{"url":"/method/sirm","slug":"sirm","name":"SIRM","full_name":"Skim and Intensive Reading Model","full_name_withheld":false,"description_markdown":"**Skim and Intensive Reading Model**, or **SIRM**, is a deep neural network for figuring out implied textual meaning. It consists of two main components, namely the skim reading component and intensive reading component. N-gram features are quickly extracted from the skim reading component, which is a combination of several convolutional neural networks, as skim (entire) information. An intensive reading component enables a hierarchical investigation for both local (sentence) and global (paragraph) representation, which encapsulates the current embedding and the contextual information with a dense connection.","description_state":"present","introduced_year":null,"introduced_by":{"title":"Read Beyond the Lines: Understanding the Implied Textual Meaning via a Skim and Intensive Reading Model","paper":"/paper/read-beyond-the-lines-understanding-the","first_author":"Guoxiu He","n_authors":7,"url_abs":null,"archive_paper_url":"https://paperswithcode.com/paper/read-beyond-the-lines-understanding-the"},"source":{"url":"https://arxiv.org/abs/2001.00572v2","title":"Read Beyond the Lines: Understanding the Implied Textual Meaning via a Skim and Intensive Reading Model","url_on_a_paper_host":true},"code_snippet_url":null,"code_snippet_url_on_a_code_host":false,"categories":[{"area":"Natural Language Processing","area_id":"natural-language-processing","collection":"Textual Meaning","url":"/methods/category/textual-meaning","pwc_aliases":[]}],"n_papers_tagged":2,"archive_num_papers":2,"papers_newest_first":[{"paper":null,"title":"DFREC: DeepFake Identity Recovery Based on Identity-aware Masked Autoencoder","date":"2024-12-10","arxiv_id":"2412.07260","n_code_links":0,"syntology":null},{"paper":"/paper/read-beyond-the-lines-understanding-the","title":"Read Beyond the Lines: Understanding the Implied Textual Meaning via a Skim and Intensive Reading Model","date":"2020-01-03","arxiv_id":"2001.00572","n_code_links":0,"syntology":null}],"papers_shown":2,"tasks":[{"task":"/task/face-swapping","name":"Face Swapping","papers":1},{"task":"/task/reading-comprehension","name":"Reading Comprehension","papers":1},{"task":"/task/sensitivity","name":"Sensitivity","papers":1},{"task":"/task/sentence","name":"Sentence","papers":1}],"tasks_shown":4,"n_tasks":4,"usage_by_year":[{"year":"2020","papers":1},{"year":"2024","papers":1}],"row_source":"methods_table","archive":{"source":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","archive_url":"https://paperswithcode.com/method/sirm"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}