{"id":"https://openalex.org/W3154407361","doi":"https://doi.org/10.1145/3404835.3463085","title":"Synthetic Target Domain Supervision for Open Retrieval QA","display_name":"Synthetic Target Domain Supervision for Open Retrieval QA","publication_year":2021,"publication_date":"2021-07-11","ids":{"openalex":"https://openalex.org/W3154407361","doi":"https://doi.org/10.1145/3404835.3463085","mag":"3154407361"},"language":"en","primary_location":{"id":"doi:10.1145/3404835.3463085","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3404835.3463085","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103240632","display_name":"Revanth Gangi Reddy","orcid":"https://orcid.org/0009-0009-8915-579X"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Revanth Gangi Reddy","raw_affiliation_strings":["University of Illinois at Urbana Champaign, Champaign, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois at Urbana Champaign, Champaign, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041684488","display_name":"Bhavani Iyer","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bhavani Iyer","raw_affiliation_strings":["IBM Research AI, Yorktown Heights, NY, USA"],"affiliations":[{"raw_affiliation_string":"IBM Research AI, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055236060","display_name":"Md Arafat Sultan","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Md Arafat Sultan","raw_affiliation_strings":["IBM Research AI, Yorktown Heights, NY, USA"],"affiliations":[{"raw_affiliation_string":"IBM Research AI, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100451786","display_name":"Rong Zhang","orcid":"https://orcid.org/0000-0002-2288-2847"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rong Zhang","raw_affiliation_strings":["IBM Research AI, Yorktown Heights, NY, USA"],"affiliations":[{"raw_affiliation_string":"IBM Research AI, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112335036","display_name":"Avirup Sil","orcid":"https://orcid.org/0000-0002-4753-3221"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Avirup Sil","raw_affiliation_strings":["IBM Research AI, Yorktown Heights, NY, USA"],"affiliations":[{"raw_affiliation_string":"IBM Research AI, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112539661","display_name":"Vittorio Castelli","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vittorio Castelli","raw_affiliation_strings":["IBM Research AI, Yorktown Heights, NY, USA"],"affiliations":[{"raw_affiliation_string":"IBM Research AI, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113515054","display_name":"Radu Florian","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Radu Florian","raw_affiliation_strings":["IBM Research AI, Yorktown Heights, NY, USA"],"affiliations":[{"raw_affiliation_string":"IBM Research AI, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043396055","display_name":"Salim Roukos","orcid":"https://orcid.org/0000-0003-2140-4349"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Salim Roukos","raw_affiliation_strings":["IBM Research AI, Yorktown Heights, NY, USA"],"affiliations":[{"raw_affiliation_string":"IBM Research AI, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I1341412227"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5103240632"],"corresponding_institution_ids":["https://openalex.org/I157725225"],"apc_list":null,"apc_paid":null,"fwci":0.4079,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.67123536,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1793","last_page":"1797"},"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":0.9958999752998352,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9939000010490417,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.8048944473266602},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.7195857167243958},{"id":"https://openalex.org/keywords/open-domain","display_name":"Open domain","score":0.7161780595779419},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5677664875984192},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.5337425470352173},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.42347294092178345},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.40513795614242554},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3913191556930542},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07157149910926819}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8048944473266602},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.7195857167243958},{"id":"https://openalex.org/C2993776861","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Open domain","level":3,"score":0.7161780595779419},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5677664875984192},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.5337425470352173},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.42347294092178345},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.40513795614242554},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3913191556930542},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07157149910926819},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3404835.3463085","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3404835.3463085","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4699999988079071,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1801866228","https://openalex.org/W2111362445","https://openalex.org/W2155482025","https://openalex.org/W2252136820","https://openalex.org/W2296024507","https://openalex.org/W2771472444","https://openalex.org/W2892181857","https://openalex.org/W2896457183","https://openalex.org/W2911489562","https://openalex.org/W2912172494","https://openalex.org/W2912924812","https://openalex.org/W2914389667","https://openalex.org/W2949849869","https://openalex.org/W2950729111","https://openalex.org/W2951434086","https://openalex.org/W2952989203","https://openalex.org/W2962985038","https://openalex.org/W2963175042","https://openalex.org/W2963339397","https://openalex.org/W2963488798","https://openalex.org/W2963716420","https://openalex.org/W2963748441","https://openalex.org/W2970771982","https://openalex.org/W2996287690","https://openalex.org/W2998702515","https://openalex.org/W3020786614","https://openalex.org/W3021397474","https://openalex.org/W3034238904","https://openalex.org/W3034987253","https://openalex.org/W3034999214","https://openalex.org/W3035621030","https://openalex.org/W3047636089","https://openalex.org/W3104330316","https://openalex.org/W4252076394","https://openalex.org/W6600424091","https://openalex.org/W6600763685"],"related_works":["https://openalex.org/W2951097643","https://openalex.org/W2391533720","https://openalex.org/W4309395021","https://openalex.org/W4307481286","https://openalex.org/W3215363805","https://openalex.org/W204133468","https://openalex.org/W2991310128","https://openalex.org/W2395174199","https://openalex.org/W4226441484","https://openalex.org/W2516703895"],"abstract_inverted_index":{"Neural":[0],"passage":[1],"retrieval":[2,11,29,129],"is":[3],"a":[4,77,93,103],"new":[5],"and":[6,32,39,114],"promising":[7],"approach":[8],"in":[9,47,98,107],"open":[10,26,128],"question":[12],"answering.":[13],"In":[14,80],"this":[15,48,83],"work,":[16],"we":[17,60,69],"stress-test":[18],"the":[19,120,125],"Dense":[20],"Passage":[21],"Retriever":[22],"(DPR)---a":[23],"state-of-the-art":[24],"(SOTA)":[25],"domain":[27,58,74,89],"neural":[28],"model---on":[30],"closed":[31],"specialized":[33],"target":[34,73,88],"domains":[35],"such":[36],"as":[37],"COVID-19,":[38],"find":[40],"that":[41],"it":[42,102],"lags":[43],"behind":[44],"standard":[45],"BM25":[46,97,113],"important":[49],"real-world":[50],"setting.":[51],"To":[52],"make":[53],"DPR":[54,92,117],"more":[55,104],"robust":[56],"under":[57],"shift,":[59],"explore":[61],"its":[62],"fine-tuning":[63],"with":[64],"synthetic":[65],"training":[66],"examples,":[67],"which":[68],"generate":[70],"from":[71],"unlabeled":[72],"text":[75],"using":[76],"text-to-text":[78],"generator.":[79],"our":[81,115],"experiments,":[82],"noisy":[84],"but":[85],"fully":[86],"automated":[87],"supervision":[90],"gives":[91],"sizable":[94],"advantage":[95],"over":[96],"out-of-domain":[99,133],"settings,":[100],"making":[101],"viable":[105],"model":[106,118],"practice.":[108],"Finally,":[109],"an":[110],"ensemble":[111],"of":[112],"improved":[116],"yields":[119],"best":[121],"results,":[122],"further":[123],"pushing":[124],"SOTA":[126],"for":[127],"QA":[130],"on":[131],"multiple":[132],"test":[134],"sets.":[135]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}