{"id":"https://openalex.org/W4385565270","doi":"https://doi.org/10.1145/3580305.3599240","title":"A Causality Inspired Framework for Model Interpretation","display_name":"A Causality Inspired Framework for Model Interpretation","publication_year":2023,"publication_date":"2023-08-04","ids":{"openalex":"https://openalex.org/W4385565270","doi":"https://doi.org/10.1145/3580305.3599240"},"language":"en","primary_location":{"id":"doi:10.1145/3580305.3599240","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3580305.3599240","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5033069158","display_name":"Chenwang Wu","orcid":"https://orcid.org/0000-0003-4937-0590"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenwang Wu","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0003-4937-0590","affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101524540","display_name":"Xiting Wang","orcid":"https://orcid.org/0000-0001-5768-1095"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiting Wang","raw_affiliation_strings":["Microsoft Research Asia, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-5768-1095","affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085254654","display_name":"Defu Lian","orcid":"https://orcid.org/0000-0002-3507-9607"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Defu Lian","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0002-3507-9607","affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044651577","display_name":"Xing Xie","orcid":"https://orcid.org/0000-0002-8608-8482"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xing Xie","raw_affiliation_strings":["Microsoft Research Asia, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-8608-8482","affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048237545","display_name":"Enhong Chen","orcid":"https://orcid.org/0000-0002-4835-4102"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Enhong Chen","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0002-4835-4102","affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2731","last_page":"2741"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9995999932289124,"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":0.9995999932289124,"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":0.988099992275238,"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/causality","display_name":"Causality (physics)","score":0.8196176886558533},{"id":"https://openalex.org/keywords/causal-inference","display_name":"Causal inference","score":0.8139647245407104},{"id":"https://openalex.org/keywords/interpretation","display_name":"Interpretation (philosophy)","score":0.7398494482040405},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7101578116416931},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.706095814704895},{"id":"https://openalex.org/keywords/causal-model","display_name":"Causal model","score":0.6822254657745361},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.622631847858429},{"id":"https://openalex.org/keywords/interpreter","display_name":"Interpreter","score":0.5534449219703674},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5167766809463501},{"id":"https://openalex.org/keywords/causal-reasoning","display_name":"Causal reasoning","score":0.45721957087516785},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42020249366760254},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.2618646025657654},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.1407122015953064},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13385191559791565},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.06500715017318726}],"concepts":[{"id":"https://openalex.org/C64357122","wikidata":"https://www.wikidata.org/wiki/Q1149766","display_name":"Causality (physics)","level":2,"score":0.8196176886558533},{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.8139647245407104},{"id":"https://openalex.org/C527412718","wikidata":"https://www.wikidata.org/wiki/Q855395","display_name":"Interpretation (philosophy)","level":2,"score":0.7398494482040405},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7101578116416931},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.706095814704895},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.6822254657745361},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.622631847858429},{"id":"https://openalex.org/C122783720","wikidata":"https://www.wikidata.org/wiki/Q183065","display_name":"Interpreter","level":2,"score":0.5534449219703674},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5167766809463501},{"id":"https://openalex.org/C115086926","wikidata":"https://www.wikidata.org/wiki/Q17004651","display_name":"Causal reasoning","level":3,"score":0.45721957087516785},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42020249366760254},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.2618646025657654},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.1407122015953064},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13385191559791565},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.06500715017318726},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3580305.3599240","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3580305.3599240","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3179083445","display_name":null,"funder_award_id":"62022077","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"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1767411471","https://openalex.org/W1849277567","https://openalex.org/W2367397349","https://openalex.org/W2516809705","https://openalex.org/W2595653137","https://openalex.org/W2764024122","https://openalex.org/W2801890059","https://openalex.org/W2949553967","https://openalex.org/W2950768109","https://openalex.org/W2963233086","https://openalex.org/W2963749936","https://openalex.org/W2998004401","https://openalex.org/W3005086430","https://openalex.org/W3012754345","https://openalex.org/W3026235644","https://openalex.org/W3037185591","https://openalex.org/W3040295870","https://openalex.org/W3040526978","https://openalex.org/W3177337639","https://openalex.org/W3187467055","https://openalex.org/W3188492908","https://openalex.org/W4212774754","https://openalex.org/W4223554833","https://openalex.org/W4283269716","https://openalex.org/W4287727981","https://openalex.org/W4287752800","https://openalex.org/W4305031253","https://openalex.org/W4312232143","https://openalex.org/W4312645761","https://openalex.org/W4361804600","https://openalex.org/W4376132596"],"related_works":["https://openalex.org/W1506300690","https://openalex.org/W1547624382","https://openalex.org/W4320159092","https://openalex.org/W2574301230","https://openalex.org/W4361865420","https://openalex.org/W2018580387","https://openalex.org/W2161504683","https://openalex.org/W3170261037","https://openalex.org/W3135588948","https://openalex.org/W3160160539"],"abstract_inverted_index":{"This":[0],"paper":[1],"introduces":[2],"a":[3,41,76,87],"unified":[4,42],"causal":[5,28,43,56,78],"lens":[6],"for":[7,114],"understanding":[8],"representative":[9],"model":[10,59,81],"interpretation":[11],"methods.":[12],"We":[13,83],"show":[14,97],"that":[15,65,73,98],"their":[16,35],"explanation":[17,79],"scores":[18],"align":[19],"with":[20,106],"the":[21,51],"concept":[22],"of":[23,80],"average":[24],"treatment":[25],"effect":[26],"in":[27,54],"inference,":[29],"which":[30,91],"allows":[31],"us":[32],"to":[33,58],"evaluate":[34],"relative":[36],"strengths":[37],"and":[38,71,103],"limitations":[39],"from":[40],"perspective.":[44],"Based":[45],"on":[46],"our":[47],"observations,":[48],"we":[49],"outline":[50],"major":[52],"challenges":[53],"applying":[55],"inference":[57],"interpretation,":[60],"including":[61],"identifying":[62],"common":[63],"causes":[64],"can":[66],"be":[67],"generalized":[68],"across":[69],"instances":[70],"ensuring":[72],"explanations":[74,105],"provide":[75],"complete":[77],"predictions.":[82],"then":[84],"present":[85],"CIMI,":[86],"Causality-Inspired":[88],"Model":[89],"Interpreter,":[90],"addresses":[92],"these":[93],"challenges.":[94],"Our":[95],"experiments":[96],"CIMI":[99],"provides":[100],"more":[101],"faithful":[102],"generalizable":[104],"improved":[107],"sampling":[108],"efficiency,":[109],"making":[110],"it":[111],"particularly":[112],"suitable":[113],"larger":[115],"pretrained":[116],"models.":[117]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":7}],"updated_date":"2026-07-21T08:15:58.654021","created_date":"2025-10-10T00:00:00"}