{"url":"/method/scarlet","slug":"scarlet","name":"SCARLET","full_name":"SCARLET","full_name_withheld":false,"description_markdown":"**SCARLET** is a type of convolutional neural architecture learnt by the [SCARLET-NAS](https://paperswithcode.com/method/scarlet-nas) [neural architecture search](https://paperswithcode.com/method/neural-architecture-search) method. The three variants are SCARLET-A, SCARLET-B and SCARLET-C. The basic building block is MBConvs from [MobileNetV2](https://paperswithcode.com/method/mobilenetv2). Squeeze-and-excitation layers are also experimented with.","description_state":"present","introduced_year":null,"introduced_by":{"title":null,"paper":null,"first_author":null,"n_authors":0,"url_abs":null,"archive_paper_url":null},"source":{"url":"https://arxiv.org/abs/1908.06022v6","title":"SCARLET-NAS: Bridging the Gap between Stability and Scalability in Weight-sharing Neural Architecture Search","url_on_a_paper_host":true},"code_snippet_url":"https://github.com/xiaomi-automl/SCARLET-NAS/blob/bfcbc1c7c82266c2350836ff3c577248be9b000b/models/Scarlet_A.py#L6","code_snippet_url_on_a_code_host":true,"categories":[{"area":"Computer Vision","area_id":"computer-vision","collection":"Convolutional Neural Networks","url":"/methods/category/convolutional-neural-networks","pwc_aliases":[]}],"n_papers_tagged":4,"archive_num_papers":null,"papers_newest_first":[{"paper":"/paper/soft-label-caching-and-sharpening-for","title":"Soft-Label Caching and Sharpening for Communication-Efficient Federated Distillation","date":"2025-04-28","arxiv_id":"2504.19602","n_code_links":1,"syntology":null},{"paper":null,"title":"AI-Based Decadal Predictive Analysis of Twenty Infectious Diseases in China with an Improved BSTS-MCMC Model","date":"2023-10-06","arxiv_id":"2310.12363","n_code_links":0,"syntology":null},{"paper":null,"title":"In vitro micropropagation and apocarotenoid gene expression in saffron","date":"2022-08-28","arxiv_id":"2208.13292","n_code_links":0,"syntology":null},{"paper":"/paper/scarletnas-bridging-the-gap-between","title":"SCARLET-NAS: Bridging the Gap between Stability and Scalability in Weight-sharing Neural Architecture Search","date":"2019-08-16","arxiv_id":"1908.06022","n_code_links":1,"syntology":null}],"papers_shown":4,"tasks":[{"task":"/task/automl","name":"AutoML","papers":1},{"task":"/task/culture","name":"Cultural Vocal Bursts Intensity Prediction","papers":1},{"task":"/task/federated-learning","name":"Federated Learning","papers":1},{"task":"/task/image-classification","name":"Image Classification","papers":1},{"task":"/task/management","name":"Management","papers":1},{"task":"/task/architecture-search","name":"Neural Architecture Search","papers":1},{"task":"/task/time-series-1","name":"Time Series","papers":1}],"tasks_shown":7,"n_tasks":7,"usage_by_year":[{"year":"2019","papers":1},{"year":"2022","papers":1},{"year":"2023","papers":1},{"year":"2025","papers":1}],"row_source":"embedded","archive":{"source":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","archive_url":"https://paperswithcode.com/method/scarlet"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}