{"id":"https://openalex.org/W7163047287","doi":"https://doi.org/10.48550/arxiv.2605.30745","title":"Immuno-VLM: Immunizing Large Vision-Language Models via Generative Semantic Antibodies for Open-World Trustworthiness","display_name":"Immuno-VLM: Immunizing Large Vision-Language Models via Generative Semantic Antibodies for Open-World Trustworthiness","publication_year":2026,"publication_date":"2026-05-29","ids":{"openalex":"https://openalex.org/W7163047287","doi":"https://doi.org/10.48550/arxiv.2605.30745"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.30745","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30745","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.2605.30745","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137555996","display_name":"Xiang Fang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fang, Xiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113067511","display_name":"Wanlong Fang","orcid":"https://orcid.org/0000-0003-4480-3107"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fang, Wanlong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137565435","display_name":"Wei Ji","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ji, Wei","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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.2879999876022339,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.2879999876022339,"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/T12576","display_name":"vaccines and immunoinformatics approaches","score":0.22949999570846558,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.09780000150203705,"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/generative-grammar","display_name":"Generative grammar","score":0.6014999747276306},{"id":"https://openalex.org/keywords/abstraction","display_name":"Abstraction","score":0.5956000089645386},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.5656999945640564},{"id":"https://openalex.org/keywords/hallucinating","display_name":"Hallucinating","score":0.559499979019165},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5396999716758728},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.41110000014305115},{"id":"https://openalex.org/keywords/trustworthiness","display_name":"Trustworthiness","score":0.3846000134944916},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.32109999656677246}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7444000244140625},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6455000042915344},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.6014999747276306},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.5956000089645386},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.5656999945640564},{"id":"https://openalex.org/C2911011789","wikidata":"https://www.wikidata.org/wiki/Q130741","display_name":"Hallucinating","level":2,"score":0.559499979019165},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5396999716758728},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44780001044273376},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.41110000014305115},{"id":"https://openalex.org/C153701036","wikidata":"https://www.wikidata.org/wiki/Q659974","display_name":"Trustworthiness","level":2,"score":0.3846000134944916},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.38040000200271606},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.32109999656677246},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.2996000051498413},{"id":"https://openalex.org/C95713431","wikidata":"https://www.wikidata.org/wiki/Q631425","display_name":"Vulnerability (computing)","level":2,"score":0.2897000014781952},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.28839999437332153},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.2847999930381775},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.2840000092983246},{"id":"https://openalex.org/C2777946921","wikidata":"https://www.wikidata.org/wiki/Q7449044","display_name":"Semantic analysis (machine learning)","level":2,"score":0.27950000762939453},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.2773999869823456},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.25369998812675476},{"id":"https://openalex.org/C2777366796","wikidata":"https://www.wikidata.org/wiki/Q6017758","display_name":"Indeterminacy (philosophy)","level":2,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.30745","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30745","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.2605.30745","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30745","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":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.7719153761863708}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0,100],"Vision-Language":[1],"Models":[2,102],"have":[3],"achieved":[4],"unprecedented":[5],"success":[6],"in":[7,26],"zero-shot":[8],"recognition":[9],"by":[10],"aligning":[11],"visual":[12],"features":[13],"with":[14,41],"broad":[15],"semantic":[16,20],"concepts.":[17],"However,":[18],"this":[19,54],"abstraction":[21],"creates":[22],"a":[23,61,138],"critical":[24],"vulnerability":[25],"open-world":[27],"deployment:":[28],"the":[29,46,66,96,120],"``Hubris":[30],"of":[31,48,69,99,110,123],"Semantics'',":[32],"where":[33],"models":[34],"force-fit":[35],"unknown":[36],"anomalies":[37],"into":[38],"known":[39,124],"categories":[40],"high":[42],"confidence":[43],"due":[44],"to":[45,73,103],"lack":[47],"explicit":[49],"negative":[50],"knowledge.":[51],"To":[52],"address":[53],"\\textit{Open-World":[55],"Trustworthiness":[56],"Paradox},":[57],"we":[58],"propose":[59],"\\textbf{Immuno-VLM},":[60],"bio-inspired":[62],"framework":[63],"that":[64,83,117,135],"adapts":[65],"biological":[67],"principle":[68],"\\textbf{Immunological":[70],"Negative":[71],"Selection}":[72],"high-dimensional":[74],"latent":[75],"spaces.":[76],"Departing":[77],"from":[78],"traditional":[79],"Open-Set":[80],"Recognition":[81],"methods":[82],"rely":[84],"on":[85,127],"passive":[86],"density":[87],"estimation":[88],"or":[89],"inefficient":[90],"pixel-space":[91],"outlier":[92],"generation,":[93],"Immuno-VLM":[94,136],"leverages":[95],"generative":[97],"reasoning":[98],"Language":[101],"actively":[104],"hallucinate":[105],"``Semantic":[106],"Antibodies'',":[107],"textual":[108],"descriptions":[109],"near-distribution":[111],"outliers":[112],"(e.g.,":[113],"look-alikes,":[114],"contextual":[115],"anomalies)":[116],"effectively":[118],"bound":[119],"decision":[121],"space":[122],"classes.Extensive":[125],"experiments":[126],"ImageNet-1K":[128],"and":[129],"four":[130],"challenging":[131],"OOD":[132],"benchmarks":[133],"reveal":[134],"establishes":[137],"new":[139],"state-of-the-art.":[140]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-02T00:00:00"}