{"id":"https://openalex.org/W4306317399","doi":"https://doi.org/10.1145/3511808.3557312","title":"Evaluating Interpolation and Extrapolation Performance of Neural Retrieval Models","display_name":"Evaluating Interpolation and Extrapolation Performance of Neural Retrieval Models","publication_year":2022,"publication_date":"2022-10-16","ids":{"openalex":"https://openalex.org/W4306317399","doi":"https://doi.org/10.1145/3511808.3557312"},"language":"en","primary_location":{"id":"doi:10.1145/3511808.3557312","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3511808.3557312","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3511808.3557312","source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3511808.3557312","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023520034","display_name":"Jingtao Zhan","orcid":"https://orcid.org/0000-0002-7253-5245"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jingtao Zhan","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101977658","display_name":"Xiaohui Xie","orcid":"https://orcid.org/0000-0001-9413-4461"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohui Xie","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072119199","display_name":"Jiaxin Mao","orcid":"https://orcid.org/0000-0002-9257-5498"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaxin Mao","raw_affiliation_strings":["Renmin University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100668121","display_name":"Yiqun Liu","orcid":"https://orcid.org/0000-0002-0140-4512"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiqun Liu","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088621320","display_name":"Jiafeng Guo","orcid":"https://orcid.org/0000-0002-9509-8674"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiafeng Guo","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100402911","display_name":"Min Zhang","orcid":"https://orcid.org/0000-0002-3895-5510"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Zhang","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100760812","display_name":"Shaoping Ma","orcid":"https://orcid.org/0000-0002-8762-8268"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaoping Ma","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5023520034"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.7305,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.71674616,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"2486","last_page":"2496"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9991999864578247,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9991999864578247,"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/T10028","display_name":"Topic Modeling","score":0.996999979019165,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","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/extrapolation","display_name":"Extrapolation","score":0.8640269041061401},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7698237895965576},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.655689001083374},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5942737460136414},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.506489634513855},{"id":"https://openalex.org/keywords/resampling","display_name":"Resampling","score":0.498729944229126},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.49136558175086975},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4285103678703308},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4142412841320038},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12149670720100403},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08178922533988953}],"concepts":[{"id":"https://openalex.org/C132459708","wikidata":"https://www.wikidata.org/wiki/Q744069","display_name":"Extrapolation","level":2,"score":0.8640269041061401},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7698237895965576},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.655689001083374},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5942737460136414},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.506489634513855},{"id":"https://openalex.org/C150921843","wikidata":"https://www.wikidata.org/wiki/Q1170431","display_name":"Resampling","level":2,"score":0.498729944229126},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.49136558175086975},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4285103678703308},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4142412841320038},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12149670720100403},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08178922533988953},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3511808.3557312","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3511808.3557312","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3511808.3557312","source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3511808.3557312","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3511808.3557312","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3511808.3557312","source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.4000000059604645,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G26613612","display_name":null,"funder_award_id":"1732008","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3085993365","display_name":null,"funder_award_id":"(Grant No.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3308505718","display_name":null,"funder_award_id":"61732008","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5249178904","display_name":null,"funder_award_id":"Grant No. 6","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7726157001","display_name":null,"funder_award_id":"Grant No.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322392","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4306317399.pdf","grobid_xml":"https://content.openalex.org/works/W4306317399.grobid-xml"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W1965559057","https://openalex.org/W1968927634","https://openalex.org/W2043909051","https://openalex.org/W2053154970","https://openalex.org/W2069870183","https://openalex.org/W2090035194","https://openalex.org/W2740517242","https://openalex.org/W2798329376","https://openalex.org/W2798658104","https://openalex.org/W2892181857","https://openalex.org/W2899154813","https://openalex.org/W3021397474","https://openalex.org/W3085914694","https://openalex.org/W3099700870","https://openalex.org/W3152624702","https://openalex.org/W3154280800","https://openalex.org/W3154670582","https://openalex.org/W3154755316","https://openalex.org/W3155895380","https://openalex.org/W3168875417","https://openalex.org/W3172750682","https://openalex.org/W3201233724","https://openalex.org/W3205509771","https://openalex.org/W3212725701","https://openalex.org/W4206121183","https://openalex.org/W4206633947","https://openalex.org/W4224233308","https://openalex.org/W4301001114"],"related_works":["https://openalex.org/W1968270095","https://openalex.org/W2220129715","https://openalex.org/W4296478327","https://openalex.org/W2042397106","https://openalex.org/W2168645698","https://openalex.org/W4237321385","https://openalex.org/W2560420848","https://openalex.org/W2167211785","https://openalex.org/W2052829037","https://openalex.org/W3212114011"],"abstract_inverted_index":{"A":[0],"retrieval":[1,26,65,175,191,199],"model":[2],"should":[3],"not":[4,206],"only":[5],"interpolate":[6],"the":[7,15,21,55,60,75,80,104,118,131,142,153,163,221],"training":[8,22,83,143,157],"data":[9,86,146],"but":[10,205],"also":[11],"extrapolate":[12],"well":[13,196],"to":[14,128,167,186,212],"queries":[16],"that":[17,103],"are":[18],"different":[19],"from":[20,74,184],"data.":[23],"While":[24],"neural":[25,64,174],"models":[27,179,192,200],"have":[28],"demonstrated":[29],"impressive":[30],"performance":[31,135,219],"on":[32,106,136,148],"ad-hoc":[33,71],"search":[34,72],"benchmarks,":[35],"we":[36,53,68,122,161],"still":[37],"know":[38],"little":[39],"about":[40],"how":[41],"they":[42],"perform":[43,180,193],"in":[44,92,201],"terms":[45,202],"of":[46,57,63,82,172,203],"interpolation":[47,113,132,185,204,216],"and":[48,84,87,97,114,133,144,151,158,217,220],"extrapolation.":[49,187,207],"In":[50],"this":[51],"paper,":[52],"demonstrate":[54],"importance":[56],"separately":[58,129,213],"evaluating":[59],"two":[61,76],"capabilities":[62],"models.":[66,176],"Firstly,":[67],"examine":[69],"existing":[70,137],"benchmarks":[73],"perspectives.":[77],"We":[78],"investigate":[79],"distribution":[81],"test":[85,108,145],"find":[88],"a":[89,124,170,227],"considerable":[90],"overlap":[91],"query":[93,95,149],"entities,":[94],"intent,":[96],"relevance":[98],"labels.":[99],"This":[100],"finding":[101],"implies":[102],"evaluation":[105,126,165,231],"these":[107],"sets":[109],"is":[110,210],"biased":[111],"toward":[112],"cannot":[115],"accurately":[116],"reflect":[117],"extrapolation":[119,134,218],"capacity.":[120],"Secondly,":[121],"propose":[123],"novel":[125],"protocol":[127,166],"evaluate":[130,214],"benchmark":[138],"datasets.":[139],"It":[140],"resamples":[141],"based":[147],"similarity":[150],"utilizes":[152],"resampled":[154],"dataset":[155],"for":[156,233],"evaluation.":[159],"Finally,":[160],"leverage":[162],"proposed":[164,222],"comprehensively":[168],"revisit":[169],"number":[171],"widely-adopted":[173],"Results":[177],"show":[178],"differently":[181],"when":[182],"moving":[183],"For":[188],"example,":[189],"representation-based":[190],"almost":[194],"as":[195,197,226],"interaction-based":[198],"Therefore,":[208],"it":[209],"necessary":[211],"both":[215],"resampling":[223],"method":[224],"serves":[225],"simple":[228],"yet":[229],"effective":[230],"tool":[232],"future":[234],"IR":[235],"studies.":[236]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}
