{"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/generating-news-headlines-with-recurrent","title":"Generating News Headlines with Recurrent Neural Networks","arxiv_id":"1512.01712","date":"2015-12-05","proceeding":null,"authors":["Konstantin Lopyrev"],"abstract":"We describe an application of an encoder-decoder recurrent neural network\nwith LSTM units and attention to generating headlines from the text of news\narticles. We find that the model is quite effective at concisely paraphrasing\nnews articles. Furthermore, we study how the neural network decides which input\nwords to pay attention to, and specifically we identify the function of the\ndifferent neurons in a simplified attention mechanism. Interestingly, our\nsimplified attention mechanism performs better that the more complex attention\nmechanism on a held out set of articles.","url_abs":"http://arxiv.org/abs/1512.01712v1","url_pdf":"http://arxiv.org/pdf/1512.01712v1.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":"generating-news-headlines-with-recurrent","repo_url":"https://github.com/PKU-TANGENT/nlp-tutorial","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"generating-news-headlines-with-recurrent","repo_url":"https://github.com/danedabomb/HeadlineGenerator","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"generating-news-headlines-with-recurrent","repo_url":"https://github.com/heenabansal/seq2seq_chatbot_encoder_decoder_model_with_attention","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"generating-news-headlines-with-recurrent","repo_url":"https://github.com/vivekmids/nlp-summarization","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"articles","task_name":"Articles"},{"task_slug":"decoder","task_name":"Decoder"}],"methods":[{"method_slug":"lstm","method_name":"LSTM"},{"method_slug":"sigmoid-activation","method_name":"Sigmoid Activation"},{"method_slug":"tanh-activation","method_name":"Tanh Activation"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1512.01712","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}