{"id":"https://openalex.org/W7225580309","doi":"https://doi.org/10.58496/bjai/2026/013","title":"Coupling-Aware Counterfactual Reasoning for Causal Artificial Intelligence: Identification, Learnability Limits, and Sharp Bounds with Finite-Sample Inference","display_name":"Coupling-Aware Counterfactual Reasoning for Causal Artificial Intelligence: Identification, Learnability Limits, and Sharp Bounds with Finite-Sample Inference","publication_year":2026,"publication_date":"2026-11-08","ids":{"openalex":"https://openalex.org/W7225580309","doi":"https://doi.org/10.58496/bjai/2026/013"},"language":"en","primary_location":{"id":"doi:10.58496/bjai/2026/013","doi":"https://doi.org/10.58496/bjai/2026/013","is_oa":true,"landing_page_url":"https://doi.org/10.58496/bjai/2026/013","pdf_url":"https://mesopotamian.press/journals/index.php/BJAI/article/download/1211/1247","source":{"id":"https://openalex.org/S5407043202","display_name":"Babylonian Journal of Artificial Intelligence","issn_l":"3006-5437","issn":["3006-5437"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Babylonian Journal of Artificial Intelligence","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://mesopotamian.press/journals/index.php/BJAI/article/download/1211/1247","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000432642","display_name":"Jordi Vallverd\u00fa","orcid":"https://orcid.org/0000-0001-9975-7780","observed_orcids":["https://orcid.org/0000-0001-9975-7780"]},"institutions":[{"id":"https://openalex.org/I123044942","display_name":"Universitat Aut\u00f2noma de Barcelona","ror":"https://ror.org/052g8jq94","country_code":"ES","type":"education","lineage":["https://openalex.org/I123044942"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Jordi Vallverd\u00fa","raw_affiliation_strings":["Departament de Filosofia, Universitat Aut\u00f2noma de Barcelona, 08193 Bellaterra (Cerdanyola del Vall\u00e8s), Barcelona, Catalonia, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Departament de Filosofia, Universitat Aut\u00f2noma de Barcelona, 08193 Bellaterra (Cerdanyola del Vall\u00e8s), Barcelona, Catalonia, Spain","institution_ids":["https://openalex.org/I123044942"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5000432642"],"corresponding_institution_ids":["https://openalex.org/I123044942"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2026","issue":null,"first_page":"77","last_page":"97"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10845","display_name":"Advanced Causal Inference Techniques","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10845","display_name":"Advanced Causal Inference Techniques","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.0007999999797903001,"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/T10778","display_name":"Philosophy of Biology and Scientific Explanation","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/1207","display_name":"History and Philosophy of Science"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/counterfactual-thinking","display_name":"counterfactual reasoning","score":0.8830000162124634},{"id":"https://openalex.org/keywords/causal-inference","display_name":"causal inference","score":0.6740000247955322},{"id":"https://openalex.org/keywords/partial-identification","display_name":"partial identification","score":0.6460000276565552},{"id":"https://openalex.org/keywords/structural-causal-models","display_name":"structural causal models","score":0.675000011920929},{"id":"https://openalex.org/keywords/individual-treatment-effects","display_name":"individual treatment effects","score":0.6700000166893005},{"id":"https://openalex.org/keywords/finite-sample-inference","display_name":"finite-sample inference","score":0.5899999737739563},{"id":"https://openalex.org/keywords/linear-programming","display_name":"linear programming","score":0.49799999594688416},{"id":"https://openalex.org/keywords/language-model-evaluation","display_name":"language model evaluation","score":0.35899999737739563}],"concepts":[{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5896000266075134},{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.579800009727478},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.4927000105381012},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.43700000643730164},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4361000061035156},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.42010000348091125},{"id":"https://openalex.org/C35651441","wikidata":"https://www.wikidata.org/wiki/Q625303","display_name":"Independence (probability theory)","level":2,"score":0.4034000039100647},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.40070000290870667},{"id":"https://openalex.org/C199163554","wikidata":"https://www.wikidata.org/wiki/Q1681619","display_name":"Univariate","level":3,"score":0.3946000039577484},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.38960000872612},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3718000054359436},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.3456000089645386},{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.34299999475479126},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.3393999934196472},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3203999996185303},{"id":"https://openalex.org/C23131810","wikidata":"https://www.wikidata.org/wiki/Q818574","display_name":"Observational study","level":2,"score":0.3131999969482422},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.30140000581741333},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.29170000553131104},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.287200003862381},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.2818000018596649},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.28130000829696655},{"id":"https://openalex.org/C610760","wikidata":"https://www.wikidata.org/wiki/Q1340706","display_name":"Endogeneity","level":2,"score":0.27300000190734863},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.2727000117301941},{"id":"https://openalex.org/C21031990","wikidata":"https://www.wikidata.org/wiki/Q355020","display_name":"Probability measure","level":2,"score":0.26750001311302185},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.2669999897480011},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.26600000262260437},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.26440000534057617},{"id":"https://openalex.org/C162838799","wikidata":"https://www.wikidata.org/wiki/Q596077","display_name":"Counterexample","level":2,"score":0.2637999951839447},{"id":"https://openalex.org/C64357122","wikidata":"https://www.wikidata.org/wiki/Q1149766","display_name":"Causality (physics)","level":2,"score":0.2635999917984009},{"id":"https://openalex.org/C71889745","wikidata":"https://www.wikidata.org/wiki/Q1783264","display_name":"Counterfactual conditional","level":3,"score":0.26249998807907104},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.2621999979019165},{"id":"https://openalex.org/C28901747","wikidata":"https://www.wikidata.org/wiki/Q177571","display_name":"Decision theory","level":2,"score":0.259799987077713},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.25920000672340393},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.25859999656677246},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.25780001282691956},{"id":"https://openalex.org/C125112378","wikidata":"https://www.wikidata.org/wiki/Q176640","display_name":"Randomness","level":2,"score":0.257099986076355},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.25589999556541443},{"id":"https://openalex.org/C79772020","wikidata":"https://www.wikidata.org/wiki/Q5159264","display_name":"Conditional independence","level":2,"score":0.2558000087738037},{"id":"https://openalex.org/C95167961","wikidata":"https://www.wikidata.org/wiki/Q4483495","display_name":"Fiducial inference","level":5,"score":0.2506999969482422}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.58496/bjai/2026/013","doi":"https://doi.org/10.58496/bjai/2026/013","is_oa":true,"landing_page_url":"https://doi.org/10.58496/bjai/2026/013","pdf_url":"https://mesopotamian.press/journals/index.php/BJAI/article/download/1211/1247","source":{"id":"https://openalex.org/S5407043202","display_name":"Babylonian Journal of Artificial Intelligence","issn_l":"3006-5437","issn":["3006-5437"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Babylonian Journal of Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:ojs2.mesopotamian.press:article/1211","doi":null,"is_oa":true,"landing_page_url":"https://mesopotamian.press/journals/index.php/index/article/view/1211","pdf_url":null,"source":{"id":"https://openalex.org/S5407043202","display_name":"Babylonian Journal of Artificial Intelligence","issn_l":"3006-5437","issn":["3006-5437"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"3006-5437","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.58496/bjai/2026/013","doi":"https://doi.org/10.58496/bjai/2026/013","is_oa":true,"landing_page_url":"https://doi.org/10.58496/bjai/2026/013","pdf_url":"https://mesopotamian.press/journals/index.php/BJAI/article/download/1211/1247","source":{"id":"https://openalex.org/S5407043202","display_name":"Babylonian Journal of Artificial Intelligence","issn_l":"3006-5437","issn":["3006-5437"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Babylonian Journal of Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7225580309.pdf","grobid_xml":"https://content.openalex.org/works/W7225580309.grobid-xml"},"referenced_works_count":5,"referenced_works":["https://openalex.org/W4387635254","https://openalex.org/W4407690051","https://openalex.org/W4414415151","https://openalex.org/W4417129627","https://openalex.org/W7223663822"],"related_works":["https://openalex.org/W7221471750","https://openalex.org/W2184322563","https://openalex.org/W4302009990","https://openalex.org/W7125630183","https://openalex.org/W6967115137","https://openalex.org/W7164932546","https://openalex.org/W7204105969","https://openalex.org/W7221599122","https://openalex.org/W3213422393","https://openalex.org/W2182747286"],"abstract_inverted_index":{"Probabilities":[0],"of":[1,4,9,17,37,115],"benefit,":[2],"probabilities":[3],"causation":[5],"and":[6,29,57,62,105,168],"the":[7,14,38,51,64,112,116,127,188,194],"dispersion":[8],"individual":[10,120],"effects":[11],"depend":[12],"on":[13,27],"joint":[15,53],"law":[16],"potential":[18],"outcomes,":[19,187],"which":[20],"interventional":[21,39],"data":[22,59],"do":[23],"not":[24],"fix.":[25],"Building":[26],"Fr\u00e9chet\u2013Makarov":[28],"partial-identification":[30],"results,":[31],"we":[32],"show":[33],"that":[34,67,88,101,118],"every":[35],"coupling":[36,86],"laws":[40,54],"is":[41,72,77,122],"induced":[42],"by":[43,94,140],"an":[44,68,119,134],"empirically":[45,131],"equivalent":[46],"structural":[47],"causal":[48],"model,":[49],"characterize":[50],"feasible":[52],"when":[55,75],"observational":[56],"experimental":[58],"are":[60,175,181],"combined,":[61],"restate":[63],"classical":[65],"criterion":[66],"expected":[69],"cross-world":[70],"score":[71],"learnable":[73],"exactly":[74],"it":[76],"additively":[78],"separable.":[79],"We":[80],"turn":[81],"these":[82],"facts":[83],"into":[84],"a":[85,154],"audit":[87],"reports":[89],"sharp":[90,113],"identification":[91],"intervals,":[92],"computed":[93],"linear":[95],"programming,":[96],"with":[97],"projection":[98],"confidence":[99],"intervals":[100],"have":[102],"finite-sample":[103],"coverage":[104],"asymptotic":[106],"Imbens\u2013Manski":[107],"intervals.":[108,152],"Over":[109],"all":[110],"couplings,":[111],"range":[114],"probability":[117],"benefits":[121],"twice":[123],"as":[124,126],"wide":[125,151],"Gaussian-copula":[128],"range;":[129],"under":[130],"indistinguishable":[132],"models,":[133],"independence":[135],"plug-in":[136],"estimator":[137],"remains":[138],"biased":[139],"up":[141],"to":[142,183],"0.16;":[143],"two":[144],"public":[145],"randomized":[146],"trials":[147],"yield":[148],"informative":[149],"but":[150],"On":[153],"240-":[155],"item":[156],"stress":[157],"test,":[158],"three":[159],"open-source":[160],"language":[161],"models":[162,197],"answered":[163],"identified":[164],"items":[165,170],"almost":[166],"perfectly":[167],"non-identified":[169],"never":[171],"correctly.":[172],"Core":[173],"results":[174],"machine-checked":[176],"in":[177],"Lean":[178],"4.":[179],"Conclusions":[180],"limited":[182],"finite":[184],"or":[185],"univariate":[186],"stated":[189],"model":[190],"classes":[191],"and,":[192],"for":[193],"pilot,":[195],"small":[196]},"counts_by_year":[],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2026-11-09T00:00:00"}