{"url":"/method/autoint","slug":"autoint","name":"AutoInt","full_name":"AutoInt","full_name_withheld":false,"description_markdown":"**AutoInt** is a deep tabular learning method that models high-order feature interactions of input features. AutoInt can be applied to both numerical and categorical input features. Specifically, both the numerical and categorical features are mapped into the same low-dimensional space. Afterwards, a multi-head self-attentive neural network with residual connections is proposed to explicitly model the feature interactions in the low-dimensional space. With different layers of the multi-head self-attentive neural networks, different orders of feature combinations of input features can be modeled.","description_state":"present","introduced_year":null,"introduced_by":{"title":null,"paper":null,"first_author":null,"n_authors":0,"url_abs":null,"archive_paper_url":null},"source":{"url":"https://arxiv.org/abs/1810.11921v2","title":"AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks","url_on_a_paper_host":true},"code_snippet_url":null,"code_snippet_url_on_a_code_host":false,"categories":[{"area":"General","area_id":"general","collection":"Deep Tabular Learning","url":"/methods/category/deep-tabular-learning","pwc_aliases":[]}],"n_papers_tagged":2,"archive_num_papers":null,"papers_newest_first":[{"paper":null,"title":"Leaf-FM: A Learnable Feature Generation Factorization Machine for Click-Through Rate Prediction","date":"2021-07-26","arxiv_id":"2107.12024","n_code_links":0,"syntology":null},{"paper":"/paper/autoint-automatic-feature-interaction","title":"AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks","date":"2018-10-29","arxiv_id":"1810.11921","n_code_links":19,"syntology":{"ran":0,"of":3,"unverified":3,"pointer_only":0}}],"papers_shown":2,"tasks":[{"task":"/task/click-through-rate-prediction","name":"Click-Through Rate Prediction","papers":2},{"task":"/task/recommendation-systems","name":"Recommendation Systems","papers":2},{"task":"/task/feature-engineering","name":"Feature Engineering","papers":1}],"tasks_shown":3,"n_tasks":3,"usage_by_year":[{"year":"2018","papers":1},{"year":"2021","papers":1}],"row_source":"embedded","archive":{"source":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","archive_url":"https://paperswithcode.com/method/autoint"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}