{"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/character-level-intra-attention-network-for","title":"Character-level Intra Attention Network for Natural Language Inference","arxiv_id":"1707.07469","date":"2017-07-24","proceeding":"WS 2017 9","authors":["Han Yang","Marta R. Costa-jussà","José A. R. Fonollosa"],"abstract":"Natural language inference (NLI) is a central problem in language\nunderstanding. End-to-end artificial neural networks have reached\nstate-of-the-art performance in NLI field recently.\n  In this paper, we propose Character-level Intra Attention Network (CIAN) for\nthe NLI task. In our model, we use the character-level convolutional network to\nreplace the standard word embedding layer, and we use the intra attention to\ncapture the intra-sentence semantics. The proposed CIAN model provides improved\nresults based on a newly published MNLI corpus.","url_abs":"http://arxiv.org/abs/1707.07469v1","url_pdf":"http://arxiv.org/pdf/1707.07469v1.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":"character-level-intra-attention-network-for","repo_url":"https://github.com/yanghanxy/CIAN","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"natural-language-inference","task_name":"Natural Language Inference"},{"task_slug":"sentence","task_name":"Sentence"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}