{"id":"https://openalex.org/W7163578448","doi":"https://doi.org/10.48550/arxiv.2606.04457","title":"Imagine Before You Draw: Visual Prompt Engineering for Image Generation","display_name":"Imagine Before You Draw: Visual Prompt Engineering for Image Generation","publication_year":2026,"publication_date":"2026-06-03","ids":{"openalex":"https://openalex.org/W7163578448","doi":"https://doi.org/10.48550/arxiv.2606.04457"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.04457","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.04457","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.2606.04457","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026004365","display_name":"Liyu Jia","orcid":"https://orcid.org/0000-0002-0275-7862"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jia, Liyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028794630","display_name":"Fengda Zhang","orcid":"https://orcid.org/0000-0001-5280-413X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Fengda","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065665560","display_name":"Jiachun Pan","orcid":"https://orcid.org/0000-0002-7573-0222"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pan, Jiachun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124909181","display_name":"Kesen Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Kesen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137837523","display_name":"Saining Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Saining","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137885847","display_name":"Wang Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Wang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137909890","display_name":"Weijia Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Weijia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137866542","display_name":"Yue Liao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liao, Yue","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041431476","display_name":"Aojun Zhou","orcid":"https://orcid.org/0000-0002-4742-8624"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Aojun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137819327","display_name":"Hanwang Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Hanwang","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":0.7444999814033508,"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":0.7444999814033508,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.04190000146627426,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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":0.03519999980926514,"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/bottleneck","display_name":"Bottleneck","score":0.6025999784469604},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.5741000175476074},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5088000297546387},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4372999966144562},{"id":"https://openalex.org/keywords/semantic-data-model","display_name":"Semantic data model","score":0.41780000925064087},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.37880000472068787},{"id":"https://openalex.org/keywords/image-editing","display_name":"Image editing","score":0.36489999294281006}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8686000108718872},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.6025999784469604},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.5741000175476074},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5393000245094299},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5088000297546387},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4408000111579895},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4372999966144562},{"id":"https://openalex.org/C90312973","wikidata":"https://www.wikidata.org/wiki/Q7449052","display_name":"Semantic data model","level":2,"score":0.41780000925064087},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.37880000472068787},{"id":"https://openalex.org/C2776674983","wikidata":"https://www.wikidata.org/wiki/Q545981","display_name":"Image editing","level":3,"score":0.36489999294281006},{"id":"https://openalex.org/C86034646","wikidata":"https://www.wikidata.org/wiki/Q474311","display_name":"Semantic gap","level":4,"score":0.3614000082015991},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.349700003862381},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.29440000653266907},{"id":"https://openalex.org/C2781020372","wikidata":"https://www.wikidata.org/wiki/Q533093","display_name":"On the fly","level":2,"score":0.287200003862381},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2709999978542328},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.2667999863624573},{"id":"https://openalex.org/C2777508537","wikidata":"https://www.wikidata.org/wiki/Q7936620","display_name":"Visual reasoning","level":2,"score":0.2630999982357025},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.26170000433921814},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.25769999623298645},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.25209999084472656}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.04457","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.04457","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.2606.04457","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.04457","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/9","display_name":"Industry, innovation and infrastructure","score":0.4131529629230499}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Incorporating":[0],"visual":[1,144],"semantic":[2,49,73,121,145,156],"representations":[3],"as":[4,27,55,89,94,150],"an":[5,58,78],"intermediate":[6,120],"step":[7],"before":[8],"image":[9,162,177],"generation":[10,22],"can":[11,130,190],"reduce":[12],"the":[13,63,68,72,114,139,155,160,213],"modeling":[14,117],"difficulty":[15],"between":[16],"text":[17],"and":[18,29,71,97,176,183,196],"images,":[19],"thereby":[20],"improving":[21],"quality.":[23],"Recent":[24],"works":[25],"such":[26,88,93,135],"X-Omni":[28],"BLIP3o-Next":[30],"have":[31],"explored":[32],"this":[33,75,100,166],"direction,":[34],"but":[35,110],"they":[36,111],"typically":[37],"use":[38],"a":[39,43,107],"two-stage":[40],"external":[41,210],"pipeline:":[42],"separate":[44],"autoregressive":[45],"model":[46,140,184],"first":[47,141],"generates":[48,143,159],"tokens,":[50],"which":[51,129],"are":[52],"then":[53,158],"fed":[54],"conditioning":[56],"to":[57],"independent":[59],"diffusion":[60],"decoder.":[61],"Since":[62],"decoder":[64],"cannot":[65],"jointly":[66],"access":[67],"original":[69],"input":[70],"plan,":[74],"design":[76],"introduces":[77],"information":[79],"bottleneck":[80,101],"that":[81,153,188],"limits":[82],"detail":[83],"preservation":[84,204],"in":[85],"downstream":[86],"tasks":[87],"editing.":[90],"Internal":[91],"architectures":[92],"Transfusion,":[95],"BAGEL,":[96],"Show-o2":[98],"avoid":[99],"by":[102],"enabling":[103],"cross-modal":[104],"interaction":[105],"within":[106],"single":[108],"model,":[109],"still":[112],"face":[113],"difficult":[115],"text-to-pixel":[116],"gap":[118],"without":[119],"guidance.":[122],"We":[123,168],"propose":[124],"Visual":[125],"Prompt":[126],"Engineering":[127],"(VPE),":[128],"be":[131],"seamlessly":[132],"integrated":[133],"into":[134],"internal":[136,198],"frameworks.":[137],"Specifically,":[138],"autoregressively":[142],"tokens":[146,163],"(e.g.,":[147],"SigLIP":[148],"2)":[149],"\"visual":[151],"prompts\"":[152],"capture":[154],"layout,":[157],"full":[161],"conditioned":[164],"on":[165],"plan.":[167],"validate":[169],"VPE":[170,189],"across":[171],"class-conditional":[172],"generation,":[173,175],"text-to-image":[174],"editing,":[178],"covering":[179],"various":[180],"token":[181],"types":[182],"architectures.":[185],"Results":[186],"show":[187],"accelerate":[191],"convergence,":[192],"raise":[193],"quality":[194],"ceilings,":[195],"through":[197],"integration,":[199],"achieve":[200],"substantially":[201],"better":[202],"editing":[203,220],"(PSNR:":[205],"26.76":[206],"vs.":[207],"19.92)":[208],"than":[209],"alternatives":[211],"of":[212],"same":[214],"parameter":[215],"scale,":[216],"while":[217],"maintaining":[218],"competitive":[219],"responsiveness.":[221]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-05T00:00:00"}