{"id":195027,"date":"2024-08-23T05:36:34","date_gmt":"2024-08-23T10:36:34","guid":{"rendered":"https:\/\/lifeboat.com\/blog\/2024\/08\/the-circle-of-life-publish-or-perish-edition-two-journals-retract-more-than-40-papers"},"modified":"2024-08-23T05:36:34","modified_gmt":"2024-08-23T10:36:34","slug":"the-circle-of-life-publish-or-perish-edition-two-journals-retract-more-than-40-papers","status":"publish","type":"post","link":"https:\/\/lifeboat.com\/blog\/2024\/08\/the-circle-of-life-publish-or-perish-edition-two-journals-retract-more-than-40-papers","title":{"rendered":"The circle of life, publish or perish edition: Two journals retract more than 40 papers"},"content":{"rendered":"<p style=\"padding-right: 20px\"><a class=\"aligncenter blog-photo\" href=\"https:\/\/lifeboat.com\/blog.images\/the-circle-of-life-publish-or-perish-edition-two-journals-retract-more-than-40-papers.jpg\"><\/a><\/p>\n<p>The team has released the width-pruned version of the model on <a href=\"https:\/\/huggingface.co\/nvidia\/Llama-3.1-Minitron-4B-Width-Base\" target=\"_blank\" rel=\"noreferrer noopener\">Hugging Face<\/a> under the Nvidia Open Model License, which allows for commercial use. This makes it accessible to a wider range of users and developers who can benefit from its efficiency and performance.<\/p>\n<p>\u201cPruning and classical knowledge distillation is a highly cost-effective method to progressively obtain LLMs [large language models] of smaller size, achieving superior accuracy compared to training from scratch across all domains,\u201d the researchers wrote. \u201cIt serves as a more effective and data-efficient approach compared to either synthetic-data-style fine-tuning or pretraining from scratch.\u201d<\/p>\n<p>This work is a reminder of the value and importance of the open-source community to the progress of AI. Pruning and distillation are part of a wider body of research that is enabling companies to optimize and customize LLMs at a fraction of the normal cost. Other notable works in the field include Sakana AI\u2019s <a href=\"https:\/\/venturebeat.com\/ai\/sakana-ais-evolutionary-algorithm-discovers-new-architectures-for-generative-models\/\">evolutionary model-merging algorithm<\/a>, which makes it possible to assemble parts of different models to combine their strengths without the need for expensive training resources.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The team has released the width-pruned version of the model on Hugging Face under the Nvidia Open Model License, which allows for commercial use. This makes it accessible to a wider range of users and developers who can benefit from its efficiency and performance. \u201cPruning and classical knowledge distillation is a highly cost-effective method to [\u2026]<\/p>\n","protected":false},"author":661,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[41,6],"tags":[],"class_list":["post-195027","post","type-post","status-publish","format-standard","hentry","category-information-science","category-robotics-ai"],"_links":{"self":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/195027","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/users\/661"}],"replies":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/comments?post=195027"}],"version-history":[{"count":0,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/195027\/revisions"}],"wp:attachment":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/media?parent=195027"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/categories?post=195027"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/tags?post=195027"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}