{"id":"https://openalex.org/W3172072815","doi":"https://doi.org/10.1145/3471158.3472256","title":"Towards Axiomatic Explanations for Neural Ranking Models","display_name":"Towards Axiomatic Explanations for Neural Ranking Models","publication_year":2021,"publication_date":"2021-07-11","ids":{"openalex":"https://openalex.org/W3172072815","doi":"https://doi.org/10.1145/3471158.3472256","mag":"3172072815"},"language":"en","primary_location":{"id":"doi:10.1145/3471158.3472256","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3471158.3472256","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 ACM SIGIR International Conference on Theory of Information Retrieval","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2106.08019","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Michael V\u00f6lske","orcid":null},"institutions":[{"id":"https://openalex.org/I51441396","display_name":"Bauhaus-Universit\u00e4t Weimar","ror":"https://ror.org/033bb5z47","country_code":"DE","type":"education","lineage":["https://openalex.org/I51441396"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Michael V\u00f6lske","raw_affiliation_strings":["Bauhaus-Universit\u00e4t Weimar, Weimar, Germany"],"affiliations":[{"raw_affiliation_string":"Bauhaus-Universit\u00e4t Weimar, Weimar, Germany","institution_ids":["https://openalex.org/I51441396"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Alexander Bondarenko","orcid":null},"institutions":[{"id":"https://openalex.org/I68956291","display_name":"Martin Luther University Halle-Wittenberg","ror":"https://ror.org/05gqaka33","country_code":"DE","type":"education","lineage":["https://openalex.org/I68956291"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Alexander Bondarenko","raw_affiliation_strings":["Martin-Luther-Universit\u00e4t Halle-Wittenberg, Halle, Germany"],"affiliations":[{"raw_affiliation_string":"Martin-Luther-Universit\u00e4t Halle-Wittenberg, Halle, Germany","institution_ids":["https://openalex.org/I68956291"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Maik Fr\u00f6be","orcid":null},"institutions":[{"id":"https://openalex.org/I68956291","display_name":"Martin Luther University Halle-Wittenberg","ror":"https://ror.org/05gqaka33","country_code":"DE","type":"education","lineage":["https://openalex.org/I68956291"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Maik Fr\u00f6be","raw_affiliation_strings":["Martin-Luther-Universit\u00e4t Halle-Wittenberg, Halle, Germany"],"affiliations":[{"raw_affiliation_string":"Martin-Luther-Universit\u00e4t Halle-Wittenberg, Halle, Germany","institution_ids":["https://openalex.org/I68956291"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Benno Stein","orcid":null},"institutions":[{"id":"https://openalex.org/I51441396","display_name":"Bauhaus-Universit\u00e4t Weimar","ror":"https://ror.org/033bb5z47","country_code":"DE","type":"education","lineage":["https://openalex.org/I51441396"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Benno Stein","raw_affiliation_strings":["Bauhaus-Universit\u00e4t Weimar, Weimar, Germany"],"affiliations":[{"raw_affiliation_string":"Bauhaus-Universit\u00e4t Weimar, Weimar, Germany","institution_ids":["https://openalex.org/I51441396"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jaspreet Singh","orcid":null},"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":"Jaspreet Singh","raw_affiliation_strings":["Amazon, Palo Alto, CA, USA"],"affiliations":[{"raw_affiliation_string":"Amazon, Palo Alto, CA, USA","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Matthias Hagen","orcid":null},"institutions":[{"id":"https://openalex.org/I68956291","display_name":"Martin Luther University Halle-Wittenberg","ror":"https://ror.org/05gqaka33","country_code":"DE","type":"education","lineage":["https://openalex.org/I68956291"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Matthias Hagen","raw_affiliation_strings":["Martin-Luther-Universit\u00e4t Halle-Wittenberg, Halle, Germany"],"affiliations":[{"raw_affiliation_string":"Martin-Luther-Universit\u00e4t Halle-Wittenberg, Halle, Germany","institution_ids":["https://openalex.org/I68956291"]}]},{"author_position":"last","author":{"id":null,"display_name":"Avishek Anand","orcid":null},"institutions":[{"id":"https://openalex.org/I114112103","display_name":"Leibniz University Hannover","ror":"https://ror.org/0304hq317","country_code":"DE","type":"education","lineage":["https://openalex.org/I114112103"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Avishek Anand","raw_affiliation_strings":["Leibniz Universit\u00e4t Hannover, Hannover, Germany"],"affiliations":[{"raw_affiliation_string":"Leibniz Universit\u00e4t Hannover, Hannover, Germany","institution_ids":["https://openalex.org/I114112103"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I51441396"],"apc_list":null,"apc_paid":null,"fwci":2.5193,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.91041843,"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":"13","last_page":"22"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9998000264167786,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9998000264167786,"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":0.9976000189781189,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9954000115394592,"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/interpretability","display_name":"Interpretability","score":0.852400004863739},{"id":"https://openalex.org/keywords/axiom","display_name":"Axiom","score":0.7455999851226807},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6565999984741211},{"id":"https://openalex.org/keywords/axiomatic-system","display_name":"Axiomatic system","score":0.6065000295639038},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5216000080108643},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5012000203132629}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.852400004863739},{"id":"https://openalex.org/C167729594","wikidata":"https://www.wikidata.org/wiki/Q17736","display_name":"Axiom","level":2,"score":0.7455999851226807},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6565999984741211},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6258000135421753},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6165000200271606},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6097000241279602},{"id":"https://openalex.org/C125773388","wikidata":"https://www.wikidata.org/wiki/Q792542","display_name":"Axiomatic system","level":3,"score":0.6065000295639038},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5216000080108643},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5012000203132629},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.44449999928474426},{"id":"https://openalex.org/C9354725","wikidata":"https://www.wikidata.org/wiki/Q286017","display_name":"Operationalization","level":2,"score":0.43290001153945923},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.3864000141620636},{"id":"https://openalex.org/C132074034","wikidata":"https://www.wikidata.org/wiki/Q154210","display_name":"Congruence (geometry)","level":2,"score":0.3450999855995178},{"id":"https://openalex.org/C124975894","wikidata":"https://www.wikidata.org/wiki/Q7293290","display_name":"Ranking SVM","level":3,"score":0.27059999108314514},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26269999146461487},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2540999948978424},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.25130000710487366},{"id":"https://openalex.org/C111012933","wikidata":"https://www.wikidata.org/wiki/Q3137210","display_name":"Rough set","level":2,"score":0.2500999867916107}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3471158.3472256","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3471158.3472256","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 ACM SIGIR International Conference on Theory of Information Retrieval","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2106.08019","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2106.08019","pdf_url":"https://arxiv.org/pdf/2106.08019","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2106.08019","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2106.08019","pdf_url":"https://arxiv.org/pdf/2106.08019","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5772793584","display_name":null,"funder_award_id":"HA 5851/2-1","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W7333970","https://openalex.org/W110562955","https://openalex.org/W136907812","https://openalex.org/W1508903578","https://openalex.org/W1598867694","https://openalex.org/W1838897829","https://openalex.org/W1970405694","https://openalex.org/W2005545412","https://openalex.org/W2018026600","https://openalex.org/W2043351574","https://openalex.org/W2051442094","https://openalex.org/W2065702061","https://openalex.org/W2082359527","https://openalex.org/W2121974408","https://openalex.org/W2134557008","https://openalex.org/W2136480620","https://openalex.org/W2152228468","https://openalex.org/W2152784831","https://openalex.org/W2153479077","https://openalex.org/W2154848821","https://openalex.org/W2162432120","https://openalex.org/W2162697159","https://openalex.org/W2534359342","https://openalex.org/W2536015822","https://openalex.org/W2585950056","https://openalex.org/W2740321901","https://openalex.org/W2741796069","https://openalex.org/W2890881127","https://openalex.org/W2891482011","https://openalex.org/W2927996276","https://openalex.org/W2945127593","https://openalex.org/W2945802750","https://openalex.org/W2954902138","https://openalex.org/W2963165092","https://openalex.org/W2963636167","https://openalex.org/W2964012472","https://openalex.org/W2971209824","https://openalex.org/W3013870856","https://openalex.org/W3093860123","https://openalex.org/W3098307623","https://openalex.org/W3103686454","https://openalex.org/W3113553002","https://openalex.org/W4237214427","https://openalex.org/W4244048212","https://openalex.org/W4288280763","https://openalex.org/W6708070045"],"related_works":[],"abstract_inverted_index":{"Recently,":[0],"neural":[1,21,53,76,144,175,205],"networks":[2],"have":[3],"been":[4,60],"successfully":[5],"employed":[6],"to":[7,51,123,135,137,198],"improve":[8],"upon":[9],"state-of-the-art":[10],"effectiveness":[11],"in":[12,25,43,55,79,149,160],"ad-hoc":[13],"retrieval":[14,22,101,114,154],"tasks":[15],"via":[16],"machine-learned":[17],"ranking":[18,65,77,90,110,141,187],"functions.":[19],"While":[20,177],"models":[23,54,78,102,115],"grow":[24],"complexity":[26],"and":[27,49,156],"impact,":[28],"little":[29,61],"is":[30],"understood":[31,86],"about":[32],"their":[33,82],"correspondence":[34],"with":[35,84],"well-studied":[36],"IR":[37,206],"principles.":[38],"Recent":[39],"work":[40,192],"on":[41,109,127],"interpretability":[42],"machine":[44],"learning":[45],"has":[46,59,103],"provided":[47],"tools":[48],"techniques":[50],"understand":[52],"general,":[56],"yet":[57],"there":[58],"progress":[62],"towards":[63],"explaining":[64],"models.":[66],"We":[67,118],"investigate":[68,136],"whether":[69],"one":[70],"can":[71,146,181],"explain":[72,183],"the":[73,140,152,178,184,195,201],"behavior":[74],"of":[75,81,88,99,107,129,143,151,170],"terms":[80,150],"congruence":[83],"well":[85],"principles":[87],"document":[89],"by":[91],"using":[92],"established":[93],"theories":[94],"from":[95],"axiomatic~IR.":[96],"Axiomatic":[97],"analysis":[98],"information":[100],"formalized":[104],"a":[105,167],"set":[106,169,197],"constraints":[108],"decisions":[111,142,188],"that":[112],"reasonable":[113],"should":[116,193],"fulfill.":[117],"operationalize":[119],"this":[120],"axiomatic":[121],"thinking":[122],"reproduce":[124],"rankings":[125],"based":[126],"combinations":[128],"elementary":[130],"constraints.":[131],"This":[132],"allows":[133],"us":[134],"what":[138],"extent":[139],"rankers":[145],"be":[147],"explained":[148],"existing":[153,179],"axioms,":[155],"which":[157,161],"axioms":[158,171,180],"apply":[159],"situations.":[162],"Our":[163],"experimental":[164],"study":[165],"considers":[166],"comprehensive":[168],"over":[172],"several":[173],"representative":[174],"rankers.":[176],"already":[182],"particularly":[185],"confident":[186],"rather":[189],"well,":[190],"future":[191],"extend":[194],"axiom":[196],"also":[199],"cover":[200],"other":[202],"still":[203],"\"unexplainable\"":[204],"rank":[207],"decisions.":[208]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":6}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2021-06-22T00:00:00"}