{"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/automatic-text-scoring-using-neural-networks","title":"Automatic Text Scoring Using Neural Networks","arxiv_id":"1606.04289","date":"2016-06-14","proceeding":"ACL 2016 8","authors":["Dimitrios Alikaniotis","Helen Yannakoudakis","Marek Rei"],"abstract":"Automated Text Scoring (ATS) provides a cost-effective and consistent\nalternative to human marking. However, in order to achieve good performance,\nthe predictive features of the system need to be manually engineered by human\nexperts. We introduce a model that forms word representations by learning the\nextent to which specific words contribute to the text's score. Using Long-Short\nTerm Memory networks to represent the meaning of texts, we demonstrate that a\nfully automated framework is able to achieve excellent results over similar\napproaches. In an attempt to make our results more interpretable, and inspired\nby recent advances in visualizing neural networks, we introduce a novel method\nfor identifying the regions of the text that the model has found more\ndiscriminative.","url_abs":"http://arxiv.org/abs/1606.04289v2","url_pdf":"http://arxiv.org/pdf/1606.04289v2.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":"automatic-text-scoring-using-neural-networks","repo_url":"https://github.com/adityasharma1234/answersheetcorrection","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"automatic-text-scoring-using-neural-networks","repo_url":"https://github.com/mankadronit/Automated-Essay--Scoring","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"automatic-text-scoring-using-neural-networks","repo_url":"https://github.com/MindSpore-paper-code-3/code1/tree/main/ats","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"mindspore","reach":null}],"tasks":[],"methods":[{"method_slug":"1-bit-adam","method_name":"1-bit Adam"},{"method_slug":"adam","method_name":"Adam"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1606.04289","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}