{"id":"https://openalex.org/W2963301888","doi":"https://doi.org/10.18653/v1/n18-4017","title":"Training a Ranking Function for Open-Domain Question Answering","display_name":"Training a Ranking Function for Open-Domain Question Answering","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2963301888","doi":"https://doi.org/10.18653/v1/n18-4017","mag":"2963301888"},"language":"en","primary_location":{"id":"doi:10.18653/v1/n18-4017","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/n18-4017","pdf_url":"https://www.aclweb.org/anthology/N18-4017.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Student Research Workshop","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/N18-4017.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5084006644","display_name":"Phu Mon Htut","orcid":null},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Phu Mon Htut","raw_affiliation_strings":["Center for Data Science New York University 60 Fifth Avenue New York, NY 10011"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Data Science New York University 60 Fifth Avenue New York, NY 10011","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067390670","display_name":"Samuel Bowman","orcid":"https://orcid.org/0000-0002-1510-174X"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Samuel Bowman","raw_affiliation_strings":["Center for Data Science New York University 60 Fifth Avenue New York, NY 10011","Dept. of Computer Science New York University 60 Fifth Avenue New York, NY 10011","Dept. of Linguistics New York University 10 Washington Place New York, NY 10003"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Data Science New York University 60 Fifth Avenue New York, NY 10011","institution_ids":["https://openalex.org/I57206974"]},{"raw_affiliation_string":"Dept. of Computer Science New York University 60 Fifth Avenue New York, NY 10011","institution_ids":["https://openalex.org/I57206974"]},{"raw_affiliation_string":"Dept. of Linguistics New York University 10 Washington Place New York, NY 10003","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091175785","display_name":"Kyunghyun Cho","orcid":"https://orcid.org/0000-0003-1669-3211"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kyunghyun Cho","raw_affiliation_strings":["Center for Data Science New York University 60 Fifth Avenue New York, NY 10011","Dept. of Computer Science New York University 60 Fifth Avenue New York, NY 10011"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Data Science New York University 60 Fifth Avenue New York, NY 10011","institution_ids":["https://openalex.org/I57206974"]},{"raw_affiliation_string":"Dept. of Computer Science New York University 60 Fifth Avenue New York, NY 10011","institution_ids":["https://openalex.org/I57206974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I57206974"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":41,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"120","last_page":"127"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9904999732971191,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8580183982849121},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.7868983745574951},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7314101457595825},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6629579663276672},{"id":"https://openalex.org/keywords/paragraph","display_name":"Paragraph","score":0.6599070429801941},{"id":"https://openalex.org/keywords/reading","display_name":"Reading (process)","score":0.6230570673942566},{"id":"https://openalex.org/keywords/reading-comprehension","display_name":"Reading comprehension","score":0.5616111755371094},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.5572780966758728},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5455257296562195},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4850741922855377},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.47243839502334595},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.46047985553741455},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.433973491191864},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.12941431999206543},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.1229557991027832}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8580183982849121},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.7868983745574951},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7314101457595825},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6629579663276672},{"id":"https://openalex.org/C2777206241","wikidata":"https://www.wikidata.org/wiki/Q194431","display_name":"Paragraph","level":2,"score":0.6599070429801941},{"id":"https://openalex.org/C554936623","wikidata":"https://www.wikidata.org/wiki/Q199657","display_name":"Reading (process)","level":2,"score":0.6230570673942566},{"id":"https://openalex.org/C2778780117","wikidata":"https://www.wikidata.org/wiki/Q3269423","display_name":"Reading comprehension","level":3,"score":0.5616111755371094},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.5572780966758728},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5455257296562195},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4850741922855377},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.47243839502334595},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.46047985553741455},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.433973491191864},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.12941431999206543},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.1229557991027832},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/n18-4017","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/n18-4017","pdf_url":"https://www.aclweb.org/anthology/N18-4017.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Student Research Workshop","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/n18-4017","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/n18-4017","pdf_url":"https://www.aclweb.org/anthology/N18-4017.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Student Research Workshop","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.8999999761581421}],"awards":[{"id":"https://openalex.org/G1578773895","display_name":null,"funder_award_id":"D3M program","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"}],"funders":[{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"},{"id":"https://openalex.org/F4320309949","display_name":"Canadian Institute for Advanced Research","ror":"https://ror.org/01sdtdd95"},{"id":"https://openalex.org/F4320316083","display_name":"Tencent","ror":"https://ror.org/00hhjss72"},{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"},{"id":"https://openalex.org/F4320332195","display_name":"Samsung","ror":"https://ror.org/04w3jy968"},{"id":"https://openalex.org/F4320332815","display_name":"Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2963301888.pdf","grobid_xml":"https://content.openalex.org/works/W2963301888.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W1486649854","https://openalex.org/W1506013151","https://openalex.org/W1522301498","https://openalex.org/W1544827683","https://openalex.org/W1840435438","https://openalex.org/W2025423507","https://openalex.org/W2095705004","https://openalex.org/W2128407051","https://openalex.org/W2250473257","https://openalex.org/W2250539671","https://openalex.org/W2536015822","https://openalex.org/W2551396370","https://openalex.org/W2734823783","https://openalex.org/W2753329127","https://openalex.org/W2949615363","https://openalex.org/W2962985038","https://openalex.org/W2963241825","https://openalex.org/W2963344337","https://openalex.org/W2963748441","https://openalex.org/W2963846996","https://openalex.org/W2963907629","https://openalex.org/W2963918774","https://openalex.org/W2964121744","https://openalex.org/W4294329082"],"related_works":["https://openalex.org/W2377059580","https://openalex.org/W4200355488","https://openalex.org/W127000293","https://openalex.org/W3215892509","https://openalex.org/W2928616779","https://openalex.org/W2412592434","https://openalex.org/W2010523086","https://openalex.org/W4244602709","https://openalex.org/W594987446","https://openalex.org/W2012131063"],"abstract_inverted_index":{"In":[0,15,99],"recent":[1],"years,":[2],"there":[3],"have":[4],"been":[5],"amazing":[6],"advances":[7],"in":[8,42,140],"deep":[9],"learning":[10],"methods":[11],"for":[12],"machine":[13,16,19,35,56,66],"reading.":[14],"reading,":[17],"the":[18,24,27,33,88,94,97,120,129],"reader":[20],"has":[21,58],"to":[22,61,68,78,86,96,111,122],"extract":[23],"answer":[25,95,121],"from":[26],"given":[28,124],"ground":[29],"truth":[30],"paragraph.":[31],"Recently,":[32],"stateof-the-art":[34],"reading":[36,47,57,67,79],"models":[37],"achieve":[38],"human":[39],"level":[40,137],"performance":[41],"SQuAD":[43],"which":[44],"is":[45,84],"a":[46,123],"comprehension-style":[48,80],"question":[49],"answering":[50],"(QA)":[51],"task.":[52],"The":[53],"success":[54],"of":[55,90,118,132],"inspired":[59],"researchers":[60],"combine":[62],"information":[63],"retrieval":[64],"with":[65],"tackle":[69],"open-domain":[70,141],"QA.":[71,142],"However,":[72],"these":[73],"systems":[74],"perform":[75],"poorly":[76],"compared":[77],"QA":[81],"because":[82],"it":[83],"difficult":[85],"retrieve":[87],"pieces":[89],"paragraphs":[91],"that":[92,108],"contain":[93],"question.":[98,125],"this":[100],"study,":[101],"we":[102,127],"propose":[103],"two":[104],"neural":[105],"network":[106],"rankers":[107],"assign":[109],"scores":[110],"different":[112],"passages":[113],"based":[114],"on":[115],"their":[116],"likelihood":[117],"containing":[119],"Additionally,":[126],"analyze":[128],"relative":[130],"importance":[131],"semantic":[133],"similarity":[134],"and":[135],"word":[136],"relevance":[138],"matching":[139]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":14},{"year":2018,"cited_by_count":2}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}