{"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/pairwise-word-interaction-modeling-with-deep","title":"Pairwise Word Interaction Modeling with Deep Neural Networks for Semantic Similarity Measurement","arxiv_id":null,"date":"2016-06-01","proceeding":"NAACL 2016 6","authors":["Hua He","Jimmy Lin"],"abstract":"","url_abs":"https://aclanthology.org/N16-1108","url_pdf":"https://aclanthology.org/N16-1108.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":[],"tasks":[{"task_slug":"answer-selection","task_name":"Answer Selection"},{"task_slug":"paraphrase-generation","task_name":"Paraphrase Generation"},{"task_slug":"question-answering","task_name":"Question Answering"},{"task_slug":"semantic-similarity","task_name":"Semantic Similarity"},{"task_slug":"semantic-textual-similarity","task_name":"Semantic Textual Similarity"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/question-answering-on-trecqa","task":"Question Answering","dataset":"TrecQA","model":"PWIN","rank_in_archive_order":11,"of":13,"metrics":{"MAP":"0.7588","MRR":"0.8219"},"uses_additional_data":false},{"leaderboard":"/sota/question-answering-on-wikiqa","task":"Question Answering","dataset":"WikiQA","model":"PWIM","rank_in_archive_order":11,"of":25,"metrics":{"MAP":"0.7090","MRR":"0.7234"},"uses_additional_data":false}],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}