{"id":"https://openalex.org/W7148423206","doi":"https://doi.org/10.48550/arxiv.2604.01010","title":"PDA: Text-Augmented Defense Framework for Robust Vision-Language Models against Adversarial Image Attacks","display_name":"PDA: Text-Augmented Defense Framework for Robust Vision-Language Models against Adversarial Image Attacks","publication_year":2026,"publication_date":"2026-04-01","ids":{"openalex":"https://openalex.org/W7148423206","doi":"https://doi.org/10.48550/arxiv.2604.01010"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.01010","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.01010","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"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.01010","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5064845207","display_name":"Jingning Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Jingning","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036933266","display_name":"Haochen Luo","orcid":"https://orcid.org/0000-0002-8846-527X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Haochen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5132816732","display_name":"Chen Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Chen","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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9520999789237976,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9520999789237976,"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":0.014000000432133675,"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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.004100000020116568,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.9218999743461609},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.8356000185012817},{"id":"https://openalex.org/keywords/closed-captioning","display_name":"Closed captioning","score":0.7433000206947327},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6879000067710876},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3806999921798706},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.366100013256073}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.9218999743461609},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.8356000185012817},{"id":"https://openalex.org/C157657479","wikidata":"https://www.wikidata.org/wiki/Q2367247","display_name":"Closed captioning","level":3,"score":0.7433000206947327},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7038999795913696},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6879000067710876},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5501999855041504},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3968000113964081},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3806999921798706},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.366100013256073},{"id":"https://openalex.org/C140547941","wikidata":"https://www.wikidata.org/wiki/Q7797194","display_name":"Threat model","level":2,"score":0.3109000027179718},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2957000136375427},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.2858999967575073},{"id":"https://openalex.org/C41065033","wikidata":"https://www.wikidata.org/wiki/Q2825412","display_name":"Adversary","level":2,"score":0.26460000872612},{"id":"https://openalex.org/C2986492983","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image matching","level":3,"score":0.2581999897956848}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.01010","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.01010","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.2604.01010","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.01010","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Vision-language":[0],"models":[1],"(VLMs)":[2],"are":[3,19],"vulnerable":[4],"to":[5,25,27,47],"adversarial":[6,13,17,53,122],"image":[7,54],"perturbations.":[8],"Existing":[9],"works":[10],"based":[11],"on":[12,73,100],"training":[14],"against":[15,120],"task-specific":[16],"examples":[18],"computationally":[20],"expensive":[21],"and":[22,62,80,104,111,133],"often":[23],"fail":[24],"generalize":[26],"unseen":[28],"attack":[29],"types.":[30],"To":[31,77],"address":[32],"these":[33],"limitations,":[34],"we":[35,82],"introduce":[36],"Paraphrase-Decomposition-Aggregation":[37],"(PDA),":[38],"a":[39,130],"training-free":[40],"defense":[41,135],"framework":[42,136],"that":[43,87,114],"leverages":[44],"text":[45],"augmentation":[46],"enhance":[48],"VLM":[49,102],"robustness":[50,79,97,118],"under":[51],"diverse":[52],"attacks.":[55],"PDA":[56,84,115],"performs":[57],"prompt":[58],"paraphrasing,":[59],"question":[60,108],"decomposition,":[61],"consistency":[63],"aggregation":[64],"entirely":[65],"at":[66],"test":[67],"time,":[68],"thus":[69],"requiring":[70],"no":[71],"modification":[72],"the":[74,89],"underlying":[75],"models.":[76],"balance":[78],"efficiency,":[81],"instantiate":[83],"as":[85],"invariants":[86],"reduce":[88],"inference":[90],"cost":[91],"while":[92,124],"retaining":[93],"most":[94],"of":[95],"its":[96],"gains.":[98],"Experiments":[99],"multiple":[101],"architectures":[103],"benchmarks":[105],"for":[106,137],"visual":[107],"answering,":[109],"classification,":[110],"captioning":[112],"show":[113],"achieves":[116],"consistent":[117],"gains":[119],"various":[121],"perturbations":[123],"maintaining":[125],"competitive":[126],"clean":[127],"accuracy,":[128],"establishing":[129],"generic,":[131],"strong":[132],"practical":[134],"VLMs":[138],"during":[139],"inference.":[140]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-04-03T00:00:00"}
