{"id":"https://openalex.org/W7165412686","doi":"https://doi.org/10.48550/arxiv.2606.20526","title":"DeepSWIP: Quotient-WMC Counterfactuals for Neural Probabilistic Logic Programs","display_name":"DeepSWIP: Quotient-WMC Counterfactuals for Neural Probabilistic Logic Programs","publication_year":2026,"publication_date":"2026-06-18","ids":{"openalex":"https://openalex.org/W7165412686","doi":"https://doi.org/10.48550/arxiv.2606.20526"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.20526","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.20526","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.20526","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130288263","display_name":"Saimun Habib","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Habib, Saimun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139009375","display_name":"Vaishak Belle","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Belle, Vaishak","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100635369","display_name":"Fengxiang He","orcid":"https://orcid.org/0000-0001-5584-2385"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Fengxiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.17739999294281006,"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":0.17739999294281006,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.10029999911785126,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.09200000017881393,"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":0.8371999859809875},{"id":"https://openalex.org/keywords/counterfactual-conditional","display_name":"Counterfactual conditional","score":0.6536999940872192},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.645799994468689},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.6164000034332275},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5016999840736389},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.49869999289512634},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.44699999690055847},{"id":"https://openalex.org/keywords/non-monotonic-logic","display_name":"Non-monotonic logic","score":0.41019999980926514},{"id":"https://openalex.org/keywords/stable-model-semantics","display_name":"Stable model semantics","score":0.34360000491142273}],"concepts":[{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.8371999859809875},{"id":"https://openalex.org/C71889745","wikidata":"https://www.wikidata.org/wiki/Q1783264","display_name":"Counterfactual conditional","level":3,"score":0.6536999940872192},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.645799994468689},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6259999871253967},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.6164000034332275},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.567799985408783},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5016999840736389},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.49869999289512634},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45879998803138733},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.44699999690055847},{"id":"https://openalex.org/C159032336","wikidata":"https://www.wikidata.org/wiki/Q2488768","display_name":"Non-monotonic logic","level":2,"score":0.41019999980926514},{"id":"https://openalex.org/C127001435","wikidata":"https://www.wikidata.org/wiki/Q7595770","display_name":"Stable model semantics","level":4,"score":0.34360000491142273},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.32589998841285706},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3249000012874603},{"id":"https://openalex.org/C134752490","wikidata":"https://www.wikidata.org/wiki/Q374182","display_name":"Logical consequence","level":2,"score":0.320499986410141},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.30869999527931213},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.30399999022483826},{"id":"https://openalex.org/C193221554","wikidata":"https://www.wikidata.org/wiki/Q5153664","display_name":"Commonsense reasoning","level":2,"score":0.29910001158714294},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.29789999127388},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.2935999929904938},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.28369998931884766},{"id":"https://openalex.org/C8521452","wikidata":"https://www.wikidata.org/wiki/Q203790","display_name":"Connectionism","level":3,"score":0.28290000557899475},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.2815999984741211},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.2775999903678894},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2727999985218048},{"id":"https://openalex.org/C46274116","wikidata":"https://www.wikidata.org/wiki/Q185521","display_name":"Truth value","level":2,"score":0.2662000060081482},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.26589998602867126},{"id":"https://openalex.org/C195344581","wikidata":"https://www.wikidata.org/wiki/Q2555318","display_name":"Automated reasoning","level":2,"score":0.26249998807907104},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.25519999861717224},{"id":"https://openalex.org/C2185349","wikidata":"https://www.wikidata.org/wiki/Q190558","display_name":"Negation","level":2,"score":0.2540999948978424}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.20526","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.20526","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.20526","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.20526","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"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":{"Neurosymbolic":[0],"systems":[1],"such":[2],"as":[3,116],"DeepProbLog":[4,35],"combine":[5],"neural":[6,38,43,92,135],"perception":[7],"with":[8],"probabilistic":[9],"logic,":[10],"but":[11],"standard":[12,84],"inference":[13,121],"is":[14,75,159],"associational.":[15],"Counterfactual":[16],"reasoning":[17],"additionally":[18],"requires":[19],"a":[20,30,64,110,119,142],"causal":[21],"semantics":[22,33],"for":[23,34,152],"interventions":[24],"and":[25,55,71,94,100,118,155],"evidence.":[26],"We":[27],"introduce":[28],"DeepSWIP,":[29],"single-world":[31],"counterfactual":[32],"programs.":[36],"Using":[37],"materialization,":[39],"we":[40],"reduce":[41],"fixed-context":[42],"predicates":[44],"to":[45,78],"ordinary":[46],"ProbLog":[47,88],"choices,":[48],"apply":[49],"Single":[50],"World":[51],"Intervention":[52],"Programs":[53],"(SWIPs),":[54],"compute":[56],"counterfactuals":[57],"by":[58],"weighted":[59],"model":[60],"counting":[61],"(WMC)":[62],"over":[63],"single":[65],"transformed":[66],"program.":[67],"Under":[68],"finite":[69],"grounding":[70],"unique-supported-model":[72],"assumptions,":[73],"DeepSWIP":[74],"exact":[76],"relative":[77],"the":[79,107,125],"learned":[80],"materialized":[81],"FCM.":[82],"The":[83],"quotient-WMC":[85],"form":[86],"of":[87],"conditionals":[89],"identifies":[90],"active":[91],"probabilities":[93],"explains":[95],"intervention":[96],"cleaning,":[97],"calibration":[98,136],"sensitivity,":[99],"rare-evidence":[101],"instability.":[102],"Experiments":[103],"on":[104],"MPI3D":[105],"confirm":[106],"transformation":[108],"against":[109,113],"DeepTwin":[111],"construction":[112],"12,000":[114],"queries,":[115],"predicted":[117],"2.14$\\times$":[120],"speedup":[122],"from":[123],"avoiding":[124],"Twin's":[126],"endogenous":[127],"duplication.":[128],"A":[129],"SUMO":[130],"HOV":[131],"experiment":[132],"shows":[133],"that":[134],"degradation":[137],"biases":[138],"plug-in":[139],"estimates,":[140],"while":[141],"correctly":[143],"scoped":[144],"randomized-policy":[145],"AIPW":[146],"estimator":[147],"removes":[148],"most":[149],"first-order":[150],"bias":[151],"population":[153],"mean":[154],"ATE":[156],"estimands.":[157],"Code":[158],"at":[160],"https://github.com/saibib/deep_SWIP.":[161]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-20T00:00:00"}
