{"id":"https://openalex.org/W7160935544","doi":"https://doi.org/10.48550/arxiv.2605.09169","title":"Prediction Bottlenecks Don't Discover Causal Structure (But Here's What They Actually Do)","display_name":"Prediction Bottlenecks Don't Discover Causal Structure (But Here's What They Actually Do)","publication_year":2026,"publication_date":"2026-05-09","ids":{"openalex":"https://openalex.org/W7160935544","doi":"https://doi.org/10.48550/arxiv.2605.09169"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.09169","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.09169","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.2605.09169","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135953283","display_name":"Ankit Hemant Lade","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lade, Ankit Hemant","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135957916","display_name":"Sai Krishna Jasti","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jasti, Sai Krishna","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109534834","display_name":"Indar Kumar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kumar, Indar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135909793","display_name":"Aman Chadha","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chadha, Aman","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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.44339999556541443,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.44339999556541443,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.09220000356435776,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.040800001472234726,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.8029999732971191},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6528000235557556},{"id":"https://openalex.org/keywords/bivariate-analysis","display_name":"Bivariate analysis","score":0.5954999923706055},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.4936000108718872},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.460999995470047},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.4302000105381012},{"id":"https://openalex.org/keywords/protocol","display_name":"Protocol (science)","score":0.3452000021934509},{"id":"https://openalex.org/keywords/lasso","display_name":"Lasso (programming language)","score":0.3416000008583069}],"concepts":[{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.8029999732971191},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6528000235557556},{"id":"https://openalex.org/C64341305","wikidata":"https://www.wikidata.org/wiki/Q4919225","display_name":"Bivariate analysis","level":2,"score":0.5954999923706055},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.4936000108718872},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4652000069618225},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.460999995470047},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.4302000105381012},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38850000500679016},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3671000003814697},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3504999876022339},{"id":"https://openalex.org/C2780385302","wikidata":"https://www.wikidata.org/wiki/Q367158","display_name":"Protocol (science)","level":3,"score":0.3452000021934509},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.3416000008583069},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3353999853134155},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.3237000107765198},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.313400000333786},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.30820000171661377},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2989000082015991},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.2944999933242798},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2921000123023987},{"id":"https://openalex.org/C2984074130","wikidata":"https://www.wikidata.org/wiki/Q73539779","display_name":"R package","level":2,"score":0.28999999165534973},{"id":"https://openalex.org/C2776029896","wikidata":"https://www.wikidata.org/wiki/Q3935810","display_name":"Relaxation (psychology)","level":2,"score":0.28949999809265137},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2890999913215637},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.27140000462532043},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.2531000077724457}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.09169","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.09169","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.2605.09169","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.09169","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":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.43498024344444275}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"A":[0],"Mamba":[1],"state-space":[2],"model":[3],"trained":[4],"only":[5,115,155],"for":[6],"next-step":[7],"prediction":[8],"appears":[9],"to":[10,45],"recover":[11],"Granger-causal":[12],"structure":[13],"through":[14,80],"a":[15,72,92,127,143,157,167,182],"simple":[16],"readout":[17],"$S":[18],"=":[19],"|W_{out}":[20],"W_{in}|$,":[21],"with":[22,118,166],"early":[23],"experiments":[24],"suggesting":[25],"the":[26,42,78,105,132,136,147,175,186,189],"phenomenon":[27],"generalized":[28],"across":[29],"architectures":[30],"and":[31,66,76,111,124,146,192],"benefited":[32],"from":[33],"interventional":[34],"data":[35],"at":[36],"$p":[37],"<":[38],"10^{-5}$.":[39],"We":[40],"package":[41],"protocol":[43],"used":[44],"test":[46],"that":[47,163],"claim":[48,79,87],"--":[49,70,174],"standardized":[50],"synthetic":[51,108],"generators":[52],"(VAR/Lorenz/CauseMe-style),":[53],"three":[54,63],"intervention":[55,138],"semantics":[56],"($do(X=c)$,":[57],"soft-noise,":[58],"random-forcing),":[59],"edge-provenance":[60],"cards":[61],"on":[62,107,112],"real":[64,116],"datasets,":[65],"size-matched":[67],"control":[68,200],"arms":[69],"as":[71,97],"reusable":[73],"falsification":[74],"benchmark,":[75],"walk":[77],"it":[81],"in":[82,130,170],"five":[83],"stages.":[84],"The":[85],"method-level":[86],"does":[88,96],"not":[89],"survive:":[90],"(i)":[91],"plain":[93],"linear":[94],"bottleneck":[95,106,133],"well":[98],"or":[99],"better;":[100],"(ii)":[101],"tuned":[102],"Lasso":[103],"beats":[104],"CauseMe-style":[109],"benchmarks,":[110],"Lorenz-96":[113],"(the":[114],"benchmark":[117,187],"unambiguous":[119],"ground":[120],"truth)":[121],"classical":[122,171],"PCMCI":[123],"Granger":[125,173],"lead":[126],"tight":[128],"cluster":[129],"which":[131],"trails;":[134],"(iii)":[135],"headline":[137],"advantage":[139],"is":[140,177,181,188,196],"roughly":[141],"60%":[142],"sample-size":[144],"confound,":[145],"residual":[148,164],"disappears":[149],"under":[150,156],"standard":[151],"$do(X=c)$":[152],"interventions,":[153],"surviving":[154],"non-standard":[158],"random-forcing":[159],"scheme;":[160],"(iv)":[161],"even":[162],"reproduces,":[165],"larger":[168],"effect,":[169],"bivariate":[172],"effect":[176],"method-agnostic.":[178],"What":[179],"survives":[180],"narrow":[183],"characterization":[184],"result;":[185],"lasting":[190],"artifact,":[191],"each":[193],"stage":[194],"above":[195],"one":[197],"of":[198],"its":[199],"arms.":[201]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-13T00:00:00"}