{"id":"https://openalex.org/W7164144120","doi":"https://doi.org/10.48550/arxiv.2606.10653","title":"STEDiff: Strengthening Text Embedding for Text-to-Image Alignment in Diffusion Model","display_name":"STEDiff: Strengthening Text Embedding for Text-to-Image Alignment in Diffusion Model","publication_year":2026,"publication_date":"2026-06-09","ids":{"openalex":"https://openalex.org/W7164144120","doi":"https://doi.org/10.48550/arxiv.2606.10653"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.10653","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.10653","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.2606.10653","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138340219","display_name":"Hailan Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Hailan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138300725","display_name":"Haipeng Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Haipeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138335818","display_name":"Bo Fu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fu, Bo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138387567","display_name":"Yang Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yang","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":0.8711000084877014,"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":0.8711000084877014,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.06970000267028809,"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/T12377","display_name":"Digital Humanities and Scholarship","score":0.003800000064074993,"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/semantics","display_name":"Semantics (computer science)","score":0.728600025177002},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6087999939918518},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5188000202178955},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.48159998655319214},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.4390000104904175},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4228000044822693}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7613999843597412},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.728600025177002},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6087999939918518},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5188000202178955},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.48159998655319214},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4636000096797943},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.4390000104904175},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4228000044822693},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4133000075817108},{"id":"https://openalex.org/C90312973","wikidata":"https://www.wikidata.org/wiki/Q7449052","display_name":"Semantic data model","level":2,"score":0.39250001311302185},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.33889999985694885},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3310999870300293},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.3089999854564667},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.29580000042915344},{"id":"https://openalex.org/C198942812","wikidata":"https://www.wikidata.org/wiki/Q496618","display_name":"Semantic property","level":2,"score":0.27869999408721924},{"id":"https://openalex.org/C45357846","wikidata":"https://www.wikidata.org/wiki/Q2001982","display_name":"Notation","level":2,"score":0.2685999870300293},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.25839999318122864}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.10653","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.10653","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.2606.10653","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.10653","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":[{"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth","score":0.6957876682281494}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Although":[0],"pretrained":[1],"text-to-image":[2],"(T2I)":[3],"generation":[4,158],"models":[5],"can":[6],"produce":[7],"high-quality":[8],"images,":[9],"they":[10],"often":[11],"fail":[12],"to":[13,23,42,46,53,77,97,122,136],"faithfully":[14],"reflect":[15],"the":[16,35,83,94,99,107,111,128,147],"semantic":[17,55,79,117,155],"intent":[18],"of":[19,102,130],"complex":[20,161],"prompts":[21],"due":[22],"stochastic":[24],"noise":[25],"and":[26,104,143,157],"inherent":[27],"model":[28,36],"limitations.":[29],"This":[30],"issue":[31],"frequently":[32],"manifests":[33],"as":[34,54],"overlooking":[37],"specific":[38],"objects":[39],"or":[40,66],"failing":[41],"correctly":[43],"bind":[44],"attributes":[45],"their":[47,137],"corresponding":[48,108],"entities,":[49],"a":[50,73,89,115],"challenge":[51],"referred":[52],"alignment.":[56],"Unlike":[57],"existing":[58],"approaches":[59],"that":[60,91,127,150],"rely":[61],"on":[62,146],"computationally":[63],"expensive":[64],"fine-tuning":[65],"labor-intensive":[67],"layout":[68],"priors,":[69],"we":[70,87],"propose":[71],"STEDiff,":[72],"training-free":[74],"method":[75,90,152],"designed":[76],"enhance":[78],"representations":[80],"directly":[81],"within":[82],"text-embedding":[84],"space.":[85],"Specifically,":[86],"introduce":[88],"primarily":[92],"leverages":[93],"[EOT]":[95],"token":[96],"strengthen":[98],"relevant":[100],"semantics":[101,129],"sub-sentences":[103],"then":[105],"replaces":[106],"tokens":[109],"in":[110,160],"original":[112],"prompt.":[113],"Furthermore,":[114],"novel":[116],"enhancement":[118],"loss":[119],"is":[120],"incorporated":[121],"enforce":[123],"spatial":[124],"constraints,":[125],"ensuring":[126],"each":[131],"entity":[132],"are":[133],"precisely":[134],"mapped":[135],"respective":[138],"image":[139],"regions.":[140],"Extensive":[141],"quantitative":[142],"qualitative":[144],"evaluations":[145],"T2I-CompBench":[148],"demonstrate":[149],"our":[151],"notably":[153],"improves":[154],"consistency":[156],"integrity":[159],"scenarios.":[162]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-11T00:00:00"}