{"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/representation-learning-for-information","title":"Representation Learning for Information Extraction from Form-like Documents","arxiv_id":null,"date":"2020-06-15","proceeding":"ACL 2020 6","authors":["Bodhisattwa Majumder","Navneet Potti","Sandeep Tata","James B. Wendt","Qi Zhao","Marc Najork"],"abstract":"We propose a novel approach using representation learning for tackling the problem of extracting structured information from form-like\r\ndocument images. We propose an extraction\r\nsystem that uses knowledge of the types of the\r\ntarget fields to generate extraction candidates,\r\nand a neural network architecture that learns a\r\ndense representation of each candidate based\r\non neighboring words in the document. These\r\nlearned representations are not only useful in\r\nsolving the extraction task for unseen document templates from two different domains,\r\nbut are also interpretable, as we show using\r\nloss cases.","url_abs":"https://research.google/pubs/pub49122/","url_pdf":"https://storage.googleapis.com/pub-tools-public-publication-data/pdf/59f3bb33216eae711b36f3d8b3ee3cc67058803f.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":"representation-learning-for-information","repo_url":"https://github.com/Praneet9/Representation-Learning-for-Information-Extraction","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"form","task_name":"Form"},{"task_slug":"representation-learning","task_name":"Representation Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}