{"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/natural-language-inference-over-interaction","title":"Natural Language Inference over Interaction Space: ICLR 2018 Reproducibility Report","arxiv_id":"1802.03198","date":"2018-02-09","proceeding":null,"authors":["Martin Mirakyan","Karen Hambardzumyan","Hrant Khachatrian"],"abstract":"We have tried to reproduce the results of the paper \"Natural Language\nInference over Interaction Space\" submitted to ICLR 2018 conference as part of\nthe ICLR 2018 Reproducibility Challenge. Initially, we were not aware that the\ncode was available, so we started to implement the network from scratch. We\nhave evaluated our version of the model on Stanford NLI dataset and reached\n86.38% accuracy on the test set, while the paper claims 88.0% accuracy. The\nmain difference, as we understand it, comes from the optimizers and the way\nmodel selection is performed.","url_abs":"http://arxiv.org/abs/1802.03198v1","url_pdf":"http://arxiv.org/pdf/1802.03198v1.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":"natural-language-inference-over-interaction","repo_url":"https://github.com/YerevaNN/DIIN-in-Keras","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"model-selection","task_name":"Model Selection"},{"task_slug":"natural-language-inference","task_name":"Natural Language Inference"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}