{"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/question-dependent-recurrent-entity-network","title":"Question Dependent Recurrent Entity Network for Question Answering","arxiv_id":"1707.07922","date":"2017-07-25","proceeding":null,"authors":["Andrea Madotto","Giuseppe Attardi"],"abstract":"Question Answering is a task which requires building models capable of\nproviding answers to questions expressed in human language. Full question\nanswering involves some form of reasoning ability. We introduce a neural\nnetwork architecture for this task, which is a form of $Memory\\ Network$, that\nrecognizes entities and their relations to answers through a focus attention\nmechanism. Our model is named $Question\\ Dependent\\ Recurrent\\ Entity\\ Network$\nand extends $Recurrent\\ Entity\\ Network$ by exploiting aspects of the question\nduring the memorization process. We validate the model on both synthetic and\nreal datasets: the $bAbI$ question answering dataset and the $CNN\\ \\&\\ Daily\\\nNews$ $reading\\ comprehension$ dataset. In our experiments, the models achieved\na State-of-The-Art in the former and competitive results in the latter.","url_abs":"http://arxiv.org/abs/1707.07922v2","url_pdf":"http://arxiv.org/pdf/1707.07922v2.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":"question-dependent-recurrent-entity-network","repo_url":"https://github.com/andreamad8/QDREN","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"form","task_name":"Form"},{"task_slug":"memorization","task_name":"Memorization"},{"task_slug":"question-answering","task_name":"Question Answering"},{"task_slug":"reading-comprehension","task_name":"Reading Comprehension"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}