{"id":9088,"date":"2025-12-14T07:02:24","date_gmt":"2025-12-14T07:02:24","guid":{"rendered":"https:\/\/mailitics.com\/index.php\/2025\/12\/14\/neurips-2025-best-paper-review-qwens-systematic-exploration-of-attention-gating\/"},"modified":"2025-12-14T07:02:24","modified_gmt":"2025-12-14T07:02:24","slug":"neurips-2025-best-paper-review-qwens-systematic-exploration-of-attention-gating","status":"publish","type":"post","link":"https:\/\/mailitics.com\/index.php\/2025\/12\/14\/neurips-2025-best-paper-review-qwens-systematic-exploration-of-attention-gating\/","title":{"rendered":"NeurIPS 2025 Best Paper Review: Qwen\u2019s Systematic Exploration of Attention Gating"},"content":{"rendered":"<p>    NeurIPS 2025 Best Paper Review: Qwen\u2019s Systematic Exploration of Attention Gating<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n    <!-- no image --><br \/>\n \t<BR><br \/>\n<BR><\/BR><\/p>\n<div>\n<p>This one little trick can bring about enhanced training stability, the use of larger learning rates and improved scaling properties<\/p>\n<p>The post <a href=\"https:\/\/towardsdatascience.com\/neurips-2025-best-paper-review-qwens-systematic-exploration-of-attention-gating\/\">NeurIPS 2025 Best Paper Review: Qwen\u2019s Systematic Exploration of Attention Gating<\/a> appeared first on <a href=\"https:\/\/towardsdatascience.com\/\">Towards Data Science<\/a>.<\/p>\n<\/div>\n<p> \t<BR><br \/>\n <BR><\/BR><br \/>\n    Sean Moran<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n<a href=\"https:\/\/towardsdatascience.com\/neurips-2025-best-paper-review-qwens-systematic-exploration-of-attention-gating\/\">Go to original source<\/a><br \/>\n \t<BR><br \/>\n <BR><\/BR><\/p>\n","protected":false},"excerpt":{"rendered":"<p>NeurIPS 2025 Best Paper Review: Qwen\u2019s Systematic Exploration of Attention Gating This one little trick can bring about enhanced training stability, the use of larger learning rates and improved scaling properties The post NeurIPS 2025 Best Paper Review: Qwen\u2019s Systematic Exploration of Attention Gating appeared first on Towards Data Science. Sean Moran Go to original [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[62,69,83,240,71,87,4419,70],"tags":[1015,4420],"class_list":["post-9088","post","type-post","status-publish","format-standard","hentry","category-aimldsaimlds","category-artificial-intelligence","category-data-science","category-editors-pick","category-large-language-models","category-llm","category-llms-large-language-models","category-machine-learning","tag-best","tag-neurips"],"_links":{"self":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/9088"}],"collection":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/comments?post=9088"}],"version-history":[{"count":0,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/9088\/revisions"}],"wp:attachment":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/media?parent=9088"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/categories?post=9088"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/tags?post=9088"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}