{"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/think-again-networks-the-delta-loss-and-an","title":"Think Again Networks and the Delta Loss","arxiv_id":"1904.11816","date":"2019-04-26","proceeding":null,"authors":["Alexandre Salle","Marcelo Prates"],"abstract":"This short paper introduces an abstraction called Think Again Networks\n(ThinkNet) which can be applied to any state-dependent function (such as a\nrecurrent neural network).","url_abs":"http://arxiv.org/abs/1904.11816v2","url_pdf":"http://arxiv.org/pdf/1904.11816v2.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":"think-again-networks-the-delta-loss-and-an","repo_url":"https://github.com/jb33k/awd-lstm-lm-ThinkNet","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"BSD-3-Clause"}}],"tasks":[{"task_slug":"language-modelling","task_name":"Language Modelling"}],"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}