{"id":"https://openalex.org/W7171802455","doi":"https://doi.org/10.48550/arxiv.2607.26735","title":"Dual Inversion for Text-to-Image Diffusion Models: From Both Prompt and Noise Perspectives","display_name":"Dual Inversion for Text-to-Image Diffusion Models: From Both Prompt and Noise Perspectives","publication_year":2026,"publication_date":"2026-07-29","ids":{"openalex":"https://openalex.org/W7171802455","doi":"https://doi.org/10.48550/arxiv.2607.26735"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.26735","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.26735","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.2607.26735","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5144082083","display_name":"Xiaolong Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Xiaolong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5143998883","display_name":"Junjian Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Junjian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5144015788","display_name":"Yuan Xiao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiao, Yuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5144010094","display_name":"Jiaqi Deng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Deng, Jiaqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5144014912","display_name":"Dayong Ye","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ye, Dayong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5144064275","display_name":"Tianqing Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Tianqing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5102878677","display_name":"Huan Huo","orcid":"https://orcid.org/0000-0003-2440-714X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huo, Huan","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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.8331999778747559,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.8331999778747559,"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/T12859","display_name":"Cell Image Analysis Techniques","score":0.02759999968111515,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"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/T12377","display_name":"Digital Humanities and Scholarship","score":0.012799999676644802,"subfield":{"id":"https://openalex.org/subfields/1208","display_name":"Literature and Literary Theory"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/inversion","display_name":"Inversion (geology)","score":0.7199000120162964},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.646399974822998},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5623000264167786},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.43130001425743103},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.35740000009536743},{"id":"https://openalex.org/keywords/high-fidelity","display_name":"High fidelity","score":0.3465999960899353},{"id":"https://openalex.org/keywords/inverse-problem","display_name":"Inverse problem","score":0.33320000767707825},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.3228999972343445}],"concepts":[{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.7199000120162964},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.646399974822998},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6388999819755554},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5738000273704529},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5623000264167786},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.43130001425743103},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4250999987125397},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39579999446868896},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.35740000009536743},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.3465999960899353},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.33320000767707825},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.3228999972343445},{"id":"https://openalex.org/C207850805","wikidata":"https://www.wikidata.org/wiki/Q269608","display_name":"Reverse engineering","level":2,"score":0.3075999915599823},{"id":"https://openalex.org/C2909457774","wikidata":"https://www.wikidata.org/wiki/Q4117845","display_name":"Noise effects","level":3,"score":0.30160000920295715},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.28690001368522644},{"id":"https://openalex.org/C35772409","wikidata":"https://www.wikidata.org/wiki/Q1323086","display_name":"Image noise","level":3,"score":0.28299999237060547},{"id":"https://openalex.org/C205372313","wikidata":"https://www.wikidata.org/wiki/Q355645","display_name":"Latent image","level":3,"score":0.2800000011920929},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.2736000120639801},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.2718000113964081},{"id":"https://openalex.org/C3020402766","wikidata":"https://www.wikidata.org/wiki/Q104376712","display_name":"Prior information","level":2,"score":0.26989999413490295},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.26919999718666077},{"id":"https://openalex.org/C100675267","wikidata":"https://www.wikidata.org/wiki/Q1371624","display_name":"Background noise","level":2,"score":0.2639000117778778},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2556000053882599}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.26735","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.26735","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.2607.26735","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.26735","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":{"Prompt":[0],"inversion,":[1],"as":[2,78],"a":[3,79,103,135,199],"typical":[4],"reverse":[5,83],"engineering":[6],"technique,":[7],"enables":[8,171],"text-to-image":[9],"(T2I)":[10],"diffusion":[11],"models":[12],"to":[13,56,61,133],"generate":[14],"the":[15,62,71,86,90,110,117,121,141,148,153,157,160,168,203],"desired":[16],"target":[17,118,154],"images":[18,43],"without":[19,175],"extensive":[20],"prompt":[21,25,76,112],"engineering.":[22],"However,":[23],"existing":[24],"inversion":[26,77,146],"methods":[27,34,49],"suffer":[28],"from":[29,74],"significant":[30],"limitations:":[31],"(1)":[32],"gradient-based":[33],"are":[35],"unstable":[36],"and":[37,113,129,190,205],"uninterpretable,":[38],"often":[39],"resulting":[40],"in":[41],"generated":[42],"with":[44],"severe":[45],"artifacts;":[46],"(2)":[47],"gradient-free":[48],"yield":[50],"human-readable":[51],"prompts":[52,189],"but":[53],"still":[54],"fail":[55],"preserve":[57],"visual":[58],"fidelity":[59],"due":[60],"lack":[63],"of":[64,89,116,152],"fine-grained":[65],"detail":[66],"alignment.":[67],"We":[68],"contend":[69],"that":[70,93,106,167,183],"limitations":[72],"stem":[73],"treating":[75],"sufficient":[80],"condition":[81],"for":[82,202],"engineering,":[84],"ignoring":[85],"critical":[87],"role":[88],"latent":[91,114,150],"noise":[92,115,151,170],"encodes":[94],"structural":[95,161],"information.":[96],"Consequently,":[97],"we":[98,124,165],"propose":[99],"Dualin":[100,184,196],"(Dual":[101],"inversion),":[102],"two-stage":[104],"method":[105],"jointly":[107],"recovers":[108],"both":[109],"semantic":[111],"image.":[119],"In":[120,140],"first":[122],"stage,":[123,143],"integrate":[125],"vision-language":[126],"model,":[127],"CLIP":[128],"large":[130],"language":[131],"model":[132],"invert":[134],"faithful,":[136],"human-interpretable":[137],"hard":[138],"prompt.":[139],"second":[142],"unconditional":[144],"DDIM":[145],"reconstructs":[147],"exact":[149],"image,":[155],"guaranteeing":[156],"consistency":[158],"at":[159],"information":[162],"level.":[163],"Theoretically,":[164],"prove":[166],"inverted":[169,188],"flexible":[172],"image":[173,193,207],"editing":[174],"re-optimization.":[176],"Extensive":[177],"experiments":[178],"on":[179],"diverse":[180],"datasets":[181],"demonstrate":[182],"simultaneously":[185],"generates":[186],"high-quality":[187],"achieves":[191],"state-of-the-art":[192],"fidelity.":[194],"Additionally,":[195],"can":[197],"establish":[198],"robust":[200],"foundation":[201],"precise":[204],"controllable":[206],"editing.":[208]},"counts_by_year":[],"updated_date":"2026-07-31T08:31:51.225901","created_date":"2026-07-31T00:00:00"}