{"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/narrative-modeling-with-memory-chains-and","title":"Narrative Modeling with Memory Chains and Semantic Supervision","arxiv_id":"1805.06122","date":"2018-05-16","proceeding":"ACL 2018 7","authors":["Fei Liu","Trevor Cohn","Timothy Baldwin"],"abstract":"Story comprehension requires a deep semantic understanding of the narrative,\nmaking it a challenging task. Inspired by previous studies on ROC Story Cloze\nTest, we propose a novel method, tracking various semantic aspects with\nexternal neural memory chains while encouraging each to focus on a particular\nsemantic aspect. Evaluated on the task of story ending prediction, our model\ndemonstrates superior performance to a collection of competitive baselines,\nsetting a new state of the art.","url_abs":"http://arxiv.org/abs/1805.06122v1","url_pdf":"http://arxiv.org/pdf/1805.06122v1.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":"narrative-modeling-with-memory-chains-and","repo_url":"https://github.com/liufly/narrative-modeling","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"cloze-test","task_name":"Cloze Test"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1805.06122","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}