{"id":"https://openalex.org/W7133526889","doi":"https://doi.org/10.48550/arxiv.2603.03163","title":"Conditioned Activation Transport for T2I Safety Steering","display_name":"Conditioned Activation Transport for T2I Safety Steering","publication_year":2026,"publication_date":"2026-03-03","ids":{"openalex":"https://openalex.org/W7133526889","doi":"https://doi.org/10.48550/arxiv.2603.03163"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.03163","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.03163","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.03163","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128112452","display_name":"Maciej Chrab\u0105szcz","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chrab\u0105szcz, Maciej","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128113022","display_name":"Aleksander Szymczyk","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Szymczyk, Aleksander","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127807270","display_name":"Jan Dubinski","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dubi\u0144ski, Jan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128120591","display_name":"Tomasz Trzci\u0144ski","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Trzci\u0144ski, Tomasz","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128046105","display_name":"Franziska Boenisch","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Boenisch, Franziska","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5044067668","display_name":"Adam Dziedzic","orcid":"https://orcid.org/0000-0001-9786-2296"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dziedzic, Adam","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"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":0.699400007724762,"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":0.699400007724762,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.15449999272823334,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.015699999406933784,"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/conditioning","display_name":"Conditioning","score":0.4307999908924103},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.397599995136261},{"id":"https://openalex.org/keywords/interference","display_name":"Interference (communication)","score":0.3959999978542328},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3944999873638153},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.37790000438690186},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.3246999979019165},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.31929999589920044}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6331999897956848},{"id":"https://openalex.org/C45262634","wikidata":"https://www.wikidata.org/wiki/Q5159291","display_name":"Conditioning","level":2,"score":0.4307999908924103},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.397599995136261},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.3959999978542328},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3944999873638153},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.37790000438690186},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35589998960494995},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.3246999979019165},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.31929999589920044},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.31119999289512634},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.3109999895095825},{"id":"https://openalex.org/C2779679103","wikidata":"https://www.wikidata.org/wiki/Q5251805","display_name":"Degradation (telecommunications)","level":2,"score":0.3073999881744385},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2847000062465668},{"id":"https://openalex.org/C176856949","wikidata":"https://www.wikidata.org/wiki/Q2001676","display_name":"Offensive","level":2,"score":0.2800000011920929},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.2782000005245209},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.26100000739097595},{"id":"https://openalex.org/C3018929209","wikidata":"https://www.wikidata.org/wiki/Q1061983","display_name":"Safe driving","level":2,"score":0.25859999656677246},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.25850000977516174}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.03163","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.03163","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.03163","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.03163","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"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":{"Despite":[0],"their":[1],"impressive":[2],"capabilities,":[3],"current":[4],"Text-to-Image":[5],"(T2I)":[6],"models":[7],"remain":[8],"prone":[9],"to":[10,36,86,129],"generating":[11],"unsafe":[12,54,90],"and":[13,53,78,108,139],"toxic":[14],"content.":[15],"While":[16],"activation":[17,28,91],"steering":[18,29],"offers":[19],"a":[20,47,70,74],"promising":[21],"inference-time":[22],"intervention,":[23],"we":[24,43,64,93],"observe":[25],"that":[26,72,112],"linear":[27],"frequently":[30],"degrades":[31],"image":[32,126],"quality":[33],"when":[34],"applied":[35],"benign":[37,97],"prompts.":[38],"To":[39],"address":[40],"this":[41,62],"trade-off,":[42],"first":[44],"construct":[45],"SafeSteerDataset,":[46],"contrastive":[48],"dataset":[49],"containing":[50],"2300":[51],"safe":[52],"prompt":[55],"pairs":[56],"with":[57,96],"high":[58],"cosine":[59],"similarity.":[60],"Leveraging":[61],"data,":[63],"propose":[65],"Conditioned":[66],"Activation":[67],"Transport":[68],"(CAT),":[69],"framework":[71],"employs":[73],"geometry-based":[75],"conditioning":[76,83],"mechanism":[77],"nonlinear":[79],"transport":[80,84],"maps.":[81],"By":[82],"maps":[85],"activate":[87],"only":[88],"within":[89],"regions,":[92],"minimize":[94],"interference":[95],"queries.":[98],"We":[99],"validate":[100],"our":[101],"approach":[102],"on":[103],"two":[104],"state-of-the-art":[105],"architectures:":[106],"Z-Image":[107],"Infinity.":[109],"Experiments":[110],"demonstrate":[111],"CAT":[113],"generalizes":[114],"effectively":[115],"across":[116],"these":[117],"backbones,":[118],"significantly":[119],"reducing":[120],"Attack":[121],"Success":[122],"Rate":[123],"while":[124],"maintaining":[125],"fidelity":[127],"compared":[128],"unsteered":[130],"generations.":[131],"Warning:":[132],"This":[133],"paper":[134],"contains":[135],"potentially":[136],"offensive":[137],"text":[138],"images.":[140]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-05T00:00:00"}
