{"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/deep-learning-for-answer-sentence-selection","title":"Deep Learning for Answer Sentence Selection","arxiv_id":"1412.1632","date":"2014-12-04","proceeding":null,"authors":["Lei Yu","Karl Moritz Hermann","Phil Blunsom","Stephen Pulman"],"abstract":"Answer sentence selection is the task of identifying sentences that contain\nthe answer to a given question. This is an important problem in its own right\nas well as in the larger context of open domain question answering. We propose\na novel approach to solving this task via means of distributed representations,\nand learn to match questions with answers by considering their semantic\nencoding. This contrasts prior work on this task, which typically relies on\nclassifiers with large numbers of hand-crafted syntactic and semantic features\nand various external resources. Our approach does not require any feature\nengineering nor does it involve specialist linguistic data, making this model\neasily applicable to a wide range of domains and languages. Experimental\nresults on a standard benchmark dataset from TREC demonstrate that---despite\nits simplicity---our model matches state of the art performance on the answer\nsentence selection task.","url_abs":"http://arxiv.org/abs/1412.1632v1","url_pdf":"http://arxiv.org/pdf/1412.1632v1.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":"deep-learning-for-answer-sentence-selection","repo_url":"https://github.com/brmson/dataset-sts","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"deep-learning-for-answer-sentence-selection","repo_url":"https://github.com/umutguneri/Question-Answering-Assistant","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}}],"tasks":[{"task_slug":"deep-learning","task_name":"Deep Learning"},{"task_slug":"feature-engineering","task_name":"Feature Engineering"},{"task_slug":"open-domain-question-answering","task_name":"Open-Domain Question Answering"},{"task_slug":"question-answering","task_name":"Question Answering"},{"task_slug":"sentence","task_name":"Sentence"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/question-answering-on-qasent","task":"Question Answering","dataset":"QASent","model":"Bigram-CNN (lexical overlap + dist output)","rank_in_archive_order":3,"of":7,"metrics":{"MAP":"0.7113","MRR":"0.7846"},"uses_additional_data":false},{"leaderboard":"/sota/question-answering-on-qasent","task":"Question Answering","dataset":"QASent","model":"Bigram-CNN","rank_in_archive_order":6,"of":7,"metrics":{"MAP":"0.5693","MRR":"0.6613"},"uses_additional_data":false},{"leaderboard":"/sota/question-answering-on-trecqa","task":"Question Answering","dataset":"TrecQA","model":"CNN","rank_in_archive_order":13,"of":13,"metrics":{"MAP":"0.711","MRR":"0.785"},"uses_additional_data":false},{"leaderboard":"/sota/question-answering-on-wikiqa","task":"Question Answering","dataset":"WikiQA","model":"Bigram-CNN (lexical overlap + dist output)","rank_in_archive_order":21,"of":25,"metrics":{"MAP":"0.6520","MRR":"0.6652"},"uses_additional_data":false},{"leaderboard":"/sota/question-answering-on-wikiqa","task":"Question Answering","dataset":"WikiQA","model":"Bigram-CNN","rank_in_archive_order":23,"of":25,"metrics":{"MAP":"0.6190","MRR":"0.6281"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1412.1632","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}