{"id":"https://openalex.org/W3035183674","doi":"https://doi.org/10.1145/3397271.3401266","title":"Reranking for Efficient Transformer-based Answer Selection","display_name":"Reranking for Efficient Transformer-based Answer Selection","publication_year":2020,"publication_date":"2020-07-25","ids":{"openalex":"https://openalex.org/W3035183674","doi":"https://doi.org/10.1145/3397271.3401266","mag":"3035183674"},"language":"en","primary_location":{"id":"doi:10.1145/3397271.3401266","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3397271.3401266","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3397271.3401266","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3397271.3401266","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5057951533","display_name":"Yoshitomo Matsubara","orcid":"https://orcid.org/0000-0002-5620-0760"},"institutions":[{"id":"https://openalex.org/I204250578","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771","country_code":"US","type":"education","lineage":["https://openalex.org/I204250578"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yoshitomo Matsubara","raw_affiliation_strings":["University of California, Irvine, Irvine, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California, Irvine, Irvine, CA, USA","institution_ids":["https://openalex.org/I204250578"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056497976","display_name":"Thuy Vu","orcid":"https://orcid.org/0000-0003-1056-6975"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Thuy Vu","raw_affiliation_strings":["Amazon Alexa, Manhattan Beach, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Amazon Alexa, Manhattan Beach, CA, USA","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056376686","display_name":"Alessandro Moschitti","orcid":"https://orcid.org/0000-0003-2216-8034"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alessandro Moschitti","raw_affiliation_strings":["Amazon Alexa, Manhattan Beach, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Amazon Alexa, Manhattan Beach, CA, USA","institution_ids":["https://openalex.org/I1311688040"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.9269,"has_fulltext":true,"cited_by_count":35,"citation_normalized_percentile":{"value":0.94699682,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1577","last_page":"1580"},"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.996999979019165,"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"}},{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9951000213623047,"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/transformer","display_name":"Transformer","score":0.8449048399925232},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7999224662780762},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.7874323129653931},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.627691388130188},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5507935285568237},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5432729125022888},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.416822612285614},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3949418365955353},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.37733206152915955},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.09879428148269653},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0793333649635315},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.0628713071346283}],"concepts":[{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.8449048399925232},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7999224662780762},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.7874323129653931},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.627691388130188},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5507935285568237},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5432729125022888},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.416822612285614},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3949418365955353},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.37733206152915955},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.09879428148269653},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0793333649635315},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0628713071346283},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3397271.3401266","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3397271.3401266","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3397271.3401266","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3397271.3401266","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3397271.3401266","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3397271.3401266","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3035183674.pdf","grobid_xml":"https://content.openalex.org/works/W3035183674.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1966443646","https://openalex.org/W2000431947","https://openalex.org/W2120735855","https://openalex.org/W2130618701","https://openalex.org/W2250539671","https://openalex.org/W2251818205","https://openalex.org/W2338364780","https://openalex.org/W2787560479","https://openalex.org/W2896457183","https://openalex.org/W2908332126","https://openalex.org/W2909544278","https://openalex.org/W2912924812","https://openalex.org/W2923890923","https://openalex.org/W2951528484","https://openalex.org/W2963809228","https://openalex.org/W2964110616","https://openalex.org/W2965373594","https://openalex.org/W2978017171","https://openalex.org/W2988869004","https://openalex.org/W2997090102","https://openalex.org/W3009496244","https://openalex.org/W3034212969"],"related_works":["https://openalex.org/W2384605597","https://openalex.org/W2387743295","https://openalex.org/W3082787378","https://openalex.org/W2136007095","https://openalex.org/W2366230879","https://openalex.org/W4381058564","https://openalex.org/W4281476908","https://openalex.org/W3003945460","https://openalex.org/W2964413124","https://openalex.org/W4288267738"],"abstract_inverted_index":{"IR-based":[0],"Question":[1],"Answering":[2],"(QA)":[3],"systems":[4],"typically":[5],"use":[6,45],"a":[7,105],"sentence":[8,68],"selector":[9],"to":[10,34,63,71,81],"extract":[11],"the":[12,27,65,90,101],"answer":[13],"from":[14,100],"retrieved":[15],"documents.":[16],"Recent":[17],"studies":[18],"have":[19],"shown":[20],"that":[21,54],"powerful":[22],"neural":[23,58,95],"models":[24,73,96],"based":[25],"on":[26],"Transformer":[28,72,106],"can":[29,60],"provide":[30],"an":[31,86],"accurate":[32],"solution":[33],"Answer":[35],"Sentence":[36],"Selection":[37],"(AS2).":[38],"Unfortunately,":[39],"their":[40,44],"computation":[41],"cost":[42],"prevents":[43],"in":[46],"real-world":[47],"applications.":[48],"In":[49],"this":[50],"paper,":[51],"we":[52],"show":[53],"standard":[55],"and":[56],"efficient":[57],"rerankers":[59],"be":[61],"used":[62,103],"reduce":[64],"amount":[66],"of":[67,93],"candidates":[69],"fed":[70],"without":[74],"hurting":[75],"Accuracy,":[76],"thus":[77],"improving":[78],"efficiency":[79],"up":[80],"four":[82],"times.":[83],"This":[84],"is":[85,97],"important":[87],"finding":[88],"as":[89],"internal":[91],"representation":[92],"shallower":[94],"dramatically":[98],"different":[99],"one":[102],"by":[104],"model,":[107],"e.g.,":[108],"word":[109],"vs.":[110],"contextual":[111],"embeddings.":[112]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":11}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
