{"id":"https://openalex.org/W4417339482","doi":"https://doi.org/10.1109/ictai66417.2025.00010","title":"Trustworthy AI for Spatio-Temporal Forecasting via Counterfactual Causality","display_name":"Trustworthy AI for Spatio-Temporal Forecasting via Counterfactual Causality","publication_year":2025,"publication_date":"2025-11-03","ids":{"openalex":"https://openalex.org/W4417339482","doi":"https://doi.org/10.1109/ictai66417.2025.00010"},"language":"en","primary_location":{"id":"doi:10.1109/ictai66417.2025.00010","doi":"https://doi.org/10.1109/ictai66417.2025.00010","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ictai66417.2025.00010","pdf_url":null,"source":{"id":"https://openalex.org/S4210176007","display_name":"IEEE International Conference on Tools with Artificial Intelligence (ICTAI)","issn_l":"1082-3409","issn":["1082-3409","2375-0197"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","jufo-1","norway-1"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 37th International Conference on Tools with Artificial Intelligence (ICTAI)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5104022998","display_name":"Aya Ferchichi","orcid":"https://orcid.org/0000-0003-1947-2756","observed_orcids":["https://orcid.org/0000-0003-1947-2756"]},"institutions":[{"id":"https://openalex.org/I83259278","display_name":"Manouba University","ror":"https://ror.org/0503ejf32","country_code":"TN","type":"education","lineage":["https://openalex.org/I83259278"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Aya Ferchichi","raw_affiliation_strings":["ENSI, University of Manouba,RIADI Laboratory,Manouba,Tunisia,2010"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ENSI, University of Manouba,RIADI Laboratory,Manouba,Tunisia,2010","institution_ids":["https://openalex.org/I83259278"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073221047","display_name":"Ali Ben Abbes","orcid":"https://orcid.org/0000-0001-5714-7562","observed_orcids":["https://orcid.org/0000-0001-5714-7562"]},"institutions":[{"id":"https://openalex.org/I83259278","display_name":"Manouba University","ror":"https://ror.org/0503ejf32","country_code":"TN","type":"education","lineage":["https://openalex.org/I83259278"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Ali Ben Abbes","raw_affiliation_strings":["ENSI, University of Manouba,RIADI Laboratory,Manouba,Tunisia,2010"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ENSI, University of Manouba,RIADI Laboratory,Manouba,Tunisia,2010","institution_ids":["https://openalex.org/I83259278"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065664708","display_name":"Vincent Barra","orcid":"https://orcid.org/0000-0002-8975-222X","observed_orcids":["https://orcid.org/0000-0002-8975-222X"]},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I198244214","display_name":"Universit\u00e9 Clermont Auvergne","ror":"https://ror.org/01a8ajp46","country_code":"FR","type":"education","lineage":["https://openalex.org/I198244214"]},{"id":"https://openalex.org/I4210099416","display_name":"Laboratoire d'Informatique, de Mod\u00e9lisation et d'Optimisation des Syst\u00e8mes","ror":"https://ror.org/00t3fpp34","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I198244214","https://openalex.org/I203339264","https://openalex.org/I205703379","https://openalex.org/I3019848993","https://openalex.org/I4210099416","https://openalex.org/I4210123221","https://openalex.org/I4210159245","https://openalex.org/I4387154249"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Vincent Barra","raw_affiliation_strings":["Clermont Auvergne University, CNRS, UMR 6158, LIMOS,Clermont-Ferrand,France,63000"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Clermont Auvergne University, CNRS, UMR 6158, LIMOS,Clermont-Ferrand,France,63000","institution_ids":["https://openalex.org/I1294671590","https://openalex.org/I198244214","https://openalex.org/I4210099416"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053542801","display_name":"Imed Riadh Farah","orcid":"https://orcid.org/0000-0001-9114-5659","observed_orcids":["https://orcid.org/0000-0001-9114-5659"]},"institutions":[{"id":"https://openalex.org/I83259278","display_name":"Manouba University","ror":"https://ror.org/0503ejf32","country_code":"TN","type":"education","lineage":["https://openalex.org/I83259278"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Imed Riadh Farah","raw_affiliation_strings":["ENSI, University of Manouba,RIADI Laboratory,Manouba,Tunisia,2010"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ENSI, University of Manouba,RIADI Laboratory,Manouba,Tunisia,2010","institution_ids":["https://openalex.org/I83259278"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.4021,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.7671095,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"10","last_page":"17"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.0005000000237487257,"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/T11106","display_name":"Data Management and Algorithms","score":0.00019999999494757503,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/spatiotemporal-prediction","display_name":"spatiotemporal prediction","score":0.9200000166893005},{"id":"https://openalex.org/keywords/counterfactual-thinking","display_name":"counterfactual reasoning","score":0.9419999718666077},{"id":"https://openalex.org/keywords/causal-inference","display_name":"causal inference","score":0.7229999899864197},{"id":"https://openalex.org/keywords/confounding","display_name":"confounding","score":0.9020000100135803},{"id":"https://openalex.org/keywords/interpretable-forecasting","display_name":"interpretable forecasting","score":0.6610000133514404},{"id":"https://openalex.org/keywords/transformer","display_name":"transformer models","score":0.3569999933242798},{"id":"https://openalex.org/keywords/traffic-flow-prediction","display_name":"traffic flow prediction","score":0.7269999980926514},{"id":"https://openalex.org/keywords/what-if-scenarios","display_name":"what-if scenarios","score":0.7350000143051147},{"id":"https://openalex.org/keywords/trustworthy-ai","display_name":"trustworthy AI","score":0.6069999933242798}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.9243999719619751},{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.8755999803543091},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.675599992275238},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6697999835014343},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6371999979019165},{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.5432999730110168},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.46860000491142273},{"id":"https://openalex.org/C64357122","wikidata":"https://www.wikidata.org/wiki/Q1149766","display_name":"Causality (physics)","level":2,"score":0.4065000116825104},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.40049999952316284},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.38609999418258667},{"id":"https://openalex.org/C115086926","wikidata":"https://www.wikidata.org/wiki/Q17004651","display_name":"Causal reasoning","level":3,"score":0.3790000081062317},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.34619998931884766},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.33820000290870667},{"id":"https://openalex.org/C149810388","wikidata":"https://www.wikidata.org/wiki/Q5374873","display_name":"Emulation","level":2,"score":0.30410000681877136},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.30239999294281006},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.2939999997615814},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.289900004863739},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.2849999964237213},{"id":"https://openalex.org/C114073186","wikidata":"https://www.wikidata.org/wiki/Q2631895","display_name":"Automated planning and scheduling","level":2,"score":0.2847000062465668},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.28299999237060547},{"id":"https://openalex.org/C610760","wikidata":"https://www.wikidata.org/wiki/Q1340706","display_name":"Endogeneity","level":2,"score":0.28060001134872437},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.27810001373291016},{"id":"https://openalex.org/C197947376","wikidata":"https://www.wikidata.org/wiki/Q5155608","display_name":"Comparability","level":2,"score":0.27219998836517334},{"id":"https://openalex.org/C2780233690","wikidata":"https://www.wikidata.org/wiki/Q535347","display_name":"Transparency (behavior)","level":2,"score":0.26649999618530273},{"id":"https://openalex.org/C2780310539","wikidata":"https://www.wikidata.org/wiki/Q12547192","display_name":"Imperfect","level":2,"score":0.2574999928474426}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ictai66417.2025.00010","doi":"https://doi.org/10.1109/ictai66417.2025.00010","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ictai66417.2025.00010","pdf_url":null,"source":{"id":"https://openalex.org/S4210176007","display_name":"IEEE International Conference on Tools with Artificial Intelligence (ICTAI)","issn_l":"1082-3409","issn":["1082-3409","2375-0197"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","jufo-1","norway-1"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 37th International Conference on Tools with Artificial Intelligence (ICTAI)","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-05249309v1","doi":null,"is_oa":false,"landing_page_url":"https://hal.science/hal-05249309","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4405252976","host_organization_name":"Centre pour la Communication Scientifique Directe","host_organization_lineage":["https://openalex.org/I4405252976"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE International Conference on Tools with Artificial Intelligence, Nov 2025, Athens, Greece","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2143891888","https://openalex.org/W2282821441","https://openalex.org/W2756203131","https://openalex.org/W2809925683","https://openalex.org/W2971724044","https://openalex.org/W3111605943","https://openalex.org/W3175645274","https://openalex.org/W3201503466","https://openalex.org/W4205464866","https://openalex.org/W4206420106","https://openalex.org/W4211063691","https://openalex.org/W4221055004","https://openalex.org/W4245384076","https://openalex.org/W4382239644","https://openalex.org/W4385565192","https://openalex.org/W4387763661","https://openalex.org/W4388988295","https://openalex.org/W4391528837","https://openalex.org/W4406894863","https://openalex.org/W4406894922"],"related_works":["https://openalex.org/W7114930424","https://openalex.org/W4412082408","https://openalex.org/W7138901602","https://openalex.org/W7106857491","https://openalex.org/W4409283306","https://openalex.org/W4410852558","https://openalex.org/W7103903029","https://openalex.org/W4402963785","https://openalex.org/W7214416248","https://openalex.org/W7123342833"],"abstract_inverted_index":{"Recent":[0],"advances":[1],"in":[2,26,32,78,140,182],"deep":[3,58],"learning":[4,59],"architectures,":[5],"driven":[6],"by":[7],"Artificial":[8],"Intelligence":[9],"(AI),":[10],"have":[11],"significantly":[12],"enhanced":[13],"time-series":[14],"forecasting":[15,184],"accuracy.":[16],"However,":[17],"the":[18,129,148,164],"inherent":[19],"lack":[20],"of":[21,137,150,168],"interpretability":[22,165],"and":[23,39,64,159,166],"causal":[24,71,80,157,172],"reasoning":[25,109],"black-box":[27],"models":[28],"limits":[29],"their":[30],"adoption":[31],"high-impact":[33],"applications":[34],"such":[35],"as":[36],"traffic":[37],"management":[38],"urban":[40],"mobility.":[41],"To":[42],"address":[43],"this":[44],"challenge,":[45],"we":[46,104],"propose$\\mathrm{C}^{2}$-STORM":[47],"(Causal":[48],"Counterfactual":[49],"Spatio-Temporal":[50,93],"TransfORmer":[51],"Model),":[52],"a":[53,86,106,179],"novel":[54],"framework":[55],"that":[56,90,111],"integrates":[57],"to":[60,73],"achieve":[61],"both":[62],"accurate":[63],"interpretable":[65],"predictions.":[66,169],"Our":[67],"approach":[68],"uses":[69],"frontdoor-adjusted":[70],"extraction":[72],"reduce":[74],"confounding":[75],"bias,":[76],"grounded":[77],"structural":[79],"principles.":[81],"This":[82],"is":[83],"coupled":[84],"with":[85,118,135,174],"Dynamic":[87],"Causality":[88],"Generator":[89],"learns":[91],"context-aware":[92],"(ST)":[94],"dependencies":[95],"via":[96],"graphstructured":[97],"attention,":[98],"enhancing":[99],"node-specific":[100],"feature":[101,160],"prioritization.":[102],"Furthermore,":[103],"develop":[105],"transformer-based":[107],"counterfactual":[108],"module":[110],"simulates":[112],"actionable":[113],"\u201cwhat-if\u201d":[114],"scenarios,":[115],"aligning":[116],"interventions":[117],"domain-specific":[119],"logic.":[120],"Experiments":[121],"conducted":[122],"on":[123],"real-world":[124],"datasets":[125],"(PeMSD7,":[126],"LondonBike)":[127],"demonstrate":[128],"effectiveness":[130],"of$\\mathrm{C}^{2}$-STORM,":[131],"achieving":[132],"state-of-the-art":[133],"performance":[134],"improvements":[136],"4.2-":[138],"6.6%":[139],"MAE/MAPE":[141],"over":[142],"baseline":[143],"methods.":[144],"Ablation":[145],"studies":[146],"confirm":[147],"significance":[149],"each":[151],"component,":[152],"while":[153],"visual":[154],"explanations,":[155],"including":[156],"graphs":[158],"importance":[161],"maps,":[162],"enhance":[163],"transparency":[167],"By":[170],"bridging":[171],"inference":[173],"ST":[175],"learning,":[176],"C\u00b2-STORM":[177],"represents":[178],"significant":[180],"advancement":[181],"trustworthy":[183],"for":[185],"complex":[186],"systems.":[187]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2025-12-15T00:00:00"}