b5 forward passes \u03c3\u03b5 prefixes \u03ba\u03b1\u03b9 \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03bf\u03cd\u03c2 targets, \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b4\u03b5\u03af\u03be\u03b5\u03b9 \u03b1\u03bd \u03bf teacher \u03b5\u03c5\u03bd\u03bf\u03b5\u03af \u03ba\u03c5\u03c1\u03af\u03c9\u03c2 \u03c4\u03b7 \u03bb\u03cd\u03c3\u03b7 \u03c0\u03bf\u03c5 \u03b5\u03af\u03b4\u03b5. \u0397 \u03bc\u03ad\u03c4\u03c1\u03b7\u03c3\u03b7 \u03b4\u03b5\u03bd \u03b1\u03bd\u03c4\u03b9\u03ba\u03b1\u03b8\u03b9\u03c3\u03c4\u03ac \u03c4\u03b7\u03bd task evaluation\u00b7 \u03b2\u03bf\u03b7\u03b8\u03ac \u03bd\u03b1 \u03b5\u03bd\u03c4\u03bf\u03c0\u03b9\u03c3\u03c4\u03b5\u03af \u03ad\u03b3\u03ba\u03b1\u03b9\u03c1\u03b1 \u03b1\u03bd \u03c4\u03bf supervision \u03bc\u03b5\u03c4\u03b1\u03c6\u03ad\u03c1\u03b5\u03b9 trajectory \u03b1\u03bd\u03c4\u03af \u03b3\u03b9\u03b1 \u03bf\u03c1\u03b8\u03cc\u03c4\u03b7\u03c4\u03b1.<\/p>\n<p>\u0393\u03b9\u03b1 marketers \u03ae e-commerce owners \u03c0\u03bf\u03c5 \u03b1\u03b3\u03bf\u03c1\u03ac\u03b6\u03bf\u03c5\u03bd AI \u03b4\u03c5\u03bd\u03b1\u03c4\u03cc\u03c4\u03b7\u03c4\u03b5\u03c2 \u03b1\u03bd\u03c4\u03af \u03bd\u03b1 \u03b5\u03ba\u03c0\u03b1\u03b9\u03b4\u03b5\u03cd\u03bf\u03c5\u03bd \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03b1, \u03b7 \u03b5\u03c6\u03b1\u03c1\u03bc\u03bf\u03b3\u03ae \u03b5\u03af\u03bd\u03b1\u03b9 \u03b1\u03be\u03b9\u03bf\u03bb\u03bf\u03b3\u03b9\u03ba\u03ae. Demo \u03bc\u03b5 \u03bf\u03bc\u03b1\u03bb\u03ad\u03c2, \u03c3\u03cd\u03bd\u03c4\u03bf\u03bc\u03b5\u03c2 \u03ba\u03b1\u03b9 \u00ab\u03c3\u03af\u03b3\u03bf\u03c5\u03c1\u03b5\u03c2\u00bb \u03b1\u03c0\u03b1\u03bd\u03c4\u03ae\u03c3\u03b5\u03b9\u03c2 \u03b4\u03b5\u03bd \u03b1\u03c1\u03ba\u03b5\u03af. \u03a7\u03c1\u03b5\u03b9\u03ac\u03b6\u03bf\u03bd\u03c4\u03b1\u03b9 \u03c3\u03b5\u03bd\u03ac\u03c1\u03b9\u03b1 \u03c0\u03bf\u03c5 \u03b5\u03c0\u03b9\u03c4\u03c1\u03ad\u03c0\u03bf\u03c5\u03bd \u03c0\u03b5\u03c1\u03b9\u03c3\u03c3\u03cc\u03c4\u03b5\u03c1\u03b5\u03c2 \u03b1\u03c0\u03cc \u03bc\u03af\u03b1 \u03c3\u03c9\u03c3\u03c4\u03ad\u03c2 \u03b4\u03b9\u03b1\u03b4\u03c1\u03bf\u03bc\u03ad\u03c2, \u03b1\u03c0\u03bf\u03c4\u03c5\u03c7\u03b7\u03bc\u03ad\u03bd\u03b5\u03c2 \u03ba\u03bb\u03ae\u03c3\u03b5\u03b9\u03c2, \u03bc\u03b5\u03c4\u03b1\u03b2\u03bf\u03bb\u03ad\u03c2 context \u03ba\u03b1\u03b9 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03bf\u03cd\u03c2 business constraints.<\/p>\n<p>\u0397 \u03b5\u03c5\u03c7\u03ad\u03c1\u03b5\u03b9\u03b1 \u03c3\u03c4\u03b7 \u03b4\u03b9\u03b1\u03c4\u03cd\u03c0\u03c9\u03c3\u03b7 \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03b4\u03b9\u03b1\u03c7\u03c9\u03c1\u03af\u03b6\u03b5\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03bf\u03c1\u03b8\u03cc\u03c4\u03b7\u03c4\u03b1 \u03c4\u03b7\u03c2 \u03b1\u03c0\u03cc\u03c6\u03b1\u03c3\u03b7\u03c2. \u03a4\u03bf \u03af\u03b4\u03b9\u03bf \u03b9\u03c3\u03c7\u03cd\u03b5\u03b9 \u03b3\u03b9\u03b1 \u03c4\u03b7\u03bd \u03b5\u03c5\u03b8\u03cd\u03bd\u03b7 \u03cc\u03c4\u03b1\u03bd \u03bc\u03b9\u03b1 \u03b1\u03c5\u03c4\u03bf\u03bc\u03b1\u03c4\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7 \u03b1\u03c0\u03bf\u03c4\u03c5\u03b3\u03c7\u03ac\u03bd\u03b5\u03b9: \u03ad\u03bd\u03b1 \u03c4\u03b5\u03bb\u03b9\u03ba\u03cc \u03bb\u03ac\u03b8\u03bf\u03c2 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03c0\u03c1\u03bf\u03ad\u03c1\u03c7\u03b5\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf, retrieval, \u03b5\u03c1\u03b3\u03b1\u03bb\u03b5\u03af\u03bf, \u03b4\u03b9\u03ba\u03b1\u03b9\u03ce\u03bc\u03b1\u03c4\u03b1 \u03ae \u03b5\u03bb\u03bb\u03b9\u03c0\u03ad\u03c2 fallback, \u03cc\u03c0\u03c9\u03c2 \u03b5\u03be\u03b7\u03b3\u03b5\u03af \u03b7 \u03b1\u03bd\u03ac\u03bb\u03c5\u03c3\u03b7 \u03b3\u03b9\u03b1 <a href=\"https:\/\/twodots.gr\/ai-agents-poios-ftaiei-otan-aftomatopoiisi-apotygchanei\/\">\u03c4\u03b7\u03bd \u03b1\u03c0\u03cc\u03b4\u03bf\u03c3\u03b7 \u03b5\u03c5\u03b8\u03cd\u03bd\u03b7\u03c2 \u03c3\u03b5 AI agents<\/a>.<\/p>\n<p>\u0393\u03b9\u03b1 software teams, \u03b7 \u03ad\u03c1\u03b5\u03c5\u03bd\u03b1 \u03c5\u03c0\u03b5\u03bd\u03b8\u03c5\u03bc\u03af\u03b6\u03b5\u03b9 \u03cc\u03c4\u03b9 \u03b7 \u03c4\u03b1\u03c7\u03cd\u03c4\u03b5\u03c1\u03b7 \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae \u03ba\u03ce\u03b4\u03b9\u03ba\u03b1 \u03ae \u03b7 \u03c0\u03c4\u03ce\u03c3\u03b7 \u03b5\u03bd\u03cc\u03c2 \u03b5\u03c3\u03c9\u03c4\u03b5\u03c1\u03b9\u03ba\u03bf\u03cd metric \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03b1\u03c0\u03cc \u03bc\u03cc\u03bd\u03b7 \u03c4\u03b7\u03c2 ROI. Tests, review, integration behavior \u03ba\u03b1\u03b9 failure recovery \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03bc\u03b5\u03c4\u03c1\u03ce\u03bd\u03c4\u03b1\u03b9 \u03c3\u03c4\u03bf \u03c0\u03b5\u03c1\u03b9\u03b2\u03ac\u03bb\u03bb\u03bf\u03bd \u03cc\u03c0\u03bf\u03c5 \u03b8\u03b1 \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03ae\u03c3\u03b5\u03b9 \u03c4\u03bf \u03c3\u03cd\u03c3\u03c4\u03b7\u03bc\u03b1. \u0391\u03c5\u03c4\u03ae \u03b7 \u03bc\u03b5\u03c4\u03ac\u03b2\u03b1\u03c3\u03b7 \u03b1\u03c0\u03cc prototype \u03c3\u03b5 \u03c5\u03c0\u03bf\u03c3\u03c4\u03b7\u03c1\u03b9\u03b6\u03cc\u03bc\u03b5\u03bd\u03b7 \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03af\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03ba\u03b5\u03bd\u03c4\u03c1\u03b9\u03ba\u03ae \u03ba\u03b1\u03b9 \u03c3\u03c4\u03b7 \u03c3\u03c5\u03b6\u03ae\u03c4\u03b7\u03c3\u03b7 \u03b3\u03b9\u03b1 <a href=\"https:\/\/twodots.gr\/vibe-coding-ai-agents-353000-developers\/\">vibe coding \u03ba\u03b1\u03b9 AI agents \u03c3\u03c4\u03b7\u03bd \u03b1\u03bd\u03ac\u03c0\u03c4\u03c5\u03be\u03b7 \u03bb\u03bf\u03b3\u03b9\u03c3\u03bc\u03b9\u03ba\u03bf\u03cd<\/a>.<\/p>\n<div class=\"td-step-list\">\n<p class=\"td-step-list-title\">\u0388\u03be\u03b9 \u03ad\u03bb\u03b5\u03b3\u03c7\u03bf\u03b9 \u03c0\u03c1\u03b9\u03bd \u03b5\u03bc\u03c0\u03b9\u03c3\u03c4\u03b5\u03c5\u03c4\u03b5\u03af\u03c4\u03b5 self-distillation \u03ae \u03ac\u03bb\u03bb\u03bf AI training proxy<\/p>\n<ol>\n<li><span class=\"td-step-kicker\">Step 1<\/span><strong>\u039f\u03c1\u03af\u03c3\u03c4\u03b5 \u03c4\u03bf \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03cc task outcome<\/strong>\n<p>\u039a\u03b1\u03c4\u03b1\u03b3\u03c1\u03ac\u03c8\u03c4\u03b5 \u03c4\u03b9 \u03c3\u03b7\u03bc\u03b1\u03af\u03bd\u03b5\u03b9 \u03c3\u03c9\u03c3\u03c4\u03ae \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7, \u03b5\u03c0\u03b9\u03c4\u03c5\u03c7\u03ae\u03c2 \u03b5\u03bd\u03ad\u03c1\u03b3\u03b5\u03b9\u03b1 \u03ae \u03b1\u03c3\u03c6\u03b1\u03bb\u03ae\u03c2 \u03ac\u03c1\u03bd\u03b7\u03c3\u03b7 \u03c3\u03c4\u03bf \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03bf workflow. \u03a4\u03bf outcome \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b5\u03bb\u03ad\u03b3\u03be\u03b9\u03bc\u03bf \u03b1\u03bd\u03b5\u03be\u03ac\u03c1\u03c4\u03b7\u03c4\u03b1 \u03b1\u03c0\u03cc \u03c4\u03bf training loss.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">Step 2<\/span><strong>\u03a7\u03c9\u03c1\u03af\u03c3\u03c4\u03b5 in-domain \u03ba\u03b1\u03b9 transfer \u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7<\/strong>\n<p>\u039c\u03b5\u03c4\u03c1\u03ae\u03c3\u03c4\u03b5 \u03c4\u03bf dataset \u03b5\u03ba\u03c0\u03b1\u03af\u03b4\u03b5\u03c5\u03c3\u03b7\u03c2, \u03b1\u03bb\u03bb\u03ac \u03ba\u03c1\u03b1\u03c4\u03ae\u03c3\u03c4\u03b5 \u03ba\u03b1\u03b9 \u03bd\u03ad\u03b1 \u03c0\u03c1\u03bf\u03b2\u03bb\u03ae\u03bc\u03b1\u03c4\u03b1, \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03ad\u03c2 \u03b4\u03b9\u03b1\u03c4\u03c5\u03c0\u03ce\u03c3\u03b5\u03b9\u03c2, \u03b5\u03bd\u03b1\u03bb\u03bb\u03b1\u03ba\u03c4\u03b9\u03ba\u03ad\u03c2 \u03c3\u03c9\u03c3\u03c4\u03ad\u03c2 \u03b4\u03b9\u03b1\u03b4\u03c1\u03bf\u03bc\u03ad\u03c2 \u03ba\u03b1\u03b9 \u03bc\u03b5\u03c4\u03b1\u03b2\u03bf\u03bb\u03ad\u03c2 context.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">Step 3<\/span><strong>\u03a3\u03c5\u03b3\u03ba\u03c1\u03af\u03bd\u03b5\u03c4\u03b5 \u03c3\u03c9\u03c3\u03c4\u03ac \u03ba\u03b1\u03b9 \u03bb\u03b1\u03bd\u03b8\u03b1\u03c3\u03bc\u03ad\u03bd\u03b1 rollouts<\/strong>\n<p>\u0395\u03bb\u03ad\u03b3\u03be\u03c4\u03b5 \u03b1\u03bd \u03c4\u03bf objective \u03b1\u03c3\u03ba\u03b5\u03af \u03c0\u03c1\u03ac\u03b3\u03bc\u03b1\u03c4\u03b9 \u03bc\u03b5\u03b3\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03b7 \u03c0\u03af\u03b5\u03c3\u03b7 \u03c3\u03c4\u03b1 failures. \u03a0\u03b1\u03c1\u03cc\u03bc\u03bf\u03b9\u03bf loss \u03ae KL \u03c3\u03c4\u03b9\u03c2 \u03b4\u03cd\u03bf \u03bf\u03bc\u03ac\u03b4\u03b5\u03c2 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c0\u03c1\u03bf\u03b5\u03b9\u03b4\u03bf\u03c0\u03bf\u03b9\u03b7\u03c4\u03b9\u03ba\u03cc \u03c3\u03ae\u03bc\u03b1.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">Step 4<\/span><strong>\u0391\u03bd\u03b1\u03bb\u03cd\u03c3\u03c4\u03b5 \u03c0\u03bf\u03cd \u03ba\u03b1\u03c4\u03b1\u03bd\u03ad\u03bc\u03b5\u03c4\u03b1\u03b9 \u03c4\u03bf token-level loss<\/strong>\n<p>\u039e\u03b5\u03c7\u03c9\u03c1\u03af\u03c3\u03c4\u03b5 content words, \u03b1\u03c1\u03b9\u03b8\u03bc\u03bf\u03cd\u03c2 \u03ba\u03b1\u03b9 tool arguments \u03b1\u03c0\u03cc punctuation, stopwords \u03ba\u03b1\u03b9 uncertainty markers, \u03ce\u03c3\u03c4\u03b5 \u03bd\u03b1 \u03c6\u03b1\u03bd\u03b5\u03af \u03c4\u03b9 \u03bc\u03b1\u03b8\u03b1\u03af\u03bd\u03b5\u03b9 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ac \u03c4\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">Step 5<\/span><strong>\u0394\u03bf\u03ba\u03b9\u03bc\u03ac\u03c3\u03c4\u03b5 \u03c0\u03b5\u03c1\u03b9\u03c3\u03c3\u03cc\u03c4\u03b5\u03c1\u03b5\u03c2 \u03b1\u03c0\u03cc \u03bc\u03af\u03b1 \u03c3\u03c9\u03c3\u03c4\u03ad\u03c2 \u03bb\u03cd\u03c3\u03b5\u03b9\u03c2<\/strong>\n<p>\u0395\u03bb\u03ad\u03b3\u03be\u03c4\u03b5 \u03b1\u03bd \u03bf teacher \u03b5\u03c5\u03bd\u03bf\u03b5\u03af \u03b5\u03bd\u03b1\u03bb\u03bb\u03b1\u03ba\u03c4\u03b9\u03ba\u03ad\u03c2 \u03bf\u03c1\u03b8\u03ad\u03c2 trajectories \u03ae \u03bc\u03cc\u03bd\u03bf \u03c4\u03b7 reference solution \u03c0\u03bf\u03c5 \u03b5\u03af\u03b4\u03b5 \u03c9\u03c2 privileged information.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">Step 6<\/span><strong>\u03a3\u03c5\u03bd\u03b4\u03ad\u03c3\u03c4\u03b5 \u03c4\u03bf release \u03bc\u03b5 production monitoring<\/strong>\n<p>\u03a0\u03b1\u03c1\u03b1\u03ba\u03bf\u03bb\u03bf\u03c5\u03b8\u03ae\u03c3\u03c4\u03b5 task success, tool errors, policy violations, human corrections \u03ba\u03b1\u03b9 rollback signals \u03bc\u03b5\u03c4\u03ac \u03c4\u03b7\u03bd \u03b5\u03bd\u03b5\u03c1\u03b3\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7. \u0397 offline \u03b2\u03b5\u03bb\u03c4\u03af\u03c9\u03c3\u03b7 \u03b4\u03b5\u03bd \u03ba\u03bb\u03b5\u03af\u03bd\u03b5\u03b9 \u03c4\u03bf\u03bd \u03ba\u03cd\u03ba\u03bb\u03bf \u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7\u03c2.<\/p>\n<\/li>\n<\/ol>\n<\/div>\n<p>\u0397 \u03c0\u03c1\u03b1\u03ba\u03c4\u03b9\u03ba\u03ae \u03c3\u03c7\u03b5\u03b4\u03af\u03b1\u03c3\u03b7 \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03ba\u03b1\u03b9 ownership. \u0397 product \u03bf\u03bc\u03ac\u03b4\u03b1 \u03bf\u03c1\u03af\u03b6\u03b5\u03b9 \u03c4\u03bf outcome, \u03b7 engineering \u03bf\u03bc\u03ac\u03b4\u03b1 \u03ba\u03b1\u03c4\u03b1\u03c3\u03ba\u03b5\u03c5\u03ac\u03b6\u03b5\u03b9 \u03c4\u03bf evaluation harness, \u03bf domain expert \u03b5\u03c0\u03b9\u03bc\u03b5\u03bb\u03b5\u03af\u03c4\u03b1\u03b9 \u03c4\u03b9\u03c2 \u03b1\u03c0\u03bf\u03b4\u03b5\u03ba\u03c4\u03ad\u03c2 \u03bb\u03cd\u03c3\u03b5\u03b9\u03c2 \u03ba\u03b1\u03b9 \u03bf \u03c5\u03c0\u03b5\u03cd\u03b8\u03c5\u03bd\u03bf\u03c2 \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03af\u03b1\u03c2 \u03c0\u03b1\u03c1\u03b1\u03ba\u03bf\u03bb\u03bf\u03c5\u03b8\u03b5\u03af \u03c4\u03b9\u03c2 \u03b1\u03c3\u03c4\u03bf\u03c7\u03af\u03b5\u03c2 \u03c3\u03c4\u03b7\u03bd \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae. \u0388\u03bd\u03b1 metric \u03c7\u03c9\u03c1\u03af\u03c2 \u03b9\u03b4\u03b9\u03bf\u03ba\u03c4\u03ae\u03c4\u03b7 \u03ba\u03b1\u03b9 \u03b1\u03c0\u03cc\u03c6\u03b1\u03c3\u03b7 \u03c0\u03bf\u03c5 \u03bd\u03b1 \u03b5\u03be\u03b1\u03c1\u03c4\u03ac\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc \u03b1\u03c5\u03c4\u03cc \u03b3\u03af\u03bd\u03b5\u03c4\u03b1\u03b9 \u03b1\u03c0\u03bb\u03ce\u03c2 \u03b4\u03b9\u03b1\u03ba\u03bf\u03c3\u03bc\u03b7\u03c4\u03b9\u03ba\u03cc dashboard.<\/p>\n<h2 id=\"ti-den-apodeiknyei\">\u03a4\u03b9 \u03b4\u03b5\u03bd \u03b1\u03c0\u03bf\u03b4\u03b5\u03b9\u03ba\u03bd\u03cd\u03b5\u03b9 \u03b7 \u03bc\u03b5\u03bb\u03ad\u03c4\u03b7<\/h2>\n<p>\u039f\u03b9 \u03c3\u03c5\u03b3\u03b3\u03c1\u03b1\u03c6\u03b5\u03af\u03c2 \u03bc\u03b5\u03bb\u03ad\u03c4\u03b7\u03c3\u03b1\u03bd \u03bc\u03af\u03b1 \u03bf\u03b9\u03ba\u03bf\u03b3\u03ad\u03bd\u03b5\u03b9\u03b1 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03c9\u03bd, Qwen3, \u03c3\u03b5 \u03b4\u03cd\u03bf \u03ba\u03bb\u03af\u03bc\u03b1\u03ba\u03b5\u03c2 \u03ba\u03b1\u03b9 \u03c4\u03ad\u03c3\u03c3\u03b5\u03c1\u03b1 domains. \u03a4\u03b1 \u03b1\u03c0\u03bf\u03c4\u03b5\u03bb\u03ad\u03c3\u03bc\u03b1\u03c4\u03b1 \u03b2\u03b1\u03c3\u03af\u03b6\u03bf\u03bd\u03c4\u03b1\u03b9 \u03c3\u03b5 \u03c4\u03ad\u03c3\u03c3\u03b5\u03c1\u03b1 sampled validation trajectories \u03b1\u03bd\u03ac task, \u03b5\u03bd\u03ce \u03bf\u03c1\u03b9\u03c3\u03bc\u03ad\u03bd\u03b5\u03c2 \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03ad\u03c2 \u03b1\u03bd\u03ac domain \u03b5\u03af\u03bd\u03b1\u03b9 \u03bc\u03b9\u03ba\u03c1\u03ad\u03c2 \u03c3\u03b5 \u03c3\u03c7\u03ad\u03c3\u03b7 \u03bc\u03b5 \u03c0\u03b9\u03b8\u03b1\u03bd\u03ae run-to-run variation. \u03a4\u03bf PI Bias Score \u03b5\u03be\u03b1\u03c1\u03c4\u03ac\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc \u03c4\u03b1 \u03b5\u03c0\u03b9\u03bb\u03b5\u03b3\u03bc\u03ad\u03bd\u03b1 targets \u03ba\u03b1\u03b9 sampled positions.<\/p>\n<p>\u0397 \u03ad\u03c1\u03b5\u03c5\u03bd\u03b1 \u03b4\u03b5\u03bd \u03b4\u03bf\u03ba\u03af\u03bc\u03b1\u03c3\u03b5 \u03b1\u03bd \u03bf \u03c3\u03c5\u03bd\u03b4\u03c5\u03b1\u03c3\u03bc\u03cc\u03c2 self-distillation \u03bc\u03b5 verifiable reward \u03b4\u03b9\u03bf\u03c1\u03b8\u03ce\u03bd\u03b5\u03b9 \u03c4\u03bf \u03c0\u03c1\u03cc\u03b2\u03bb\u03b7\u03bc\u03b1. \u0391\u03bd\u03b1\u03c6\u03ad\u03c1\u03b5\u03b9 \u03c3\u03c7\u03b5\u03c4\u03b9\u03ba\u03ad\u03c2 \u03bc\u03b5\u03b8\u03cc\u03b4\u03bf\u03c5\u03c2 \u03c0\u03bf\u03c5 \u03ba\u03c1\u03b1\u03c4\u03bf\u03cd\u03bd \u03c4\u03bf reward \u03c9\u03c2 \u03ba\u03cd\u03c1\u03b9\u03bf \u03c3\u03ae\u03bc\u03b1 \u03ba\u03b1\u03b9 \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03bf\u03cd\u03bd \u03c4\u03bf SD \u03c9\u03c2 \u03b2\u03bf\u03b7\u03b8\u03b7\u03c4\u03b9\u03ba\u03cc \u03cc\u03c1\u03bf, \u03b1\u03bb\u03bb\u03ac \u03b4\u03b7\u03bb\u03ce\u03bd\u03b5\u03b9 \u03c1\u03b7\u03c4\u03ac \u03cc\u03c4\u03b9 \u03c4\u03b1 \u03b4\u03b9\u03ba\u03ac \u03c4\u03b7\u03c2 experiments \u03b4\u03b5\u03bd \u03b1\u03c0\u03b1\u03bd\u03c4\u03bf\u03cd\u03bd \u03c3\u03b5 \u03b1\u03c5\u03c4\u03cc \u03c4\u03bf \u03b5\u03c1\u03ce\u03c4\u03b7\u03bc\u03b1.<\/p>\n<p>\u03a4\u03bf \u03b1\u03c3\u03c6\u03b1\u03bb\u03ad\u03c2 \u03c3\u03c5\u03bc\u03c0\u03ad\u03c1\u03b1\u03c3\u03bc\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03bf: \u03c3\u03c4\u03b9\u03c2 \u03b5\u03be\u03b5\u03c4\u03b1\u03b6\u03cc\u03bc\u03b5\u03bd\u03b5\u03c2 \u03c3\u03c5\u03bd\u03b8\u03ae\u03ba\u03b5\u03c2, \u03ad\u03bd\u03b1 PI-conditioned per-token objective \u03c9\u03c2 \u03bc\u03bf\u03bd\u03b1\u03b4\u03b9\u03ba\u03cc training signal \u03b4\u03b5\u03bd \u03b5\u03c5\u03b8\u03c5\u03b3\u03c1\u03b1\u03bc\u03bc\u03af\u03c3\u03c4\u03b7\u03ba\u03b5 \u03bc\u03b5 \u03c4\u03b7\u03bd \u03bf\u03c1\u03b8\u03cc\u03c4\u03b7\u03c4\u03b1 \u03b4\u03cd\u03c3\u03ba\u03bf\u03bb\u03c9\u03bd \u03b5\u03c1\u03b3\u03b1\u03c3\u03b9\u03ce\u03bd. \u0397 \u03c0\u03c5\u03ba\u03bd\u03cc\u03c4\u03b7\u03c4\u03b1 \u03c4\u03bf\u03c5 supervision \u03b4\u03b5\u03bd \u03ae\u03c4\u03b1\u03bd \u03c4\u03bf \u03c0\u03c1\u03cc\u03b2\u03bb\u03b7\u03bc\u03b1 \u03b1\u03c0\u03cc \u03bc\u03cc\u03bd\u03b7 \u03c4\u03b7\u03c2\u00b7 \u03c4\u03bf target \u03b4\u03b5\u03bd \u03bc\u03c0\u03bf\u03c1\u03bf\u03cd\u03c3\u03b5 \u03bd\u03b1 \u03be\u03b5\u03c7\u03c9\u03c1\u03af\u03c3\u03b5\u03b9 \u03c4\u03bf \u03c3\u03cd\u03bd\u03bf\u03bb\u03bf \u03c4\u03c9\u03bd \u03c3\u03c9\u03c3\u03c4\u03ce\u03bd \u03bb\u03cd\u03c3\u03b5\u03c9\u03bd \u03b1\u03c0\u03cc \u03c4\u03b7 \u03bc\u03af\u03b1 \u03bb\u03cd\u03c3\u03b7 \u03c0\u03bf\u03c5 \u03b5\u03af\u03c7\u03b5 \u03b4\u03b5\u03b9.<\/p>\n<p>\u0395\u03c0\u03b5\u03b9\u03b4\u03ae \u03c0\u03c1\u03cc\u03ba\u03b5\u03b9\u03c4\u03b1\u03b9 \u03b3\u03b9\u03b1 \u03c0\u03c1\u03cc\u03c3\u03c6\u03b1\u03c4\u03bf arXiv preprint, \u03c4\u03b1 \u03b1\u03c0\u03bf\u03c4\u03b5\u03bb\u03ad\u03c3\u03bc\u03b1\u03c4\u03b1 \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03bf\u03bd\u03c4\u03b1\u03b9 \u03b1\u03bd\u03b5\u03be\u03ac\u03c1\u03c4\u03b7\u03c4\u03b7 \u03b1\u03bd\u03b1\u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae \u03ba\u03b1\u03b9 \u03ad\u03bb\u03b5\u03b3\u03c7\u03bf \u03c3\u03b5 \u03c0\u03b5\u03c1\u03b9\u03c3\u03c3\u03cc\u03c4\u03b5\u03c1\u03b1 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03b1. \u0397 \u03bc\u03b5\u03bb\u03ad\u03c4\u03b7 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b9\u03c3\u03c7\u03c5\u03c1\u03cc diagnostic \u03b5\u03c0\u03b9\u03c7\u03b5\u03af\u03c1\u03b7\u03bc\u03b1, \u03cc\u03c7\u03b9 \u03c4\u03b5\u03bb\u03b9\u03ba\u03ae \u03b1\u03c0\u03cc\u03c6\u03b1\u03c3\u03b7 \u03b3\u03b9\u03b1 \u03bf\u03bb\u03cc\u03ba\u03bb\u03b7\u03c1\u03bf \u03c4\u03bf \u03c0\u03b5\u03b4\u03af\u03bf \u03c4\u03bf\u03c5 self-distillation.<\/p>\n<h2 id=\"symperasma\">\u0391\u03c0\u03cc \u03c4\u03b7 \u03bc\u03af\u03bc\u03b7\u03c3\u03b7 \u03bc\u03b9\u03b1\u03c2 \u03bb\u03cd\u03c3\u03b7\u03c2 \u03c3\u03c4\u03b7 \u03bc\u03ad\u03c4\u03c1\u03b7\u03c3\u03b7 \u03c4\u03b7\u03c2 \u03bf\u03c1\u03b8\u03cc\u03c4\u03b7\u03c4\u03b1\u03c2<\/h2>\n<p>\u0397 \u03bc\u03b5\u03bb\u03ad\u03c4\u03b7 \u03c6\u03c9\u03c4\u03af\u03b6\u03b5\u03b9 \u03bc\u03b9\u03b1 \u03b5\u03c5\u03c1\u03cd\u03c4\u03b5\u03c1\u03b7 \u03b1\u03c1\u03c7\u03ae \u03b3\u03b9\u03b1 \u03c4\u03b7\u03bd \u03b5\u03c6\u03b1\u03c1\u03bc\u03bf\u03c3\u03bc\u03ad\u03bd\u03b7 \u03c4\u03b5\u03c7\u03bd\u03b7\u03c4\u03ae \u03bd\u03bf\u03b7\u03bc\u03bf\u03c3\u03cd\u03bd\u03b7: \u03cc\u03c4\u03b1\u03bd \u03b2\u03b5\u03bb\u03c4\u03b9\u03c3\u03c4\u03bf\u03c0\u03bf\u03b9\u03bf\u03cd\u03bc\u03b5 \u03ad\u03bd\u03b1 proxy, \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03b1\u03c0\u03bf\u03b4\u03b5\u03b9\u03ba\u03bd\u03cd\u03bf\u03c5\u03bc\u03b5 \u03cc\u03c4\u03b9 \u03c0\u03b1\u03c1\u03b1\u03bc\u03ad\u03bd\u03b5\u03b9 \u03c3\u03c5\u03bd\u03b4\u03b5\u03b4\u03b5\u03bc\u03ad\u03bd\u03bf \u03bc\u03b5 \u03c4\u03bf\u03bd \u03b5\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03b7\u03c3\u03b9\u03b1\u03ba\u03cc \u03c3\u03c4\u03cc\u03c7\u03bf. \u03a3\u03c4\u03bf self-distillation, \u03c4\u03bf proxy \u03ae\u03c4\u03b1\u03bd \u03b7 token-level \u03c3\u03c5\u03bc\u03c6\u03c9\u03bd\u03af\u03b1 \u03bc\u03b5 teacher \u03c0\u03bf\u03c5 \u03b5\u03af\u03c7\u03b5 \u03b4\u03b5\u03b9 \u03bc\u03af\u03b1 \u03c3\u03c9\u03c3\u03c4\u03ae trajectory. \u03a3\u03b5 \u03c0\u03b5\u03c1\u03b9\u03bf\u03c1\u03b9\u03c3\u03bc\u03ad\u03bd\u03b5\u03c2 \u03b5\u03c1\u03b3\u03b1\u03c3\u03af\u03b5\u03c2 \u03b1\u03c5\u03c4\u03cc \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b2\u03c1\u03af\u03c3\u03ba\u03b5\u03c4\u03b1\u03b9 \u03b1\u03c1\u03ba\u03b5\u03c4\u03ac \u03ba\u03bf\u03bd\u03c4\u03ac \u03c3\u03c4\u03b7\u03bd \u03bf\u03c1\u03b8\u03cc\u03c4\u03b7\u03c4\u03b1. \u03a3\u03b5 \u03b1\u03bd\u03bf\u03b9\u03c7\u03c4\u03cc reasoning, \u03b7 \u03b1\u03c0\u03cc\u03c3\u03c4\u03b1\u03c3\u03b7 \u03bc\u03b5\u03b3\u03b1\u03bb\u03ce\u03bd\u03b5\u03b9.<\/p>\n<p>\u0393\u03b9\u03b1 \u03ba\u03ac\u03b8\u03b5 AI roadmap, \u03b7 \u03c3\u03c9\u03c3\u03c4\u03ae \u03b5\u03c1\u03ce\u03c4\u03b7\u03c3\u03b7 \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03bc\u03cc\u03bd\u03bf \u00ab\u03c0\u03ad\u03c6\u03c4\u03b5\u03b9 \u03c4\u03bf loss;\u00bb, \u03b1\u03bb\u03bb\u03ac \u00ab\u03c0\u03bf\u03b9\u03b1 \u03c3\u03c5\u03bc\u03c0\u03b5\u03c1\u03b9\u03c6\u03bf\u03c1\u03ac \u03b1\u03bd\u03c4\u03b1\u03bc\u03b5\u03af\u03b2\u03b5\u03b9 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ac \u03b1\u03c5\u03c4\u03cc \u03c4\u03bf loss;\u00bb. \u0391\u03bd \u03b7 \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b7 \u03bc\u03af\u03bc\u03b7\u03c3\u03b7 \u03b4\u03b9\u03b1\u03c4\u03cd\u03c0\u03c9\u03c3\u03b7\u03c2, \u03b7 \u03c3\u03c5\u03bd\u03c4\u03bf\u03bc\u03af\u03b1 \u03ae \u03b7 \u03b1\u03c0\u03bf\u03c6\u03c5\u03b3\u03ae \u03b1\u03b2\u03b5\u03b2\u03b1\u03b9\u03cc\u03c4\u03b7\u03c4\u03b1\u03c2, \u03c4\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03c6\u03b1\u03af\u03bd\u03b5\u03c4\u03b1\u03b9 \u03c0\u03b9\u03bf polished \u03c7\u03c9\u03c1\u03af\u03c2 \u03bd\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c0\u03b9\u03bf \u03b1\u03be\u03b9\u03cc\u03c0\u03b9\u03c3\u03c4\u03bf.<\/p>\n<p>\u0397 \u03b5\u03c0\u03cc\u03bc\u03b5\u03bd\u03b7 \u03b5\u03c1\u03b5\u03c5\u03bd\u03b7\u03c4\u03b9\u03ba\u03ae \u03c0\u03c1\u03cc\u03ba\u03bb\u03b7\u03c3\u03b7 \u03b5\u03af\u03bd\u03b1\u03b9 target \u03c0\u03bf\u03c5 \u03b4\u03b9\u03b1\u03c4\u03b7\u03c1\u03b5\u03af \u03c4\u03b7\u03bd \u03c0\u03c5\u03ba\u03bd\u03ae \u03ba\u03b1\u03b8\u03bf\u03b4\u03ae\u03b3\u03b7\u03c3\u03b7, \u03b1\u03bb\u03bb\u03ac \u03c3\u03c5\u03bd\u03b4\u03ad\u03b5\u03b9 \u03c1\u03b7\u03c4\u03ac \u03c4\u03bf learning signal \u03bc\u03b5 \u03c4\u03b7\u03bd \u03b5\u03c0\u03b9\u03c4\u03c5\u03c7\u03af\u03b1 \u03c4\u03bf\u03c5 task \u03ba\u03b1\u03b9 \u03bc\u03b5 \u03c4\u03bf \u03c3\u03cd\u03bd\u03bf\u03bb\u03bf \u03c4\u03c9\u03bd \u03b1\u03c0\u03bf\u03b4\u03b5\u03ba\u03c4\u03ce\u03bd continuations. \u039c\u03ad\u03c7\u03c1\u03b9 \u03c4\u03cc\u03c4\u03b5, \u03bf\u03b9 \u03b5\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03ae\u03c3\u03b5\u03b9\u03c2 \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03bd\u03b1 \u03b1\u03bd\u03c4\u03b9\u03bc\u03b5\u03c4\u03c9\u03c0\u03af\u03b6\u03bf\u03c5\u03bd \u03c4\u03bf training loss \u03c9\u03c2 \u03ad\u03bd\u03b1 \u03c3\u03ae\u03bc\u03b1 \u03b1\u03bd\u03ac\u03bc\u03b5\u03c3\u03b1 \u03c3\u03b5 \u03c0\u03bf\u03bb\u03bb\u03ac \u03ba\u03b1\u03b9 \u03cc\u03c7\u03b9 \u03c9\u03c2 \u03b1\u03c0\u03cc\u03b4\u03b5\u03b9\u03be\u03b7 capability.<\/p>\n<p>\u0393\u03b9\u03b1 \u03bf\u03bc\u03ac\u03b4\u03b5\u03c2 \u03c0\u03bf\u03c5 \u03b8\u03ad\u03bb\u03bf\u03c5\u03bd \u03bd\u03b1 \u03bc\u03b5\u03c4\u03b1\u03c4\u03c1\u03ad\u03c8\u03bf\u03c5\u03bd AI \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03b1, \u03b5\u03c1\u03b3\u03b1\u03bb\u03b5\u03af\u03b1 \u03ba\u03b1\u03b9 business rules \u03c3\u03b5 \u03b5\u03bb\u03b5\u03b3\u03c7\u03cc\u03bc\u03b5\u03bd\u03b7 \u03b4\u03b9\u03b1\u03b4\u03b9\u03ba\u03b1\u03c3\u03af\u03b1, \u03bf\u03b9 <a href=\"https:\/\/twodots.gr\/aftomatismoi-epicheiriseon-ai\/\">\u0391\u03c5\u03c4\u03bf\u03bc\u03b1\u03c4\u03b9\u03c3\u03bc\u03bf\u03af \u0395\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03ae\u03c3\u03b5\u03c9\u03bd &amp; AI \u03c4\u03b7\u03c2 TWO DOTS<\/a> \u03be\u03b5\u03ba\u03b9\u03bd\u03bf\u03cd\u03bd \u03b1\u03c0\u03cc \u03c4\u03bf \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03cc workflow, \u03c4\u03b1 outcomes, \u03c4\u03b1 quality gates \u03ba\u03b1\u03b9 \u03c4\u03b1 \u03c3\u03b7\u03bc\u03b5\u03af\u03b1 \u03b1\u03bd\u03b8\u03c1\u03ce\u03c0\u03b9\u03bd\u03b7\u03c2 \u03ad\u03b3\u03ba\u03c1\u03b9\u03c3\u03b7\u03c2.<\/p>\n<section class=\"td-service-cta\">\n<div class=\"td-service-cta-content\">\n<p class=\"td-service-cta-eyebrow\">Business Automation &amp; AI by TWO DOTS<\/p>\n<p class=\"td-service-cta-title\">\u03a3\u03c5\u03bd\u03b4\u03ad\u03c3\u03c4\u03b5 \u03ba\u03ac\u03b8\u03b5 AI metric \u03bc\u03b5 \u03ad\u03bd\u03b1 \u03b1\u03c0\u03bf\u03c4\u03ad\u03bb\u03b5\u03c3\u03bc\u03b1 \u03c0\u03bf\u03c5 \u03b7 \u03b5\u03c0\u03b9\u03c7\u03b5\u03af\u03c1\u03b7\u03c3\u03b7 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b5\u03bb\u03ad\u03b3\u03be\u03b5\u03b9.<\/p>\n<p>\u0397 TWO DOTS \u03c7\u03b1\u03c1\u03c4\u03bf\u03b3\u03c1\u03b1\u03c6\u03b5\u03af \u03c4\u03bf workflow, \u03bf\u03c1\u03af\u03b6\u03b5\u03b9 task-level quality gates, \u03b4\u03bf\u03ba\u03b9\u03bc\u03ac\u03b6\u03b5\u03b9 failures \u03ba\u03b1\u03b9 \u03c3\u03c7\u03b5\u03b4\u03b9\u03ac\u03b6\u03b5\u03b9 human approvals \u03ba\u03b1\u03b9 monitoring, \u03ce\u03c3\u03c4\u03b5 \u03ad\u03bd\u03b1 AI \u03b2\u03ae\u03bc\u03b1 \u03bd\u03b1 \u03b1\u03be\u03b9\u03bf\u03bb\u03bf\u03b3\u03b5\u03af\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ae \u03c4\u03bf\u03c5 \u03b5\u03c0\u03af\u03b4\u03c1\u03b1\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03cc\u03c7\u03b9 \u03b1\u03c0\u03cc \u03ad\u03bd\u03b1 \u03b5\u03bd\u03c4\u03c5\u03c0\u03c9\u03c3\u03b9\u03b1\u03ba\u03cc proxy.<\/p>\n<div class=\"td-service-cta-actions\"><a class=\"td-service-cta-button\" href=\"https:\/\/twodots.gr\/aftomatismoi-epicheiriseon-ai\/\">Check out Business Automation &amp; AI<\/a><\/div>\n<\/div>\n<\/section>\n<section id=\"sychnes-erotiseis\" class=\"td-faq-section\">\n<div class=\"td-faq\">\n<p class=\"td-faq-heading\">Frequently Asked Questions (FAQs)<\/p>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u03a4\u03b9 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c4\u03bf self-distillation \u03c3\u03c4\u03b1 LLMs;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u0395\u03af\u03bd\u03b1\u03b9 \u03b5\u03ba\u03c0\u03b1\u03af\u03b4\u03b5\u03c5\u03c3\u03b7 \u03cc\u03c0\u03bf\u03c5 \u03c4\u03bf \u03af\u03b4\u03b9\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03b5\u03af \u03c9\u03c2 teacher \u03ba\u03b1\u03b9 student. \u039f teacher \u03bb\u03b1\u03bc\u03b2\u03ac\u03bd\u03b5\u03b9 \u03c0\u03c1\u03cc\u03c3\u03b8\u03b5\u03c4\u03b7 \u03c0\u03bb\u03b7\u03c1\u03bf\u03c6\u03bf\u03c1\u03af\u03b1 \u03ba\u03b1\u03b9 \u03bf student \u03b5\u03ba\u03c0\u03b1\u03b9\u03b4\u03b5\u03cd\u03b5\u03c4\u03b1\u03b9 \u03bd\u03b1 \u03c0\u03c1\u03bf\u03c3\u03b5\u03b3\u03b3\u03af\u03c3\u03b5\u03b9 \u03c4\u03b9\u03c2 token-level \u03c0\u03c1\u03bf\u03b2\u03bb\u03ad\u03c8\u03b5\u03b9\u03c2 \u03c4\u03bf\u03c5.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u03a4\u03b9 \u03c3\u03b7\u03bc\u03b1\u03af\u03bd\u03b5\u03b9 privileged information;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u0395\u03af\u03bd\u03b1\u03b9 \u03c0\u03bb\u03b7\u03c1\u03bf\u03c6\u03bf\u03c1\u03af\u03b1 \u03b4\u03b9\u03b1\u03b8\u03ad\u03c3\u03b9\u03bc\u03b7 \u03c3\u03c4\u03bf\u03bd teacher \u03ba\u03b1\u03c4\u03ac \u03c4\u03b7\u03bd \u03b5\u03ba\u03c0\u03b1\u03af\u03b4\u03b5\u03c5\u03c3\u03b7 \u03b1\u03bb\u03bb\u03ac \u03cc\u03c7\u03b9 \u03c3\u03c4\u03bf\u03bd student \u03ba\u03b1\u03c4\u03ac \u03c4\u03bf inference, \u03cc\u03c0\u03c9\u03c2 \u03bc\u03b9\u03b1 reference solution, \u03ad\u03bd\u03b1 hint \u03ae feedback \u03b1\u03c0\u03cc \u03b5\u03ba\u03c4\u03ad\u03bb\u03b5\u03c3\u03b7.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u0397 \u03bc\u03b5\u03bb\u03ad\u03c4\u03b7 \u03bb\u03ad\u03b5\u03b9 \u03cc\u03c4\u03b9 \u03ba\u03ac\u03b8\u03b5 self-distillation \u03b1\u03c0\u03bf\u03c4\u03c5\u03b3\u03c7\u03ac\u03bd\u03b5\u03b9;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u038c\u03c7\u03b9. \u0395\u03be\u03b5\u03c4\u03ac\u03b6\u03b5\u03b9 PI-conditioned per-token self-distillation \u03c9\u03c2 \u03bc\u03bf\u03bd\u03b1\u03b4\u03b9\u03ba\u03cc objective \u03c3\u03b5 \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03b1 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03b1 \u03ba\u03b1\u03b9 \u03b4\u03cd\u03c3\u03ba\u03bf\u03bb\u03b1 domains. \u0394\u03b5\u03bd \u03b1\u03c0\u03bf\u03c1\u03c1\u03af\u03c0\u03c4\u03b5\u03b9 \u03ba\u03ac\u03b8\u03b5 \u03bc\u03bf\u03c1\u03c6\u03ae distillation \u03ae \u03c3\u03c5\u03bd\u03b4\u03c5\u03b1\u03c3\u03bc\u03cc \u03bc\u03b5 rewards.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u0393\u03b9\u03b1\u03c4\u03af \u03b4\u03b5\u03bd \u03b1\u03c1\u03ba\u03b5\u03af \u03b7 \u03c0\u03c4\u03ce\u03c3\u03b7 \u03c4\u03bf\u03c5 training loss;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u0395\u03c0\u03b5\u03b9\u03b4\u03ae \u03c4\u03bf loss \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03bc\u03b5\u03c4\u03c1\u03ac \u03ba\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03b7 \u03bc\u03af\u03bc\u03b7\u03c3\u03b7 \u03bc\u03b9\u03b1\u03c2 \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03b7\u03c2 trajectory \u03c7\u03c9\u03c1\u03af\u03c2 \u03bd\u03b1 \u03be\u03b5\u03c7\u03c9\u03c1\u03af\u03b6\u03b5\u03b9 \u03c3\u03c9\u03c3\u03c4\u03ac \u03ba\u03b1\u03b9 \u03bb\u03b1\u03bd\u03b8\u03b1\u03c3\u03bc\u03ad\u03bd\u03b1 rollouts. \u03a7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03b1\u03bd\u03b5\u03be\u03ac\u03c1\u03c4\u03b7\u03c4\u03b7 task-level validation.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u03a4\u03b9 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c4\u03bf PI Bias Score;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u039c\u03b5\u03c4\u03c1\u03ac \u03c0\u03cc\u03c3\u03bf \u03c0\u03b5\u03c1\u03b9\u03c3\u03c3\u03cc\u03c4\u03b5\u03c1\u03bf \u03bf PI-conditioned teacher \u03b5\u03c5\u03bd\u03bf\u03b5\u03af \u03ad\u03bd\u03b1\u03bd target \u03c3\u03b5 \u03c3\u03c7\u03ad\u03c3\u03b7 \u03bc\u03b5 \u03c4\u03bf\u03bd student. \u0397 \u03c3\u03cd\u03b3\u03ba\u03c1\u03b9\u03c3\u03b7 \u03b5\u03bd\u03b1\u03bb\u03bb\u03b1\u03ba\u03c4\u03b9\u03ba\u03ce\u03bd \u03c3\u03c9\u03c3\u03c4\u03ce\u03bd \u03ba\u03b1\u03b9 \u03bb\u03b1\u03bd\u03b8\u03b1\u03c3\u03bc\u03ad\u03bd\u03c9\u03bd \u03bb\u03cd\u03c3\u03b5\u03c9\u03bd \u03b4\u03b5\u03af\u03c7\u03bd\u03b5\u03b9 \u03b1\u03bd \u03bf teacher \u03ad\u03c7\u03b5\u03b9 \u03b1\u03b3\u03ba\u03c5\u03c1\u03c9\u03b8\u03b5\u03af \u03c3\u03c4\u03b7 \u03bb\u03cd\u03c3\u03b7 \u03c0\u03bf\u03c5 \u03b5\u03af\u03b4\u03b5.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u0393\u03b9\u03b1\u03c4\u03af \u03b7 \u03c4\u03b5\u03c7\u03bd\u03b9\u03ba\u03ae \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03b5\u03af \u03c3\u03b5 \u03b5\u03c5\u03ba\u03bf\u03bb\u03cc\u03c4\u03b5\u03c1\u03b5\u03c2 \u03b5\u03c1\u03b3\u03b1\u03c3\u03af\u03b5\u03c2;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u03a3\u03b5 \u03c3\u03cd\u03bd\u03c4\u03bf\u03bc\u03b5\u03c2 \u03b1\u03c0\u03b1\u03bd\u03c4\u03ae\u03c3\u03b5\u03b9\u03c2 \u03ae bounded choices, \u03bc\u03af\u03b1 reference solution \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03ba\u03b1\u03bb\u03cd\u03c0\u03c4\u03b5\u03b9 \u03bc\u03b5\u03b3\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03bf \u03bc\u03ad\u03c1\u03bf\u03c2 \u03c4\u03bf\u03c5 \u03c7\u03ce\u03c1\u03bf\u03c5 \u03c4\u03c9\u03bd \u03c3\u03c9\u03c3\u03c4\u03ce\u03bd \u03b1\u03c0\u03b1\u03bd\u03c4\u03ae\u03c3\u03b5\u03c9\u03bd \u03ba\u03b1\u03b9 \u03c5\u03c0\u03ac\u03c1\u03c7\u03b5\u03b9 \u03bb\u03b9\u03b3\u03cc\u03c4\u03b5\u03c1\u03b7 \u03c7\u03c1\u03ae\u03c3\u03b9\u03bc\u03b7 \u03b5\u03be\u03b5\u03c1\u03b5\u03cd\u03bd\u03b7\u03c3\u03b7 \u03b3\u03b9\u03b1 \u03bd\u03b1 \u03ba\u03b1\u03c4\u03b1\u03c3\u03c4\u03b1\u03bb\u03b5\u03af.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u03a4\u03b9 \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03bc\u03b5\u03c4\u03c1\u03ac \u03bc\u03b9\u03b1 \u03b5\u03c0\u03b9\u03c7\u03b5\u03af\u03c1\u03b7\u03c3\u03b7 \u03c3\u03b5 AI agents;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u0395\u03c0\u03b1\u03bb\u03b7\u03b8\u03b5\u03cd\u03c3\u03b9\u03bc\u03b7 \u03bf\u03bb\u03bf\u03ba\u03bb\u03ae\u03c1\u03c9\u03c3\u03b7 task, \u03b1\u03ba\u03c1\u03af\u03b2\u03b5\u03b9\u03b1, \u03c3\u03c9\u03c3\u03c4\u03ae \u03c7\u03c1\u03ae\u03c3\u03b7 \u03b5\u03c1\u03b3\u03b1\u03bb\u03b5\u03af\u03c9\u03bd, \u03c4\u03ae\u03c1\u03b7\u03c3\u03b7 \u03c0\u03bf\u03bb\u03b9\u03c4\u03b9\u03ba\u03ae\u03c2, \u03b1\u03bd\u03ac\u03ba\u03b1\u03bc\u03c8\u03b7 \u03b1\u03c0\u03cc failures, \u03b1\u03bd\u03b8\u03b5\u03ba\u03c4\u03b9\u03ba\u03cc\u03c4\u03b7\u03c4\u03b1 \u03c3\u03b5 \u03b1\u03bb\u03bb\u03b1\u03b3\u03ad\u03c2 context \u03ba\u03b1\u03b9 \u03b1\u03bd\u03ac\u03b3\u03ba\u03b7 \u03b1\u03bd\u03b8\u03c1\u03ce\u03c0\u03b9\u03bd\u03b7\u03c2 \u03b4\u03b9\u03cc\u03c1\u03b8\u03c9\u03c3\u03b7\u03c2.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u03a0\u03bf\u03b9\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b7 \u03b2\u03b1\u03c3\u03b9\u03ba\u03ae \u03b1\u03bd\u03bf\u03b9\u03c7\u03c4\u03ae \u03b5\u03c1\u03b5\u03c5\u03bd\u03b7\u03c4\u03b9\u03ba\u03ae \u03c0\u03c1\u03cc\u03ba\u03bb\u03b7\u03c3\u03b7;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u039d\u03b1 \u03c3\u03c7\u03b5\u03b4\u03b9\u03b1\u03c3\u03c4\u03b5\u03af \u03c0\u03c5\u03ba\u03bd\u03cc training target \u03c0\u03bf\u03c5 \u03ba\u03c9\u03b4\u03b9\u03ba\u03bf\u03c0\u03bf\u03b9\u03b5\u03af \u03c4\u03b7\u03bd \u03bf\u03c1\u03b8\u03cc\u03c4\u03b7\u03c4\u03b1 \u03ba\u03b1\u03b9 \u03c4\u03bf \u03c3\u03cd\u03bd\u03bf\u03bb\u03bf \u03c4\u03c9\u03bd \u03b1\u03c0\u03bf\u03b4\u03b5\u03ba\u03c4\u03ce\u03bd continuations, \u03b1\u03bd\u03c4\u03af \u03bd\u03b1 \u03b1\u03b3\u03ba\u03c5\u03c1\u03ce\u03bd\u03b5\u03c4\u03b1\u03b9 \u03c3\u03b5 \u03bc\u03af\u03b1 \u03bc\u03cc\u03bd\u03bf reference trajectory.<\/p>\n<\/div>\n<\/details>\n<\/div>\n<\/section>\n<div class=\"td-source-list\">\n<p id=\"piges\" class=\"td-source-list-title\">Sources<\/p>\n<ul>\n<li><a href=\"https:\/\/arxiv.org\/abs\/2608.04794\" target=\"_blank\" rel=\"noopener\">arXiv \u2014 Privileged, but Biased: How PI-Conditioned Teachers Break Self-Distillation<\/a><\/li>\n<li><a href=\"https:\/\/arxiv.org\/abs\/2601.20802\" target=\"_blank\" rel=\"noopener\">arXiv \u2014 Reinforcement Learning via Self-Distillation (SDPO)<\/a><\/li>\n<li><a href=\"https:\/\/arxiv.org\/abs\/2601.18734\" target=\"_blank\" rel=\"noopener\">arXiv \u2014 Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models (OPSD)<\/a><\/li>\n<\/ul>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>\u03a4\u03bf self-distillation \u03c3\u03c4\u03b1 LLMs \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03bc\u03b5\u03b9\u03ce\u03bd\u03b5\u03b9 \u03c4\u03bf training loss \u03c7\u03c9\u03c1\u03af\u03c2 \u03bd\u03b1 \u03b2\u03b5\u03bb\u03c4\u03b9\u03ce\u03bd\u03b5\u03b9 \u03c4\u03bf reasoning. \u0397 \u03bc\u03b5\u03bb\u03ad\u03c4\u03b7 \u03b5\u03be\u03b7\u03b3\u03b5\u03af \u03c4\u03bf PI bias \u03ba\u03b1\u03b9 \u03c4\u03b1 \u03c3\u03c9\u03c3\u03c4\u03ac task-level metrics.<\/p>","protected":false},"author":1,"featured_media":88517,"comment_status":"open","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_gspb_post_css":"","content-type":"","footnotes":""},"categories":[17366],"tags":[6506,9261,9225,7477,3597],"class_list":["post-88349","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-digital-marketing","tag-ai-agents","tag-ai-strategy","tag-llm","tag-machine-learning","tag-techniti-noimosyni"],"blocksy_meta":{"styles_descriptor":{"styles":{"desktop":"","tablet":"","mobile":""},"google_fonts":[],"version":7}},"_links":{"self":[{"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/posts\/88349","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/comments?post=88349"}],"version-history":[{"count":1,"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/posts\/88349\/revisions"}],"predecessor-version":[{"id":88441,"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/posts\/88349\/revisions\/88441"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/media\/88517"}],"wp:attachment":[{"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/media?parent=88349"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/categories?post=88349"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/tags?post=88349"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}