{"id":"https://openalex.org/W7204239225","doi":"https://doi.org/10.48550/arxiv.2608.24361","title":"Adaptive Influence Graphs for Failure Attribution in Multi-Agent Systems","display_name":"Adaptive Influence Graphs for Failure Attribution in Multi-Agent Systems","publication_year":2026,"publication_date":"2026-08-25","ids":{"openalex":"https://openalex.org/W7204239225","doi":"https://doi.org/10.48550/arxiv.2608.24361"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2608.24361","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.24361","pdf_url":"https://arxiv.org/pdf/2608.24361","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,"listed_in":[],"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2608.24361","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5119977850","display_name":"Yarden Bakish","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I16391192","display_name":"Tel Aviv University","ror":"https://ror.org/04mhzgx49","country_code":"IL","type":"education","lineage":["https://openalex.org/I16391192"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Bakish, Yarden","raw_affiliation_strings":["Tel Aviv University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tel Aviv University","institution_ids":["https://openalex.org/I16391192"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023379329","display_name":"Amir Dudai","orcid":"https://orcid.org/0000-0003-0417-1619","observed_orcids":["https://orcid.org/0000-0003-0417-1619"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dudai, Amir","raw_affiliation_strings":["AWS Agentic AI"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AWS Agentic AI","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091239620","display_name":"Roy Ganz","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ganz, Roy","raw_affiliation_strings":["AWS Agentic AI"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AWS Agentic AI","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075513070","display_name":"Oren Nuriel","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nuriel, Oren","raw_affiliation_strings":["AWS Agentic AI"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AWS Agentic AI","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093673271","display_name":"Elad Ben Avraham","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Avraham, Elad Ben","raw_affiliation_strings":["AWS Agentic AI"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AWS Agentic AI","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034589843","display_name":"Mor Shpigel Nacson","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nacson, Mor Shpigel","raw_affiliation_strings":["AWS Agentic AI"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AWS Agentic AI","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053244815","display_name":"Ron Litman","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Litman, Ron","raw_affiliation_strings":["AWS Agentic AI"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AWS Agentic AI","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":2,"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/T12127","display_name":"Software System Performance and Reliability","score":0.8916000127792358,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T12127","display_name":"Software System Performance and Reliability","score":0.8916000127792358,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10743","display_name":"Software Testing and Debugging Techniques","score":0.07029999792575836,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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/T10260","display_name":"Software Engineering Research","score":0.006200000178068876,"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/failure-attribution","display_name":"failure attribution","score":0.9610000252723694},{"id":"https://openalex.org/keywords/multi-agent-systems","display_name":"multi-agent systems","score":0.9309999942779541},{"id":"https://openalex.org/keywords/llm-based-agents","display_name":"LLM agents","score":0.6259999871253967},{"id":"https://openalex.org/keywords/trace-representation","display_name":"trace representation","score":0.6740000247955322},{"id":"https://openalex.org/keywords/graph-construction","display_name":"graph construction","score":0.5460000038146973},{"id":"https://openalex.org/keywords/error-localization","display_name":"error localization","score":0.6549999713897705},{"id":"https://openalex.org/keywords/observability","display_name":"observability","score":0.48399999737739563},{"id":"https://openalex.org/keywords/multi-agent-llm-systems","display_name":"multi-agent LLM systems","score":0.652999997138977}],"concepts":[{"id":"https://openalex.org/C168065819","wikidata":"https://www.wikidata.org/wiki/Q845566","display_name":"Debugging","level":2,"score":0.7297000288963318},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.7293999791145325},{"id":"https://openalex.org/C36299963","wikidata":"https://www.wikidata.org/wiki/Q1369844","display_name":"Observability","level":2,"score":0.6687999963760376},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6218000054359436},{"id":"https://openalex.org/C143299363","wikidata":"https://www.wikidata.org/wiki/Q900584","display_name":"Attribution","level":2,"score":0.4596000015735626},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.45010000467300415},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.44670000672340393},{"id":"https://openalex.org/C140745168","wikidata":"https://www.wikidata.org/wiki/Q1210082","display_name":"Tree traversal","level":2,"score":0.42179998755455017},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.4185999929904938},{"id":"https://openalex.org/C136643341","wikidata":"https://www.wikidata.org/wiki/Q1361526","display_name":"Reachability","level":2,"score":0.3490999937057495},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.34610000252723694},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.34209999442100525},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31310001015663147},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.29789999127388},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.2865999937057495},{"id":"https://openalex.org/C26713055","wikidata":"https://www.wikidata.org/wiki/Q245962","display_name":"Implementation","level":2,"score":0.28360000252723694},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.2831000089645386},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.2791999876499176},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2770000100135803},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2734000086784363},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.2685999870300293},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.2685000002384186},{"id":"https://openalex.org/C197947376","wikidata":"https://www.wikidata.org/wiki/Q5155608","display_name":"Comparability","level":2,"score":0.2630999982357025},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.2596000134944916},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.2500999867916107}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2608.24361","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.24361","pdf_url":"https://arxiv.org/pdf/2608.24361","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,"listed_in":[],"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2608.24361","doi":"https://doi.org/10.48550/arxiv.2608.24361","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2608.24361","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,"listed_in":[],"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2608.24361","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.24361","pdf_url":"https://arxiv.org/pdf/2608.24361","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,"listed_in":[],"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7204239225.pdf","grobid_xml":"https://content.openalex.org/works/W7204239225.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W4387559176","https://openalex.org/W4387799916","https://openalex.org/W4391876619","https://openalex.org/W4403996099","https://openalex.org/W4414597217","https://openalex.org/W4414972653","https://openalex.org/W4415336027","https://openalex.org/W4416716969","https://openalex.org/W4417070626","https://openalex.org/W6948524426","https://openalex.org/W7127528697","https://openalex.org/W7133222082","https://openalex.org/W7140103799","https://openalex.org/W7141713967","https://openalex.org/W7154201446","https://openalex.org/W7160865650","https://openalex.org/W7160896442","https://openalex.org/W7161680277","https://openalex.org/W7163179117","https://openalex.org/W7163637799","https://openalex.org/W7164885673","https://openalex.org/W7166683690","https://openalex.org/W7166819471"],"related_works":["https://openalex.org/W7157506569","https://openalex.org/W7090833590","https://openalex.org/W4416716969","https://openalex.org/W7211867988","https://openalex.org/W7160865650","https://openalex.org/W7133222082","https://openalex.org/W7137802010","https://openalex.org/W7203895559","https://openalex.org/W7163179117","https://openalex.org/W7204931061"],"abstract_inverted_index":{"Multi-agent":[0],"LLM":[1],"systems":[2,39],"are":[3],"increasingly":[4],"deployed":[5],"in":[6],"real-world":[7],"applications,":[8],"where":[9],"failures":[10],"can":[11,66],"be":[12],"costly":[13],"and":[14,55,96,122,167],"difficult":[15],"to":[16,21,45,57,100],"localize.":[17],"Despite":[18],"growing":[19],"efforts":[20],"automate":[22],"failure":[23,116,144],"attribution,":[24,117],"diagnosing":[25,157],"failed":[26,90],"runs":[27],"still":[28],"largely":[29],"relies":[30],"on":[31,137,155,161],"human":[32],"engineers.":[33],"Yet":[34],"engineers":[35],"rarely":[36],"debug":[37],"complex":[38],"by":[40],"reading":[41],"raw":[42],"logs":[43],"end":[44],"end.":[46],"Instead,":[47],"observability":[48],"tools":[49],"organize":[50],"traces":[51],"around":[52],"components,":[53],"actions,":[54],"dependencies":[56],"support":[58],"targeted":[59],"navigation.":[60],"We":[61],"hypothesize":[62],"that":[63,86,110,150],"modern":[64],"LLMs":[65],"benefit":[67],"from":[68],"the":[69,102,126,135,139,156,163],"same":[70],"paradigm.":[71],"To":[72],"test":[73],"this":[74],"hypothesis,":[75],"we":[76,108],"introduce":[77],"Adaptive":[78],"Influence":[79],"Graphs":[80],"(AIGs),":[81],"a":[82,89,93,131],"two-stage":[83],"agentic":[84],"framework":[85],"first":[87],"transforms":[88],"trace":[91,112,164],"into":[92],"structured":[94],"graph":[95,120],"then":[97],"navigates":[98],"it":[99],"identify":[101],"critical":[103],"error.":[104],"Across":[105],"multiple":[106],"models,":[107],"show":[109],"richer":[111],"representations":[113],"consistently":[114],"improve":[115],"with":[118],"adaptive":[119],"construction":[121],"agent-directed":[123],"traversal":[124],"yielding":[125],"strongest":[127],"results.":[128],"AIGs":[129],"establish":[130],"new":[132],"state":[133],"of":[134],"art":[136],"Who&When,":[138],"standard":[140],"benchmark":[141],"for":[142],"multi-agent":[143],"attribution.":[145],"This":[146],"affirms":[147],"our":[148],"hypothesis":[149],"attribution":[151],"depends":[152],"not":[153],"only":[154],"model,":[158],"but":[159],"also":[160],"how":[162],"is":[165],"represented":[166],"explored.":[168]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-08-27T00:00:00"}