{"id":"https://openalex.org/W7163671870","doi":"https://doi.org/10.48550/arxiv.2606.06267","title":"Many Circuits, One Mechanism: Input Variation and Evaluation Granularity in Circuit Discovery","display_name":"Many Circuits, One Mechanism: Input Variation and Evaluation Granularity in Circuit Discovery","publication_year":2026,"publication_date":"2026-06-04","ids":{"openalex":"https://openalex.org/W7163671870","doi":"https://doi.org/10.48550/arxiv.2606.06267"},"language":"en","primary_location":{"id":"pmh:oai:tubiblio.ulb.tu-darmstadt.de:161176","is_oa":false,"landing_page_url":"http://tubiblio.ulb.tu-darmstadt.de/view/person/Makou=3AAlireza_Bayat=3A=3A.html>","pdf_url":null,"source":{"id":"https://openalex.org/S4377196390","display_name":"TUbilio (Technical University of Darmstadt)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I31512782","host_organization_name":"Technische Universit\u00e4t Darmstadt","host_organization_lineage":["https://openalex.org/I31512782"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"Report"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.06267","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012918168","display_name":"Alireza Bayat Makou","orcid":"https://orcid.org/0009-0000-7849-2488"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Makou, Alireza Bayat","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047674908","display_name":"Jingcheng Niu","orcid":"https://orcid.org/0000-0002-2358-9466"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Niu, Jingcheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023507685","display_name":"Subhabrata Dutta","orcid":"https://orcid.org/0000-0002-0730-0685"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dutta, Subhabrata","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137950586","display_name":"Iryna Gurevych","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gurevych, Iryna","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/T11948","display_name":"Machine Learning in Materials Science","score":0.14489999413490295,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.14489999413490295,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.0763000026345253,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.06310000270605087,"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/granularity","display_name":"Granularity","score":0.6640999913215637},{"id":"https://openalex.org/keywords/equivalence","display_name":"Equivalence (formal languages)","score":0.5253999829292297},{"id":"https://openalex.org/keywords/electronic-circuit","display_name":"Electronic circuit","score":0.5120000243186951},{"id":"https://openalex.org/keywords/network-analysis","display_name":"Network analysis","score":0.4027000069618225},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.36550000309944153},{"id":"https://openalex.org/keywords/transfer","display_name":"Transfer (computing)","score":0.36399999260902405},{"id":"https://openalex.org/keywords/variation","display_name":"Variation (astronomy)","score":0.36250001192092896},{"id":"https://openalex.org/keywords/core","display_name":"Core (optical fiber)","score":0.36160001158714294},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.3544999957084656}],"concepts":[{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.6640999913215637},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5758000016212463},{"id":"https://openalex.org/C2780069185","wikidata":"https://www.wikidata.org/wiki/Q7977945","display_name":"Equivalence (formal languages)","level":2,"score":0.5253999829292297},{"id":"https://openalex.org/C134146338","wikidata":"https://www.wikidata.org/wiki/Q1815901","display_name":"Electronic circuit","level":2,"score":0.5120000243186951},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4819999933242798},{"id":"https://openalex.org/C32946077","wikidata":"https://www.wikidata.org/wiki/Q618079","display_name":"Network analysis","level":2,"score":0.4027000069618225},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3917999863624573},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.36550000309944153},{"id":"https://openalex.org/C2776175482","wikidata":"https://www.wikidata.org/wiki/Q1195816","display_name":"Transfer (computing)","level":2,"score":0.36399999260902405},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.36250001192092896},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.36160001158714294},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.3544999957084656},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.3521000146865845},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.3508000075817108},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.34599998593330383},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.32739999890327454},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31790000200271606},{"id":"https://openalex.org/C2777044963","wikidata":"https://www.wikidata.org/wiki/Q5384707","display_name":"Equivalence class (music)","level":2,"score":0.2847000062465668},{"id":"https://openalex.org/C187075797","wikidata":"https://www.wikidata.org/wiki/Q173245","display_name":"Sequential logic","level":3,"score":0.2800999879837036},{"id":"https://openalex.org/C112313634","wikidata":"https://www.wikidata.org/wiki/Q7886648","display_name":"Complement (music)","level":5,"score":0.2775000035762787},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.2718999981880188},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.2685000002384186},{"id":"https://openalex.org/C193244246","wikidata":"https://www.wikidata.org/wiki/Q5432696","display_name":"False discovery rate","level":3,"score":0.2662999927997589},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2639000117778778},{"id":"https://openalex.org/C2779151265","wikidata":"https://www.wikidata.org/wiki/Q1156791","display_name":"Copying","level":2,"score":0.25679999589920044},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2549999952316284},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.25200000405311584},{"id":"https://openalex.org/C17231256","wikidata":"https://www.wikidata.org/wiki/Q5156540","display_name":"Completeness (order theory)","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:tubiblio.ulb.tu-darmstadt.de:161176","is_oa":false,"landing_page_url":"http://tubiblio.ulb.tu-darmstadt.de/view/person/Makou=3AAlireza_Bayat=3A=3A.html>","pdf_url":null,"source":{"id":"https://openalex.org/S4377196390","display_name":"TUbilio (Technical University of Darmstadt)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I31512782","host_organization_name":"Technische Universit\u00e4t Darmstadt","host_organization_lineage":["https://openalex.org/I31512782"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"Report"},{"id":"doi:10.48550/arxiv.2606.06267","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.06267","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2606.06267","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.06267","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":{"Circuit":[0],"discovery":[1,133],"methods":[2],"identify":[3],"subgraphs":[4,142],"that":[5,39,83,115,132,174,187],"explain":[6],"specific":[7],"model":[8],"behaviors,":[9],"and":[10,37,81,110,186,193],"structural":[11,42,175],"differences":[12,43,176],"between":[13,177],"discovered":[14],"circuits":[15,80,86,178],"are":[16,118,179],"commonly":[17],"interpreted":[18],"as":[19],"evidence":[20,182],"of":[21,107,140],"distinct":[22,85,184],"mechanisms.":[23],"We":[24],"test":[25],"this":[26,153,189],"assumption":[27],"by":[28],"varying":[29],"input":[30],"statistics":[31],"while":[32,160],"holding":[33],"the":[34,40,88,126,164],"task":[35],"fixed,":[36],"show":[38,173],"resulting":[41],"exhibit":[44],"apparent":[45,158],"specialization":[46],"but":[47],"do":[48],"not":[49,180],"correspond":[50],"to":[51,169],"functional":[52],"differences,":[53],"a":[54,69,97,146],"pattern":[55],"we":[56,77],"term":[57],"phantom":[58],"specialization.":[59],"Using":[60],"Literal":[61],"Sequence":[62],"Copying":[63],"across":[64,95,100,120],"four":[65],"token-frequency":[66],"bands":[67,102],"plus":[68],"control":[70],"condition":[71],"in":[72],"five":[73],"Pythia":[74],"models":[75],"(70M-1.4B),":[76],"extract":[78],"75":[79],"find":[82],"structurally":[84],"implement":[87],"same":[89,127],"computation:":[90],"band-specific":[91],"edges":[92],"transfer":[93,195],"broadly":[94],"bands,":[96],"core":[98],"shared":[99],"most":[101],"recovers":[103],"at":[104],"least":[105],"99%":[106],"circuit":[108],"performance,":[109],"causal":[111],"interchange":[112],"interventions":[113],"confirm":[114],"internal":[116],"representations":[117],"interchangeable":[119],"frequency":[121,128],"bands.":[122],"Repeated":[123],"extractions":[124],"within":[125],"band":[129],"further":[130],"suggest":[131],"algorithms":[134],"sample":[135],"from":[136,167],"an":[137],"equivalence":[138],"class":[139],"valid":[141],"rather":[143],"than":[144],"recovering":[145],"unique":[147],"mechanism.":[148],"Standard":[149],"evaluation":[150,156,162,192],"practice":[151],"obscures":[152],"pattern:":[154],"source-level":[155],"inflates":[157],"faithfulness,":[159],"edge-level":[161,191],"reveals":[163],"many-to-one":[165],"mapping":[166],"structure":[168],"function.":[170],"Our":[171],"results":[172],"sufficient":[181],"for":[183],"mechanisms,":[185],"exposing":[188],"requires":[190],"cross-condition":[194],"tests.":[196]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-06T00:00:00"}