{"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/dynamic-entity-representations-in-neural","title":"Dynamic Entity Representations in Neural Language Models","arxiv_id":"1708.00781","date":"2017-08-02","proceeding":"EMNLP 2017 9","authors":["Yangfeng Ji","Chenhao Tan","Sebastian Martschat","Yejin Choi","Noah A. Smith"],"abstract":"Understanding a long document requires tracking how entities are introduced\nand evolve over time. We present a new type of language model, EntityNLM, that\ncan explicitly model entities, dynamically update their representations, and\ncontextually generate their mentions. Our model is generative and flexible; it\ncan model an arbitrary number of entities in context while generating each\nentity mention at an arbitrary length. In addition, it can be used for several\ndifferent tasks such as language modeling, coreference resolution, and entity\nprediction. Experimental results with all these tasks demonstrate that our\nmodel consistently outperforms strong baselines and prior work.","url_abs":"http://arxiv.org/abs/1708.00781v1","url_pdf":"http://arxiv.org/pdf/1708.00781v1.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":"dynamic-entity-representations-in-neural","repo_url":"https://github.com/smartschat/cort","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"dynamic-entity-representations-in-neural","repo_url":"https://github.com/jiyfeng/entitynlm","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"coreference-resolution","task_name":"Coreference Resolution"},{"task_slug":"language-modeling","task_name":"Language Modeling"},{"task_slug":"language-modelling","task_name":"Language Modelling"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1708.00781","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}