{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,12]],"date-time":"2024-09-12T04:42:13Z","timestamp":1726116133378},"publisher-location":"Cham","reference-count":31,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030698850"},{"type":"electronic","value":"9783030698867"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-69886-7_12","type":"book-chapter","created":{"date-parts":[[2021,2,19]],"date-time":"2021-02-19T16:18:56Z","timestamp":1613751536000},"page":"138-151","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Challenge Closed-Book Science Exam: A Meta-Learning Based Question Answering System"],"prefix":"10.1007","author":[{"given":"Xinyue","family":"Zheng","sequence":"first","affiliation":[]},{"given":"Peng","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Qigang","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Zhongchao","family":"Shi","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,2,20]]},"reference":[{"key":"12_CR1","doi-asserted-by":"crossref","unstructured":"Clark, P.: Elementary school science and math tests as a driver for AI: take the aristo challenge! In: Twenty-Seventh IAAI Conference (2015)","DOI":"10.1609\/aaai.v29i2.19066"},{"issue":"1","key":"12_CR2","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1609\/aimag.v37i1.2636","volume":"37","author":"P Clark","year":"2016","unstructured":"Clark, P., Etzioni, O.: My computer is an honor student-but how intelligent is it? Standardized tests as a measure of AI. AI Mag. 37(1), 5\u201312 (2016)","journal-title":"AI Mag."},{"key":"12_CR3","unstructured":"Clark, P., et al.: From\u2018F\u2019 to \u2018A\u2019 on the ny regents science exams: an overview of the aristo project. arXiv preprint arXiv:1909.01958 (2019)"},{"key":"12_CR4","doi-asserted-by":"crossref","unstructured":"Clark, P., Harrison, P., Balasubramanian, N.: A study of the knowledge base requirements for passing an elementary science test. In: Proceedings of the 2013 workshop on Automated knowledge base construction, pp. 37\u201342. ACM (2013)","DOI":"10.1145\/2509558.2509565"},{"key":"12_CR5","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: Bert: pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)"},{"key":"12_CR6","unstructured":"Dua, D., Wang, Y., Dasigi, P., Stanovsky, G., Singh, S., Gardner, M.: Drop: a reading comprehension benchmark requiring discrete reasoning over paragraphs. arXiv preprint arXiv:1903.00161 (2019)"},{"key":"12_CR7","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1146\/annurev.psych.59.103006.093629","volume":"59","author":"JSBT Evans","year":"2008","unstructured":"Evans, J.S.B.T.: Dual-processing accounts of reasoning, judgment, and social cognition. Annu. Rev. Psychol. 59, 255\u2013278 (2008)","journal-title":"Annu. Rev. Psychol."},{"key":"12_CR8","unstructured":"Finn, C., Abbeel, P., Levine, S.: Model-agnostic meta-learning for fast adaptation of deep networks. In: Proceedings of the 34th International Conference on Machine Learning-Volume 70, pp. 1126\u20131135. JMLR. org (2017)"},{"key":"12_CR9","unstructured":"Godea, A., Nielsen, R.: Annotating educational questions for student response analysis. In: Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018) (2018)"},{"key":"12_CR10","unstructured":"Graves, A., Wayne, G., Danihelka, I.: Neural turing machines. arXiv preprint arXiv:1410.5401 (2014)"},{"key":"12_CR11","doi-asserted-by":"crossref","unstructured":"Gu, J., Wang, Y., Chen, Y., Cho, K., Li, V.O.: Meta-learning for low-resource neural machine translation. arXiv preprint arXiv:1808.08437 (2018)","DOI":"10.18653\/v1\/D18-1398"},{"key":"12_CR12","doi-asserted-by":"crossref","unstructured":"Hovy, E., Gerber, L., Hermjakob, U., Lin, C.Y., Ravichandran, D.: Toward semantics-based answer pinpointing. In: Proceedings of the First International Conference on Human Language Technology Research (2001)","DOI":"10.3115\/1072133.1072221"},{"issue":"2","key":"12_CR13","doi-asserted-by":"publisher","first-page":"407","DOI":"10.1162\/COLI_a_00287","volume":"43","author":"P Jansen","year":"2017","unstructured":"Jansen, P., Sharp, R., Surdeanu, M., Clark, P.: Framing qa as building and ranking intersentence answer justifications. Comput. Linguist. 43(2), 407\u2013449 (2017)","journal-title":"Comput. Linguist."},{"key":"12_CR14","unstructured":"Jansen, P.A., Wainwright, E., Marmorstein, S., Morrison, C.T.: Worldtree: a corpus of explanation graphs for elementary science questions supporting multi-hop inference. arXiv preprint arXiv:1802.03052 (2018)"},{"key":"12_CR15","doi-asserted-by":"crossref","unstructured":"Khashabi, D., Khot, T., Sabharwal, A., Roth, D.: Question answering as global reasoning over semantic abstractions. In: Thirty-Second AAAI Conference on Artificial Intelligence (2018)","DOI":"10.1609\/aaai.v32i1.11574"},{"key":"12_CR16","doi-asserted-by":"crossref","unstructured":"Lai, G., Xie, Q., Liu, H., Yang, Y., Hovy, E.: Race: large-scale reading comprehension dataset from examinations. arXiv preprint arXiv:1704.04683 (2017)","DOI":"10.18653\/v1\/D17-1082"},{"key":"12_CR17","unstructured":"Liu, Y., et al.: Roberta: a robustly optimized bert pretraining approach. arXiv preprint arXiv:1907.11692 (2019)"},{"key":"12_CR18","volume-title":"Society of Mind","author":"M Minsky","year":"1988","unstructured":"Minsky, M.: Society of Mind. Simon and Schuster, New York (1988)"},{"key":"12_CR19","unstructured":"Mishra, N., Rohaninejad, M., Chen, X., Abbeel, P.: A simple neural attentive meta-learner (2017)"},{"key":"12_CR20","unstructured":"Munkhdalai, T., Yu, H.: Meta networks. In: Proceedings of the 34th International Conference on Machine Learning-Volume 70, pp. 2554\u20132563. JMLR. org (2017)"},{"key":"12_CR21","unstructured":"Musa, R., et al.: Answering science exam questions using query reformulation with background knowledge (2018)"},{"key":"12_CR22","unstructured":"Nichol, A., Schulman, J.: Reptile: a scalable metalearning algorithm, vol. 2. arXiv preprint arXiv:1803.02999 (2018)"},{"key":"12_CR23","doi-asserted-by":"crossref","unstructured":"Pan, X., Sun, K., Yu, D., Ji, H., Yu, D.: Improving question answering with external knowledge. arXiv preprint arXiv:1902.00993 (2019)","DOI":"10.18653\/v1\/D19-5804"},{"key":"12_CR24","unstructured":"Peters, M.E., et al.: Deep contextualized word representations. arXiv preprint arXiv:1802.05365 (2018)"},{"key":"12_CR25","doi-asserted-by":"crossref","unstructured":"Qiu, Y., Frei, H.P.: Concept based query expansion. In: Proceedings of the 16th annual international ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 160\u2013169. ACM (1993)","DOI":"10.1145\/160688.160713"},{"key":"12_CR26","doi-asserted-by":"crossref","unstructured":"Ran, Q., Lin, Y., Li, P., Zhou, J., Liu, Z.: Numnet: machine reading comprehension with numerical reasoning. arXiv preprint arXiv:1910.06701 (2019)","DOI":"10.18653\/v1\/D19-1251"},{"key":"12_CR27","unstructured":"Roberts, K., et al., K.: Automatically classifying question types for consumer health questions. In: AMIA Annual Symposium Proceedings, vol. 2014, p. 1018. American Medical Informatics Association (2014)"},{"key":"12_CR28","unstructured":"Santoro, A., Bartunov, S., Botvinick, M., Wierstra, D., Lillicrap, T.: One-shot learning with memory-augmented neural networks. arXiv preprint arXiv:1605.06065 (2016)"},{"key":"12_CR29","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1037\/0033-2909.119.1.3","volume":"119","author":"SA Sloman","year":"1996","unstructured":"Sloman, S.A.: The empirical case for two systems of reasoning. Psychol. Bull. 119, 3 (1996)","journal-title":"Psychol. Bull."},{"key":"12_CR30","doi-asserted-by":"crossref","unstructured":"Vig, J.: A multiscale visualization of attention in the transformer model. arXiv preprint arXiv:1906.05714 (2019)","DOI":"10.18653\/v1\/P19-3007"},{"key":"12_CR31","unstructured":"Xu, D., et al., J.: Multi-class hierarchical question classification for multiple choice science exams. arXiv preprint arXiv:1908.05441 (2019)"}],"container-title":["Lecture Notes in Computer Science","Knowledge Management and Acquisition for Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-69886-7_12","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,18]],"date-time":"2022-12-18T02:17:36Z","timestamp":1671329856000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-69886-7_12"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030698850","9783030698867"],"references-count":31,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-69886-7_12","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"20 February 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PKAW","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Pacific Rim Knowledge Acquisition Workshop","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Yokohama","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Japan","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 January 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 January 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"pkaw2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.pkaw.org\/pkaw2020\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"28","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"10","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"5","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"36% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2,5","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}