{"id":"https://openalex.org/W7133502048","doi":"https://doi.org/10.48550/arxiv.2603.02829","title":"Toward Early Quality Assessment of Text-to-Image Diffusion Models","display_name":"Toward Early Quality Assessment of Text-to-Image Diffusion Models","publication_year":2026,"publication_date":"2026-03-03","ids":{"openalex":"https://openalex.org/W7133502048","doi":"https://doi.org/10.48550/arxiv.2603.02829"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.02829","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5082888961","display_name":"Huanlei Guo","orcid":"https://orcid.org/0000-0002-8224-1339"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Huanlei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128063130","display_name":"Hongxin Wei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei, Hongxin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128070583","display_name":"Bingyi Jing","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jing, Bingyi","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":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.27383843,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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":0.7092999815940857,"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":0.7092999815940857,"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":0.07670000195503235,"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/T11448","display_name":"Face recognition and analysis","score":0.014999999664723873,"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/pipeline","display_name":"Pipeline (software)","score":0.6403999924659729},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.6155999898910522},{"id":"https://openalex.org/keywords/property","display_name":"Property (philosophy)","score":0.5394999980926514},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4787999987602234},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.4781999886035919},{"id":"https://openalex.org/keywords/inefficiency","display_name":"Inefficiency","score":0.4496999979019165},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4235999882221222},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4219000041484833},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.4023999869823456}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7170000076293945},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6403999924659729},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.6155999898910522},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.5394999980926514},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4787999987602234},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.4781999886035919},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4577000141143799},{"id":"https://openalex.org/C2778869765","wikidata":"https://www.wikidata.org/wiki/Q6028363","display_name":"Inefficiency","level":2,"score":0.4496999979019165},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4235999882221222},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4219000041484833},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.4023999869823456},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3926999866962433},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.38339999318122864},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.37299999594688416},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.37209999561309814},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.364300012588501},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.36039999127388},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36010000109672546},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.32170000672340393},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.31459999084472656},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.30149999260902405},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2793000042438507},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.27230000495910645},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2694999873638153},{"id":"https://openalex.org/C203504353","wikidata":"https://www.wikidata.org/wiki/Q4765461","display_name":"Anisotropic diffusion","level":3,"score":0.26759999990463257},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2628999948501587},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.2526000142097473}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.02829","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2603.02829","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.02829","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":"Preprint"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2603.02829","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"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":{"Recent":[0],"text-to-image":[1],"(T2I)":[2],"diffusion":[3,139],"and":[4,32,57,63,109,140,159],"flow-matching":[5,141],"models":[6],"can":[7,184],"produce":[8],"highly":[9,45],"realistic":[10],"images":[11,36],"from":[12,128],"natural":[13],"language":[14],"prompts.":[15],"In":[16,67],"practical":[17],"scenarios,":[18],"T2I":[19],"systems":[20],"are":[21,30,37,65],"often":[22],"run":[23],"in":[24],"a":[25,34,77,103],"``generate--then--select''":[26],"mode:":[27],"many":[28],"seeds":[29,133,158],"sampled":[31],"only":[33,150],"few":[35],"kept":[38],"for":[39],"use.":[40],"However,":[41],"this":[42,68,72,120],"pipeline":[43],"is":[44,196],"resource-intensive":[46],"since":[47],"each":[48],"candidate":[49,157],"requires":[50],"tens":[51],"to":[52,134],"hundreds":[53],"of":[54,84,152,175],"denoising":[55],"steps,":[56],"evaluation":[58,83,148],"metrics":[59],"such":[60],"as":[61],"CLIPScore":[62],"ImageReward":[64],"post-hoc.":[66],"work,":[69],"we":[70],"address":[71],"inefficiency":[73],"by":[74,122,168],"introducing":[75],"Probe-Select,":[76],"plug-in":[78],"module":[79],"that":[80,93,146,180],"enables":[81,160],"efficient":[82],"image":[85,116],"quality":[86,125,174],"within":[87],"the":[88,153,173,176,191],"generation":[89,188],"process.":[90],"We":[91],"observe":[92],"certain":[94],"intermediate":[95],"denoiser":[96],"activations,":[97,130],"even":[98],"at":[99,149,198],"early":[100,129,147,181],"timesteps,":[101],"encode":[102],"stable":[104],"coarse":[105],"structure,":[106],"object":[107],"layout":[108],"spatial":[110],"arrangement--that":[111],"strongly":[112],"correlates":[113],"with":[114],"final":[115,124],"fidelity.":[117],"Probe-Select":[118],"exploits":[119],"property":[121],"predicting":[123],"scores":[126],"directly":[127],"allowing":[131],"unpromising":[132],"be":[135],"terminated":[136],"early.":[137],"Across":[138],"backbones,":[142],"our":[143],"experiments":[144],"show":[145],"20\\%":[151],"trajectory":[154],"accurately":[155],"ranks":[156],"selective":[161,187],"continuation.":[162],"This":[163],"strategy":[164],"reduces":[165],"sampling":[166],"cost":[167],"over":[169],"60\\%":[170],"while":[171],"improving":[172],"retained":[177],"images,":[178],"demonstrating":[179],"structural":[182],"signals":[183],"effectively":[185],"guide":[186],"without":[189],"altering":[190],"underlying":[192],"generative":[193],"model.":[194],"Code":[195],"available":[197],"https://github.com/Guhuary/ProbeSelect.":[199]},"counts_by_year":[],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2026-03-05T00:00:00"}