{"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/modelling-sentence-pairs-with-tree-structured","title":"Modelling Sentence Pairs with Tree-structured Attentive Encoder","arxiv_id":"1610.02806","date":"2016-10-10","proceeding":"COLING 2016 12","authors":["Yao Zhou","Cong Liu","Yan Pan"],"abstract":"We describe an attentive encoder that combines tree-structured recursive\nneural networks and sequential recurrent neural networks for modelling sentence\npairs. Since existing attentive models exert attention on the sequential\nstructure, we propose a way to incorporate attention into the tree topology.\nSpecially, given a pair of sentences, our attentive encoder uses the\nrepresentation of one sentence, which generated via an RNN, to guide the\nstructural encoding of the other sentence on the dependency parse tree. We\nevaluate the proposed attentive encoder on three tasks: semantic similarity,\nparaphrase identification and true-false question selection. Experimental\nresults show that our encoder outperforms all baselines and achieves\nstate-of-the-art results on two tasks.","url_abs":"http://arxiv.org/abs/1610.02806v1","url_pdf":"http://arxiv.org/pdf/1610.02806v1.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":"modelling-sentence-pairs-with-tree-structured","repo_url":"https://github.com/yoosan/sentpair","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"paraphrase-identification","task_name":"Paraphrase Identification"},{"task_slug":"question-selection","task_name":"Question Selection"},{"task_slug":"semantic-similarity","task_name":"Semantic Similarity"},{"task_slug":"semantic-textual-similarity","task_name":"Semantic Textual Similarity"},{"task_slug":"sentence","task_name":"Sentence"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1610.02806","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}