{"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/two-stage-synthesis-networks-for-transfer","title":"Two-Stage Synthesis Networks for Transfer Learning in Machine Comprehension","arxiv_id":"1706.09789","date":"2017-06-29","proceeding":"EMNLP 2017 9","authors":["David Golub","Po-Sen Huang","Xiaodong He","Li Deng"],"abstract":"We develop a technique for transfer learning in machine comprehension (MC)\nusing a novel two-stage synthesis network (SynNet). Given a high-performing MC\nmodel in one domain, our technique aims to answer questions about documents in\nanother domain, where we use no labeled data of question-answer pairs. Using\nthe proposed SynNet with a pretrained model from the SQuAD dataset on the\nchallenging NewsQA dataset, we achieve an F1 measure of 44.3% with a single\nmodel and 46.6% with an ensemble, approaching performance of in-domain models\n(F1 measure of 50.0%) and outperforming the out-of-domain baseline of 7.6%,\nwithout use of provided annotations.","url_abs":"http://arxiv.org/abs/1706.09789v3","url_pdf":"http://arxiv.org/pdf/1706.09789v3.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":"two-stage-synthesis-networks-for-transfer","repo_url":"https://github.com/davidgolub/QuestionGeneration","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"NOASSERTION"}},{"paper_slug":"two-stage-synthesis-networks-for-transfer","repo_url":"https://github.com/lucasgnz/question_answering","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"reading-comprehension","task_name":"Reading Comprehension"},{"task_slug":"transfer-learning","task_name":"Transfer Learning"},{"task_slug":"two","task_name":"Vocal Bursts Valence Prediction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1706.09789","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}