{"id":"https://openalex.org/W7155838180","doi":"https://doi.org/10.1145/3774904.3792482","title":"AC$ <sup>2</sup> $L-GAD: Active Counterfactual Contrastive Learning for Graph Anomaly Detection","display_name":"AC$ <sup>2</sup> $L-GAD: Active Counterfactual Contrastive Learning for Graph Anomaly Detection","publication_year":2026,"publication_date":"2026-04-12","ids":{"openalex":"https://openalex.org/W7155838180","doi":"https://doi.org/10.1145/3774904.3792482"},"language":null,"primary_location":{"id":"doi:10.1145/3774904.3792482","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774904.3792482","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 ACM Web Conference 2026","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3774904.3792482","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065051130","display_name":"Kamal Berahmand","orcid":"https://orcid.org/0000-0003-4459-0703"},"institutions":[{"id":"https://openalex.org/I82951845","display_name":"RMIT University","ror":"https://ror.org/04ttjf776","country_code":"AU","type":"education","lineage":["https://openalex.org/I82951845"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Kamal Berahmand","raw_affiliation_strings":["RMIT University, Melbourne, VIC, Australia"],"raw_orcid":"https://orcid.org/0000-0003-4459-0703","affiliations":[{"raw_affiliation_string":"RMIT University, Melbourne, VIC, Australia","institution_ids":["https://openalex.org/I82951845"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037377774","display_name":"Saman Forouzandeh","orcid":"https://orcid.org/0000-0002-5952-156X"},"institutions":[{"id":"https://openalex.org/I82951845","display_name":"RMIT University","ror":"https://ror.org/04ttjf776","country_code":"AU","type":"education","lineage":["https://openalex.org/I82951845"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Saman Forouzandeh","raw_affiliation_strings":["RMIT University, Melbourne, VIC, Australia"],"raw_orcid":"https://orcid.org/0000-0002-5952-156X","affiliations":[{"raw_affiliation_string":"RMIT University, Melbourne, VIC, Australia","institution_ids":["https://openalex.org/I82951845"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037332127","display_name":"Mehrnoush Mohammadi","orcid":"https://orcid.org/0000-0001-9596-7414"},"institutions":[{"id":"https://openalex.org/I165143802","display_name":"The University of Queensland","ror":"https://ror.org/00rqy9422","country_code":"AU","type":"education","lineage":["https://openalex.org/I165143802"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Mehrnoush Mohammadi","raw_affiliation_strings":["The University of Queensland, Brisbane, QLD, Australia"],"raw_orcid":"https://orcid.org/0000-0001-9596-7414","affiliations":[{"raw_affiliation_string":"The University of Queensland, Brisbane, QLD, Australia","institution_ids":["https://openalex.org/I165143802"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063995470","display_name":"Parham Moradi","orcid":"https://orcid.org/0000-0002-5604-565X"},"institutions":[{"id":"https://openalex.org/I82951845","display_name":"RMIT University","ror":"https://ror.org/04ttjf776","country_code":"AU","type":"education","lineage":["https://openalex.org/I82951845"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Parham Moradi","raw_affiliation_strings":["RMIT University, Melbourne, VIC, Australia"],"raw_orcid":"https://orcid.org/0000-0002-5604-565X","affiliations":[{"raw_affiliation_string":"RMIT University, Melbourne, VIC, Australia","institution_ids":["https://openalex.org/I82951845"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030903468","display_name":"Mahdi Jalili","orcid":"https://orcid.org/0000-0002-0517-9420"},"institutions":[{"id":"https://openalex.org/I82951845","display_name":"RMIT University","ror":"https://ror.org/04ttjf776","country_code":"AU","type":"education","lineage":["https://openalex.org/I82951845"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Mahdi Jalili","raw_affiliation_strings":["RMIT University, Melbourne, VIC, Australia"],"raw_orcid":"https://orcid.org/0000-0002-0517-9420","affiliations":[{"raw_affiliation_string":"RMIT University, Melbourne, VIC, Australia","institution_ids":["https://openalex.org/I82951845"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":63.8681,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.99869667,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1183","last_page":"1194"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9108999967575073,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9108999967575073,"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/T11719","display_name":"Data Quality and Management","score":0.016200000420212746,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.010999999940395355,"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":0.920799970626831},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4674000144004822},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.42320001125335693},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.37950000166893005},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.3752000033855438},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.36970001459121704}],"concepts":[{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.920799970626831},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6317999958992004},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5719000101089478},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5396000146865845},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4674000144004822},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.42320001125335693},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.37950000166893005},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.3752000033855438},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.36970001459121704},{"id":"https://openalex.org/C58315980","wikidata":"https://www.wikidata.org/wiki/Q179436","display_name":"Asymptote","level":2,"score":0.3564999997615814},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.32429999113082886},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.3012999892234802},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.29910001158714294},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26809999346733093},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.25760000944137573},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2563999891281128}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3774904.3792482","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774904.3792482","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 ACM Web Conference 2026","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3774904.3792482","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774904.3792482","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 ACM Web Conference 2026","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W2741114205","https://openalex.org/W2808130788","https://openalex.org/W2808544127","https://openalex.org/W2944250323","https://openalex.org/W2963486145","https://openalex.org/W3016159950","https://openalex.org/W3048072497","https://openalex.org/W3133518153","https://openalex.org/W3210350882","https://openalex.org/W4205942400","https://openalex.org/W4221023051","https://openalex.org/W4221095033","https://openalex.org/W4254182148","https://openalex.org/W4311079930","https://openalex.org/W4320828694","https://openalex.org/W4379927591","https://openalex.org/W4382239148","https://openalex.org/W4393159601","https://openalex.org/W4399849661","https://openalex.org/W4400880042","https://openalex.org/W4409363394","https://openalex.org/W4409363958","https://openalex.org/W4409365221","https://openalex.org/W4409657560","https://openalex.org/W4410089268"],"related_works":[],"abstract_inverted_index":{"Graph":[0],"anomaly":[1],"detection":[2,108],"identifies":[3,70],"abnormal":[4],"patterns":[5],"in":[6,34,137],"networks":[7],"but":[8],"faces":[9],"label":[10],"scarcity":[11],"and":[12,74],"extreme":[13],"class":[14],"imbalance.":[15],"While":[16],"graph":[17],"contrastive":[18],"learning":[19],"offers":[20],"unsupervised":[21],"solutions,":[22],"existing":[23],"methods":[24],"suffer":[25],"from":[26,120],"two":[27],"limitations:":[28],"random":[29],"augmentations":[30,78],"break":[31],"semantic":[32],"consistency":[33],"positive":[35,77],"pairs,":[36],"while":[37,83,106],"naive":[38],"negative":[39,81],"sampling":[40],"produces":[41],"trivial":[42],"contrasts.":[43],"We":[44],"propose":[45],"AC2L-GAD,":[46],"an":[47],"Active":[48],"Counterfactual":[49],"Contrastive":[50],"Learning":[51],"framework":[52],"addressing":[53],"both":[54],"limitations":[55],"through":[56],"principled":[57],"counterfactual":[58,66,86,104],"reasoning.":[59],"By":[60],"combining":[61],"information-theoretic":[62],"active":[63],"selection":[64],"with":[65,134],"generation,":[67],"our":[68],"approach":[69],"structurally":[71],"complex":[72,142],"nodes":[73],"generates":[75],"anomaly-preserving":[76],"alongside":[79],"hard":[80],"contrasts,":[82],"restricting":[84],"expensive":[85],"generation":[87,105],"to":[88,102,131],"a":[89],"strategically":[90],"selected":[91],"subset.":[92],"This":[93],"design":[94],"reduces":[95],"computational":[96],"overhead":[97],"by":[98],"approximately":[99],"65%":[100],"compared":[101,130],"full-graph":[103],"maintaining":[107],"quality.":[109],"Experiments":[110],"on":[111],"nine":[112],"benchmark":[113],"datasets,":[114],"including":[115],"real-world":[116],"financial":[117],"transaction":[118],"graphs":[119],"GADBench,":[121],"show":[122],"that":[123],"AC2L-GAD":[124],"achieves":[125],"competitive":[126],"or":[127],"superior":[128],"performance":[129],"state-of-the-art":[132],"baselines,":[133],"notable":[135],"gains":[136],"datasets":[138],"where":[139],"anomalies":[140],"exhibit":[141],"attribute-structure":[143],"interactions.":[144]},"counts_by_year":[{"year":2026,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-04-28T00:00:00"}
