{"id":"https://openalex.org/W2949847757","doi":"https://doi.org/10.18653/v1/p19-1221","title":"Retrieve, Read, Rerank: Towards End-to-End Multi-Document Reading Comprehension","display_name":"Retrieve, Read, Rerank: Towards End-to-End Multi-Document Reading Comprehension","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2949847757","doi":"https://doi.org/10.18653/v1/p19-1221","mag":"2949847757"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p19-1221","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1221","pdf_url":"https://www.aclweb.org/anthology/P19-1221.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 57th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/P19-1221.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101814774","display_name":"Minghao Hu","orcid":"https://orcid.org/0000-0002-5002-3724"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Minghao Hu","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026813633","display_name":"Yuxing Peng","orcid":"https://orcid.org/0000-0002-2192-8129"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxing Peng","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011008665","display_name":"Zhen Huang","orcid":"https://orcid.org/0000-0003-4819-373X"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Huang","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100440903","display_name":"Dongsheng Li","orcid":"https://orcid.org/0000-0001-9743-2034"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongsheng Li","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101814774"],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":null,"apc_paid":null,"fwci":6.0702,"has_fulltext":false,"cited_by_count":54,"citation_normalized_percentile":{"value":0.96976561,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2285","last_page":"2295"},"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":0.9980999827384949,"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":0.9921000003814697,"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":0.8639931678771973},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7590452432632446},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6989426612854004},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.6367111802101135},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.596233606338501},{"id":"https://openalex.org/keywords/end-to-end-principle","display_name":"End-to-end principle","score":0.5945335626602173},{"id":"https://openalex.org/keywords/upstream","display_name":"Upstream (networking)","score":0.5857605934143066},{"id":"https://openalex.org/keywords/reading-comprehension","display_name":"Reading comprehension","score":0.5710229277610779},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4792056977748871},{"id":"https://openalex.org/keywords/reading","display_name":"Reading (process)","score":0.4748777747154236},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4732523560523987},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4706394374370575},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.470465749502182},{"id":"https://openalex.org/keywords/comprehension","display_name":"Comprehension","score":0.42539310455322266},{"id":"https://openalex.org/keywords/downstream","display_name":"Downstream (manufacturing)","score":0.4177696704864502},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.11458218097686768}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8639931678771973},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7590452432632446},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6989426612854004},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.6367111802101135},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.596233606338501},{"id":"https://openalex.org/C74296488","wikidata":"https://www.wikidata.org/wiki/Q2527392","display_name":"End-to-end principle","level":2,"score":0.5945335626602173},{"id":"https://openalex.org/C191172861","wikidata":"https://www.wikidata.org/wiki/Q7899321","display_name":"Upstream (networking)","level":2,"score":0.5857605934143066},{"id":"https://openalex.org/C2778780117","wikidata":"https://www.wikidata.org/wiki/Q3269423","display_name":"Reading comprehension","level":3,"score":0.5710229277610779},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4792056977748871},{"id":"https://openalex.org/C554936623","wikidata":"https://www.wikidata.org/wiki/Q199657","display_name":"Reading (process)","level":2,"score":0.4748777747154236},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4732523560523987},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4706394374370575},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.470465749502182},{"id":"https://openalex.org/C511192102","wikidata":"https://www.wikidata.org/wiki/Q5156948","display_name":"Comprehension","level":2,"score":0.42539310455322266},{"id":"https://openalex.org/C2776207758","wikidata":"https://www.wikidata.org/wiki/Q5303302","display_name":"Downstream (manufacturing)","level":2,"score":0.4177696704864502},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.11458218097686768},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/p19-1221","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1221","pdf_url":"https://www.aclweb.org/anthology/P19-1221.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 57th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/p19-1221","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1221","pdf_url":"https://www.aclweb.org/anthology/P19-1221.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 57th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.8899999856948853,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G4488484741","display_name":null,"funder_award_id":"2018YFB0204300","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2949847757.pdf","grobid_xml":"https://content.openalex.org/works/W2949847757.grobid-xml"},"referenced_works_count":45,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1968245656","https://openalex.org/W2121863487","https://openalex.org/W2468783103","https://openalex.org/W2609826708","https://openalex.org/W2613718673","https://openalex.org/W2624871570","https://openalex.org/W2734823783","https://openalex.org/W2740747242","https://openalex.org/W2741263286","https://openalex.org/W2759477115","https://openalex.org/W2766508367","https://openalex.org/W2769395616","https://openalex.org/W2788448041","https://openalex.org/W2799081691","https://openalex.org/W2896457183","https://openalex.org/W2898858752","https://openalex.org/W2912817604","https://openalex.org/W2912924812","https://openalex.org/W2949428332","https://openalex.org/W2962718483","https://openalex.org/W2962808855","https://openalex.org/W2962985038","https://openalex.org/W2963159735","https://openalex.org/W2963195889","https://openalex.org/W2963246595","https://openalex.org/W2963301888","https://openalex.org/W2963339397","https://openalex.org/W2963341956","https://openalex.org/W2963403868","https://openalex.org/W2963547127","https://openalex.org/W2963564796","https://openalex.org/W2963748441","https://openalex.org/W2963898730","https://openalex.org/W2963969878","https://openalex.org/W2964181805","https://openalex.org/W2964222246","https://openalex.org/W2964348592","https://openalex.org/W3103111734","https://openalex.org/W3121694563","https://openalex.org/W3209042722","https://openalex.org/W4294329082","https://openalex.org/W4295253143","https://openalex.org/W4299280717","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W3113528484","https://openalex.org/W2241146542","https://openalex.org/W3124058258","https://openalex.org/W2209220924","https://openalex.org/W4214653257","https://openalex.org/W1499733765","https://openalex.org/W3125376000","https://openalex.org/W2031986320","https://openalex.org/W4362671650","https://openalex.org/W2117453324"],"abstract_inverted_index":{"This":[0],"paper":[1],"considers":[2],"the":[3,29,33,39,79,115,118,123,132,142],"reading":[4,72],"comprehension":[5],"task":[6],"in":[7],"which":[8],"multiple":[9],"documents":[10],"are":[11],"given":[12],"as":[13],"input.":[14],"Prior":[15],"work":[16],"has":[17],"shown":[18],"that":[19,68,138],"a":[20,63,121],"pipeline":[21,34],"of":[22,152,157],"retriever,":[23],"reader,":[24],"and":[25,46,74,94,145,154],"reranker":[26],"can":[27,126],"improve":[28],"overall":[30],"performance.":[31],"However,":[32],"system":[35],"is":[36,41,47,95],"inefficient":[37],"since":[38],"input":[40],"re-encoded":[42],"within":[43],"each":[44],"module,":[45],"unable":[48],"to":[49,53,77,98,130],"leverage":[50],"upstream":[51,101],"components":[52],"help":[54],"downstream":[55,112],"training.":[56],"In":[57],"this":[58],"work,":[59],"we":[60],"present":[61],"RE3QA,":[62],"unified":[64],"question":[65],"answering":[66],"model":[67,140],"combines":[69],"context":[70,105,133],"retrieving,":[71],"comprehension,":[73],"answer":[75],"reranking":[76],"predict":[78],"final":[80],"answer.":[81],"Unlike":[82],"previous":[83],"pipelined":[84,143],"approaches,":[85],"RE3QA":[86],"shares":[87],"contextualized":[88],"text":[89],"representation":[90],"across":[91],"different":[92],"components,":[93],"carefully":[96],"designed":[97],"use":[99],"high-quality":[100],"outputs":[102],"(e.g.,":[103,114],"retrieved":[104],"or":[106,117],"candidate":[107],"answers)":[108],"for":[109],"directly":[110],"supervising":[111],"modules":[113],"reader":[116],"reranker).":[119],"As":[120],"result,":[122],"whole":[124],"network":[125],"be":[127],"trained":[128],"end-to-end":[129],"avoid":[131],"inconsistency":[134],"problem.":[135],"Experiments":[136],"show":[137],"our":[139],"outperforms":[141],"baseline":[144],"achieves":[146],"state-of-the-art":[147],"results":[148],"on":[149],"two":[150,155],"versions":[151],"TriviaQA":[153],"variants":[156],"SQuAD.":[158]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":16},{"year":2020,"cited_by_count":14},{"year":2019,"cited_by_count":5}],"updated_date":"2026-03-11T14:59:36.786465","created_date":"2025-10-10T00:00:00"}