{"id":"https://openalex.org/W4415317054","doi":"https://doi.org/10.1145/3767695.3769507","title":"Reproducing and Extending Causal Insights Into Term Frequency Computation in Neural Rankers","display_name":"Reproducing and Extending Causal Insights Into Term Frequency Computation in Neural Rankers","publication_year":2025,"publication_date":"2025-12-03","ids":{"openalex":"https://openalex.org/W4415317054","doi":"https://doi.org/10.1145/3767695.3769507"},"language":"en","primary_location":{"id":"doi:10.1145/3767695.3769507","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3767695.3769507","pdf_url":null,"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 2025 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3767695.3769507","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120050016","display_name":"Cile van Marken","orcid":null},"institutions":[{"id":"https://openalex.org/I4210135670","display_name":"Amsterdam University of the Arts","ror":"https://ror.org/04dde1554","country_code":"NL","type":"education","lineage":["https://openalex.org/I4210135670"]},{"id":"https://openalex.org/I887064364","display_name":"University of Amsterdam","ror":"https://ror.org/04dkp9463","country_code":"NL","type":"education","lineage":["https://openalex.org/I887064364"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Cile van Marken","raw_affiliation_strings":["University of Amsterdam, Amsterdam, Netherlands"],"affiliations":[{"raw_affiliation_string":"University of Amsterdam, Amsterdam, Netherlands","institution_ids":["https://openalex.org/I4210135670","https://openalex.org/I887064364"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5093967424","display_name":"Roxana Petcu","orcid":"https://orcid.org/0000-0002-2617-205X"},"institutions":[{"id":"https://openalex.org/I4210135670","display_name":"Amsterdam University of the Arts","ror":"https://ror.org/04dde1554","country_code":"NL","type":"education","lineage":["https://openalex.org/I4210135670"]},{"id":"https://openalex.org/I887064364","display_name":"University of Amsterdam","ror":"https://ror.org/04dkp9463","country_code":"NL","type":"education","lineage":["https://openalex.org/I887064364"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Roxana Petcu","raw_affiliation_strings":["University of Amsterdam, Amsterdam, Netherlands"],"affiliations":[{"raw_affiliation_string":"University of Amsterdam, Amsterdam, Netherlands","institution_ids":["https://openalex.org/I4210135670","https://openalex.org/I887064364"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5120050016"],"corresponding_institution_ids":["https://openalex.org/I4210135670","https://openalex.org/I887064364"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15548202,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"189","last_page":"198"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9828000068664551,"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/T10320","display_name":"Neural Networks and Applications","score":0.9828000068664551,"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":0.9301999807357788},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.6345000267028809},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6208000183105469},{"id":"https://openalex.org/keywords/axiom","display_name":"Axiom","score":0.5529999732971191},{"id":"https://openalex.org/keywords/chen","display_name":"Chen","score":0.5307000279426575},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.4584999978542328},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41370001435279846},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.41019999980926514}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.9301999807357788},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6951000094413757},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6420999765396118},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.6345000267028809},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6208000183105469},{"id":"https://openalex.org/C167729594","wikidata":"https://www.wikidata.org/wiki/Q17736","display_name":"Axiom","level":2,"score":0.5529999732971191},{"id":"https://openalex.org/C2776085556","wikidata":"https://www.wikidata.org/wiki/Q183361","display_name":"Chen","level":2,"score":0.5307000279426575},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5074999928474426},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.4584999978542328},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41370001435279846},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.41019999980926514},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.373199999332428},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.36329999566078186},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.3425000011920929},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.3411000072956085},{"id":"https://openalex.org/C3832189","wikidata":"https://www.wikidata.org/wiki/Q8588916","display_name":"Models of neural computation","level":3,"score":0.31790000200271606},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.30649998784065247},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.302700012922287},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.28940001130104065},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2700999975204468},{"id":"https://openalex.org/C59656382","wikidata":"https://www.wikidata.org/wiki/Q191536","display_name":"Conjunction (astronomy)","level":2,"score":0.2660999894142151},{"id":"https://openalex.org/C125773388","wikidata":"https://www.wikidata.org/wiki/Q792542","display_name":"Axiomatic system","level":3,"score":0.2549999952316284}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3767695.3769507","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3767695.3769507","pdf_url":null,"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 2025 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region","raw_type":"proceedings-article"},{"id":"pmh:oai:dare.uva.nl:openaire/77fc16fa-23ff-4353-9660-c74aa9824e61","is_oa":true,"landing_page_url":"https://handle.uba.uva.nl/personal/pure/en/publications/reproducing-and-extending-causal-insights-into-term-frequency-computation-in-neural-rankers(77fc16fa-23ff-4353-9660-c74aa9824e61).html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400088","display_name":"UvA-DARE (University of Amsterdam)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I887064364","host_organization_name":"University of Amsterdam","host_organization_lineage":["https://openalex.org/I887064364"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"van Marken, C & Petcu, R 2025, Reproducing and Extending Causal Insights Into Term Frequency Computation in Neural Rankers. in SIGIR-AP 2025 : Proceedings of the 2025 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region : December 7-10, 2025, Xi'an, China. Association for Computing Machinery, New York, NY, pp. 189-198, 3rd International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region, SIGIR-AP 2025, Xi'an, China, 7/12/25. https://doi.org/10.1145/3767695.3769507","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:arXiv.org:2510.06728","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.06728","pdf_url":"https://arxiv.org/pdf/2510.06728","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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"}],"best_oa_location":{"id":"doi:10.1145/3767695.3769507","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3767695.3769507","pdf_url":null,"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 2025 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Neural":[0,65],"ranking":[1,108,193,226],"models":[2,29,35,99,109],"have":[3],"shown":[4],"outstanding":[5],"performance":[6],"across":[7],"a":[8,77,83,203],"variety":[9],"of":[10,27,126,153,186,205,224],"tasks,":[11],"such":[12,42,129],"as":[13,34,43,130,195],"document":[14,101,192],"retrieval,":[15],"re-ranking,":[16],"question":[17],"answering":[18],"and":[19,147,171,212],"conversational":[20],"retrieval.":[21],"However,":[22],"the":[23,89,127,141,151,163,173,184,196,220],"inner":[24,221],"decision":[25],"process":[26,223],"these":[28,118],"remains":[30],"largely":[31],"unclear,":[32],"especially":[33],"increase":[36],"in":[37,64,88,157],"size.":[38],"Most":[39],"interpretability":[40,85],"approaches,":[41],"probing,":[44],"focus":[45],"on":[46,191],"correlational":[47],"insights":[48,94],"rather":[49],"than":[50],"establishing":[51],"causal":[52,84],"relationships.":[53],"The":[54,103],"paper":[55,137],"'Axiomatic":[56],"Causal":[57],"Interventions":[58],"for":[59,79],"Reverse":[60],"Engineering":[61],"Relevance":[62],"Computation":[63],"Retrieval":[66],"Models'":[67],"by":[68,75,143,167],"Chen":[69,144,168],"et":[70,145,169],"al.":[71,146],"addresses":[72],"this":[73,210],"gap":[74],"introducing":[76],"framework":[78,174],"activation":[80],"patching":[81],"-":[82,87],"method":[86],"information":[90],"retrieval":[91,98,155],"domain,":[92],"offering":[93],"into":[95,219],"how":[96],"neural":[97,107,158,225],"compute":[100],"relevance.":[102],"study":[104],"demonstrates":[105],"that":[106,117,183,208],"not":[110],"only":[111],"capture":[112],"term-frequency":[113,179],"information,":[114],"but":[115],"also":[116],"representations":[119],"can":[120],"be":[121],"localized":[122],"to":[123,139,148,175,216],"specific":[124],"components":[125],"model,":[128],"individual":[131],"attention":[132,206],"heads":[133,207],"or":[134],"layers.":[135],"This":[136],"aims":[138],"reproduce":[140],"findings":[142],"further":[149],"explore":[150],"presence":[152],"pre-defined":[154],"axioms":[156],"IR":[159],"models.":[160,227],"We":[161,200],"validate":[162],"main":[164],"claims":[165],"made":[166],"al.,":[170],"extend":[172],"include":[176],"an":[177],"additional":[178],"axiom,":[180],"which":[181],"states":[182],"impact":[185],"increasing":[187],"query":[188],"term":[189],"frequency":[190,197],"diminishes":[194],"becomes":[198],"higher.":[199],"successfully":[201],"identify":[202],"group":[204],"encode":[209],"axiom":[211],"analyze":[213],"their":[214],"behavior":[215],"give":[217],"insight":[218],"decision-making":[222]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-18T00:00:00"}