{"id":"https://openalex.org/W7161935992","doi":"https://doi.org/10.48550/arxiv.2605.20682","title":"IndusAgent: Reinforcing Open-Vocabulary Industrial Anomaly Detection with Agentic Tools","display_name":"IndusAgent: Reinforcing Open-Vocabulary Industrial Anomaly Detection with Agentic Tools","publication_year":2026,"publication_date":"2026-05-20","ids":{"openalex":"https://openalex.org/W7161935992","doi":"https://doi.org/10.48550/arxiv.2605.20682"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.20682","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.20682","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":null,"license_id":null,"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.2605.20682","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136720448","display_name":"Rongbin Tan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tan, Rongbin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136712886","display_name":"Fangfang Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Fangfang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136629897","display_name":"Zhenlong Yuan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuan, Zhenlong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101927712","display_name":"Min Qiu","orcid":"https://orcid.org/0000-0002-2379-0194"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qiu, Min","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136651817","display_name":"Kejin Cui","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cui, Kejin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136707143","display_name":"Mengmeng Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Mengmeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136632199","display_name":"Y\u00ec Xi\u00e1ng J. W\u00e1ng","orcid":"https://orcid.org/0009-0005-0816-8152"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136628312","display_name":"Zijian Song","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Zijian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136668362","display_name":"Zhiyuan Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Zhiyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136709944","display_name":"Jiyuan Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Jiyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136680924","display_name":"Wang, Yue, 1973 Aug. 1-","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yue","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136635805","display_name":"Shuhan Song\u00a7","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song\u00a7, Shuhan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5061641694","display_name":"Huawei Cao","orcid":"https://orcid.org/0000-0003-2192-7115"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cao, Huawei","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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.8833000063896179,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.8833000063896179,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.042899999767541885,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.011300000362098217,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.777899980545044},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5329999923706055},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.49549999833106995},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4860999882221222},{"id":"https://openalex.org/keywords/hallucinating","display_name":"Hallucinating","score":0.47870001196861267},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4318000078201294},{"id":"https://openalex.org/keywords/bridging","display_name":"Bridging (networking)","score":0.42289999127388},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.3846000134944916}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.777899980545044},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6881999969482422},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.557200014591217},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5329999923706055},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.49549999833106995},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4860999882221222},{"id":"https://openalex.org/C2911011789","wikidata":"https://www.wikidata.org/wiki/Q130741","display_name":"Hallucinating","level":2,"score":0.47870001196861267},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46059998869895935},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4318000078201294},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.42289999127388},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.3846000134944916},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.38359999656677246},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.3653999865055084},{"id":"https://openalex.org/C2983787585","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature matching","level":3,"score":0.3650999963283539},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.33399999141693115},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.3260999917984009},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.3190999925136566},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.3158000111579895},{"id":"https://openalex.org/C2777508537","wikidata":"https://www.wikidata.org/wiki/Q7936620","display_name":"Visual reasoning","level":2,"score":0.3061000108718872},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.29330000281333923},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.26750001311302185},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26440000534057617},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.26109999418258667},{"id":"https://openalex.org/C2780695315","wikidata":"https://www.wikidata.org/wiki/Q3799040","display_name":"Unobservable","level":2,"score":0.25760000944137573}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.20682","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.20682","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.20682","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.20682","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":null,"license_id":null,"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":{"Multimodal":[0],"large":[1],"language":[2],"models":[3],"(MLLMs)":[4],"have":[5],"shown":[6],"remarkable":[7],"capability":[8],"in":[9,26],"bridging":[10],"visual":[11,67,115],"perception":[12],"and":[13,38,72,105,117,139,163,179],"textual":[14],"reasoning,":[15,138],"enabling":[16,109],"zero-shot":[17,170],"understanding":[18],"across":[19],"diverse":[20],"industrial":[21,28,84,155],"scenarios.":[22],"However,":[23],"their":[24],"performance":[25,171],"open-vocabulary":[27,54],"anomaly":[29,132,136,156],"detection":[30],"(IAD)":[31],"is":[32],"often":[33],"limited":[34],"by":[35],"domain-misaligned":[36],"reasoning":[37],"hallucinated":[39],"structural":[40],"inferences.":[41],"To":[42],"address":[43],"these":[44],"challenges,":[45],"we":[46,57,122],"propose":[47],"\\textbf{IndusAgent},":[48],"a":[49,61,93,124],"tool-augmented":[50],"agentic":[51],"framework":[52],"for":[53,78],"IAD.":[55],"Specifically,":[56],"first":[58],"construct":[59],"\\textbf{Indus-CoT},":[60],"structured":[62],"dataset":[63],"that":[64,129,144,166],"integrates":[65],"global":[66],"observations,":[68],"high-resolution":[69],"local":[70],"patches,":[71],"expert":[73],"normalcy":[74],"priors,":[75],"providing":[76],"supervision":[77],"fine-tuning":[79],"the":[80,110],"model":[81],"on":[82,88,153],"rigorous":[83],"inspection":[85],"trajectories.":[86],"Building":[87],"this,":[89],"IndusAgent":[90,167],"dynamically":[91],"orchestrates":[92],"set":[94],"of":[95],"external":[96],"tools,":[97],"including":[98,158],"dynamic":[99],"region":[100],"cropping,":[101],"high-frequency":[102],"feature":[103],"enhancement,":[104],"prior":[106],"retrieval,":[107],"thus":[108],"agent":[111],"to":[112],"actively":[113],"resolve":[114],"ambiguities":[116],"disentangle":[118],"subtle":[119],"anomalies.":[120],"Furthermore,":[121],"introduce":[123],"gated":[125],"reinforcement":[126],"learning":[127],"objective":[128],"jointly":[130],"optimizes":[131],"classification,":[133],"localization":[134],"accuracy,":[135],"type":[137],"efficient":[140],"tool":[141,145],"usage,":[142],"ensuring":[143],"invocation":[146],"occurs":[147],"only":[148],"when":[149],"beneficial.":[150],"Extensive":[151],"evaluations":[152],"five":[154],"benchmarks,":[157],"MVTec-AD,":[159],"VisA,":[160],"MPDD,":[161],"DTD,":[162],"SDD,":[164],"demonstrate":[165],"achieves":[168],"state-of-the-art":[169],"among":[172],"all":[173],"existing":[174],"methods,":[175],"validating":[176],"our":[177],"robustness":[178],"generalization":[180],"capacity.":[181]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-22T00:00:00"}
