{"id":5683,"date":"2024-10-31T04:57:10","date_gmt":"2024-10-30T19:57:10","guid":{"rendered":"https:\/\/devneko.jp\/wordpress\/?p=5683"},"modified":"2024-10-31T04:57:10","modified_gmt":"2024-10-30T19:57:10","slug":"unleashing-reasoning-capability-of-llms-via-scalable-question-synthesis-from-scratch","status":"publish","type":"post","link":"https:\/\/devneko.jp\/wordpress\/?p=5683","title":{"rendered":"Unleashing Reasoning Capability of LLMs via Scalable Question Synthesis from Scratch\u00a0"},"content":{"rendered":"\n<ul class=\"wp-block-list\">\n<li><strong>Unleashing Reasoning Capability of LLMs via Scalable Question Synthesis from Scratch\u00a0<\/strong>[28.5]<br>ScaleQuest\u306f\u30b9\u30b1\u30fc\u30e9\u30d6\u30eb\u3067\u65ac\u65b0\u306a\u30c7\u30fc\u30bf\u5408\u6210\u624b\u6cd5\u3067\u3042\u308b\u3002 \u8907\u96d1\u306a\u62e1\u5f35\u5236\u7d04\u3092\u6301\u3064\u30b7\u30fc\u30c9\u30c7\u30fc\u30bf\u3092\u5fc5\u8981\u3068\u305b\u305a\u306b\u3001\u30b9\u30af\u30e9\u30c3\u30c1\u304b\u3089\u8cea\u554f\u3092\u751f\u6210\u3059\u308b\u3002 \u4e3b\u8981\u306a\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30e2\u30c7\u30eb\u306e\u6027\u80fd\u3092\u666e\u904d\u7684\u306b\u5411\u4e0a\u3055\u305b\u308b\u3053\u3068\u304c\u3067\u304d\u308b\u3002<br><a href=\"http:\/\/arxiv.org\/abs\/2410.18693v1\">\u8ad6\u6587<\/a>\u00a0\u00a0<a href=\"https:\/\/fugumt.com\/fugumt\/paper_check\/2410.18693v1\">\u53c2\u8003\u8a33\uff08\u30e1\u30bf\u30c7\u30fc\u30bf\uff09<\/a>\u00a0 \u00a0(Thu, 24 Oct 2024 12:42:04 GMT)<\/li>\n\n\n\n<li>\u5546\u7528\u30e2\u30c7\u30eb\u3067\u306f\u5e83\u304f\u5229\u7528\u3055\u308c\u3066\u3044\u308b\u3068\u601d\u308f\u308c\u308b\u3001\u5408\u6210\u30c7\u30fc\u30bf\u3092\u4ecb\u3057\u3066\u30e2\u30c7\u30eb\u6027\u80fd\u3092\u5f37\u5316\u3059\u308b\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\u306e\u63d0\u6848\u3002\u300c Our experiments demonstrate the model\u2019s self-improvement capability, meaning that it can generate data of higher quality than its original training set.\u300d\u3068\u3044\u3046\u8a18\u8f09\u3082\u8208\u5473\u6df1\u3044\u3002<\/li>\n\n\n\n<li>\u30ea\u30dd\u30b8\u30c8\u30ea\u306f<a href=\"https:\/\/github.com\/yyDing1\/ScaleQuest\">GitHub &#8211; yyDing1\/ScaleQuest: We introduce ScaleQuest, a scalable, novel and cost-effective data synthesis method to unleash the reasoning capability of LLMs.<\/a><\/li>\n<\/ul>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[390],"class_list":["post-5683","post","type-post","status-publish","format-standard","hentry","category-arxiv","tag-synthetic-data"],"_links":{"self":[{"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/5683","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=5683"}],"version-history":[{"count":0,"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/5683\/revisions"}],"wp:attachment":[{"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=5683"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=5683"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=5683"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}