{"id":"https://openalex.org/W4403589700","doi":"https://doi.org/10.18653/v1/2026.findings-acl.1917","title":"A Counterfactual Explanation Framework for Retrieval Models","display_name":"A Counterfactual Explanation Framework for Retrieval Models","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W4403589700","doi":"https://doi.org/10.18653/v1/2026.findings-acl.1917"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2026.findings-acl.1917","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.1917","pdf_url":"https://aclanthology.org/2026.findings-acl.1917.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":"Findings of the Association for Computational Linguistics: ACL 2026","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2026.findings-acl.1917.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114342377","display_name":"Bhavik Chandna","orcid":null},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bhavik Chandna","raw_affiliation_strings":["University of California San Diego , USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California San Diego , USA","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000569823","display_name":"Procheta Sen","orcid":"https://orcid.org/0000-0002-3814-5462"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Procheta Sen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.00244141,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"38477","last_page":"38490"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11986","display_name":"Scientific Computing and Data Management","score":0.9617000222206116,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11986","display_name":"Scientific Computing and Data Management","score":0.9617000222206116,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.9602000117301941,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10215","display_name":"Semantic Web and Ontologies","score":0.9466000199317932,"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/counterfactual-thinking","display_name":"Counterfactual thinking","score":0.9337408542633057},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.4596713185310364},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4265105426311493},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.35521334409713745},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.331484854221344},{"id":"https://openalex.org/keywords/epistemology","display_name":"Epistemology","score":0.23624718189239502},{"id":"https://openalex.org/keywords/philosophy","display_name":"Philosophy","score":0.1634090542793274}],"concepts":[{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.9337408542633057},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.4596713185310364},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4265105426311493},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.35521334409713745},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.331484854221344},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.23624718189239502},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.1634090542793274}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.18653/v1/2026.findings-acl.1917","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.1917","pdf_url":"https://aclanthology.org/2026.findings-acl.1917.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":"Findings of the Association for Computational Linguistics: ACL 2026","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2409.00860","is_oa":true,"landing_page_url":"https://arxiv.org/abs/2409.00860","pdf_url":"https://arxiv.org/pdf/2409.00860","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2409.00860","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2409.00860","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.18653/v1/2026.findings-acl.1917","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.1917","pdf_url":"https://aclanthology.org/2026.findings-acl.1917.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":"Findings of the Association for Computational Linguistics: ACL 2026","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4403589700.pdf","grobid_xml":"https://content.openalex.org/works/W4403589700.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4391375266","https://openalex.org/W3201448254","https://openalex.org/W4286970243","https://openalex.org/W2066431708","https://openalex.org/W4384133558","https://openalex.org/W3025615835","https://openalex.org/W173210993","https://openalex.org/W2390660599"],"abstract_inverted_index":{"Explainability":[0],"has":[1,31,76],"become":[2],"a":[3,40,46,51,63,72,82,88,92,118,133,139,143,147,177],"crucial":[4],"concern":[5],"in":[6,100,124],"modern":[7],"machine":[8],"learning":[9,12],"and":[10,194],"deep":[11],"because":[13],"it":[14,96],"improves":[15],"model":[16,90,141],"transparency.Information":[17],"retrieval":[18,41,89,140],"(IR)":[19],"is":[20,48,56,68,84,160,206],"no":[21],"exception.In":[22],"the":[23,29,101,109,154,161,182,185],"existing":[24],"literature":[25],"on":[26,34],"explainable":[27],"IR,":[28],"emphasis":[30],"predominantly":[32],"been":[33,77],"explaining":[35],"relevance":[36],"with":[37],"respect":[38],"to":[39,50,79,117,120,132,150,164],"model.Typical":[42],"questions":[43],"include":[44],"why":[45,53,62,81,95],"document":[47,55,83,119,134],"relevant":[49,58,70],"query,":[52],"one":[54],"more":[57],"than":[59],"another,":[60],"or":[61],"particular":[64],"set":[65],"of":[66,156,184],"documents":[67],"considered":[69],"for":[71,91,142,188,203],"query.However,":[73],"limited":[74],"attention":[75],"given":[78,144],"understanding":[80],"not":[85,98,135],"favored":[86,137],"by":[87,138],"query":[93],"(e.g.,":[94,192,197],"does":[97],"appear":[99],"top-K":[102],"results).To":[103],"address":[104,151],"this":[105,152,159,166],"gap,":[106],"we":[107],"study":[108,165],"following":[110],"question:":[111],"which":[112,128,172],"terms":[113],"should":[114],"be":[115],"added":[116],"improve":[121],"its":[122],"ranking?This,":[123],"turn,":[125],"helps":[126],"explain":[127],"missing":[129,173],"words":[130,174],"contribute":[131],"being":[136],"query.We":[145],"use":[146],"counterfactual":[148,168],"framework":[149],"problem.To":[153],"best":[155],"our":[157,204],"knowledge,":[158],"first":[162],"attempt":[163],"specific":[167],"setting,":[169],"namely,":[170],"identifying":[171],"can":[175],"affect":[176],"document's":[178],"ranking.Our":[179],"experiments":[180],"demonstrate":[181],"effectiveness":[183],"proposed":[186],"approach":[187,205],"both":[189],"statistical":[190],"models":[191,196],"BM25)":[193],"deeplearning-based":[195],"DRMM,":[198],"DSSM,":[199],"ColBERT,":[200],"MonoT5).The":[201],"code":[202],"available":[207],"at":[208],"https://github.com/":[209],"TheProParadox/Explainable-IR.":[210]},"counts_by_year":[],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}