{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/reproduction-report-on-learn-to-pay-attention","title":"Reproduction Report on \"Learn to Pay Attention\"","arxiv_id":"1812.04650","date":"2018-12-11","proceeding":null,"authors":["Levan Shugliashvili","Davit Soselia","Shota Amashukeli","Irakli Koberidze"],"abstract":"We have successfully implemented the \"Learn to Pay Attention\" model of\nattention mechanism in convolutional neural networks, and have replicated the\nresults of the original paper in the categories of image classification and\nfine-grained recognition.","url_abs":"http://arxiv.org/abs/1812.04650v1","url_pdf":"http://arxiv.org/pdf/1812.04650v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"reproduction-report-on-learn-to-pay-attention","repo_url":"https://github.com/DadianisBidza/LearnToPayAttention-Keras","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"image-classification","task_name":"Image Classification"},{"task_slug":"image-classification","task_name":"image-classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}