{"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/feed-forward-networks-with-attention-can","title":"Feed-Forward Networks with Attention Can Solve Some Long-Term Memory Problems","arxiv_id":"1512.08756","date":"2015-12-29","proceeding":null,"authors":["Colin Raffel","Daniel P. W. Ellis"],"abstract":"We propose a simplified model of attention which is applicable to\nfeed-forward neural networks and demonstrate that the resulting model can solve\nthe synthetic \"addition\" and \"multiplication\" long-term memory problems for\nsequence lengths which are both longer and more widely varying than the best\npublished results for these tasks.","url_abs":"http://arxiv.org/abs/1512.08756v5","url_pdf":"http://arxiv.org/pdf/1512.08756v5.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":"feed-forward-networks-with-attention-can","repo_url":"https://github.com/WenYanger/Contextual-Attention","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"feed-forward-networks-with-attention-can","repo_url":"https://github.com/dtsbourg/ff-attention","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"feed-forward-networks-with-attention-can","repo_url":"https://github.com/firfre/Chinese-Text-sentiment-analysis-with-key-word","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"feed-forward-networks-with-attention-can","repo_url":"https://github.com/shawnyxiao/textclassification-keras","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"feed-forward-networks-with-attention-can","repo_url":"https://github.com/zaczou/keras_summary","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=1512.08756","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}