{"id":"https://openalex.org/W7224133452","doi":"https://doi.org/10.5281/zenodo.23720847","title":"Lookahead Objective Reweighting Intervention Optimization for Diffusion Models: Predicting Downstream Generation Outcomes to Select Adaptive Multi-Objective Priorities","display_name":"Lookahead Objective Reweighting Intervention Optimization for Diffusion Models: Predicting Downstream Generation Outcomes to Select Adaptive Multi-Objective Priorities","publication_year":2026,"publication_date":"2026-10-28","ids":{"openalex":"https://openalex.org/W7224133452","doi":"https://doi.org/10.5281/zenodo.23720847"},"language":"en","primary_location":{"id":"doi:10.5281/zenodo.23720847","doi":"https://doi.org/10.5281/zenodo.23720847","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.23720847","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"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"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.5281/zenodo.23720847","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100638045","display_name":"Jincheng Zhang","orcid":"https://orcid.org/0000-0001-7332-6704","observed_orcids":["https://orcid.org/0000-0001-7332-6704","https://orcid.org/0009-0005-1860-0009"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zhang, Jincheng","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0009-0005-1860-0009","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5100638045"],"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":0.9994999766349792,"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":0.9994999766349792,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.0,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.0,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/diffusion-models","display_name":"diffusion models","score":0.9049999713897705},{"id":"https://openalex.org/keywords/image-generation","display_name":"image generation","score":0.6700000166893005},{"id":"https://openalex.org/keywords/multi-objective-optimization","display_name":"multi-objective optimization","score":0.7710000276565552},{"id":"https://openalex.org/keywords/adaptive-guidance","display_name":"adaptive guidance","score":0.7860000133514404},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"noise reduction","score":0.6710000038146973},{"id":"https://openalex.org/keywords/image-text-alignment","display_name":"image-text alignment","score":0.847000002861023},{"id":"https://openalex.org/keywords/quality-efficiency-trade-off","display_name":"quality-efficiency trade-off","score":0.8799999952316284},{"id":"https://openalex.org/keywords/uncertainty-estimation","display_name":"uncertainty estimation","score":0.40299999713897705}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6674000024795532},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5692999958992004},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.5687999725341797},{"id":"https://openalex.org/C2778738651","wikidata":"https://www.wikidata.org/wiki/Q16546687","display_name":"Novelty","level":2,"score":0.5291000008583069},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5115000009536743},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4918999969959259},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37709999084472656},{"id":"https://openalex.org/C68781425","wikidata":"https://www.wikidata.org/wiki/Q2052203","display_name":"Multi-objective optimization","level":2,"score":0.36149999499320984},{"id":"https://openalex.org/C2776207758","wikidata":"https://www.wikidata.org/wiki/Q5303302","display_name":"Downstream (manufacturing)","level":2,"score":0.35659998655319214},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3521000146865845},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.3472999930381775},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.33489999175071716},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.3328999876976013},{"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/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.329800009727478},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.31130000948905945},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.30250000953674316},{"id":"https://openalex.org/C144559511","wikidata":"https://www.wikidata.org/wiki/Q2986279","display_name":"Principal (computer security)","level":2,"score":0.29179999232292175},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.28119999170303345},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.2728999853134155},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2720000147819519},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.2696000039577484},{"id":"https://openalex.org/C150921843","wikidata":"https://www.wikidata.org/wiki/Q1170431","display_name":"Resampling","level":2,"score":0.2676999866962433},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.266400009393692},{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.26579999923706055},{"id":"https://openalex.org/C2780385302","wikidata":"https://www.wikidata.org/wiki/Q367158","display_name":"Protocol (science)","level":3,"score":0.265500009059906},{"id":"https://openalex.org/C167393769","wikidata":"https://www.wikidata.org/wiki/Q4680768","display_name":"Adaptive strategies","level":2,"score":0.2628999948501587},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.2623000144958496},{"id":"https://openalex.org/C143587482","wikidata":"https://www.wikidata.org/wiki/Q1543216","display_name":"Iterative and incremental development","level":2,"score":0.2547999918460846}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.5281/zenodo.23720847","doi":"https://doi.org/10.5281/zenodo.23720847","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.23720847","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"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"},{"id":"doi:10.5281/zenodo.23720848","doi":"https://doi.org/10.5281/zenodo.23720848","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.23720848","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"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"}],"best_oa_location":{"id":"doi:10.5281/zenodo.23720847","doi":"https://doi.org/10.5281/zenodo.23720847","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.23720847","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"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":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7224116289","https://openalex.org/W7224137454","https://openalex.org/W7224130750","https://openalex.org/W7224095425","https://openalex.org/W7224118210","https://openalex.org/W7224091087","https://openalex.org/W7224122826","https://openalex.org/W7224113681","https://openalex.org/W7224107942","https://openalex.org/W7224130202"],"abstract_inverted_index":{"Diffusion":[0],"models":[1,197],"generate":[2],"images":[3],"through":[4,76,198,253],"iterative":[5],"denoising":[6,78,105],"processes":[7],"in":[8,210],"which":[9],"multiple":[10],"objectives,":[11,178],"including":[12],"text\u2013image":[13],"alignment,":[14],"perceptual":[15],"aesthetics,":[16],"structural":[17],"correctness,":[18],"attribute":[19],"binding,":[20],"and":[21,29,34,124,132,140,150,166,181,240,248,264],"computational":[22,30,133,243],"efficiency,":[23],"may":[24,48],"compete":[25],"for":[26],"limited":[27],"representational":[28],"resources.":[31],"Conventional":[32],"generation":[33,56,101],"guidance":[35,201,266],"strategies":[36,156],"often":[37],"employ":[38],"fixed":[39,159],"objective":[40,50,145,160],"weights":[41],"or":[42,202],"predefined":[43],"schedules,":[44],"whereas":[45],"adaptive":[46,231,265],"methods":[47],"adjust":[49],"priorities":[51],"according":[52,96],"to":[53,97,192],"the":[54,68,117,226,235],"current":[55],"state.":[57],"However,":[58],"a":[59,89,109,126],"locally":[60],"appropriate":[61],"weighting":[62],"configuration":[63,127],"does":[64],"not":[65],"necessarily":[66],"produce":[67],"best":[69],"final":[70,118],"image":[71],"because":[72],"its":[73,241],"effects":[74],"propagate":[75],"subsequent":[77],"steps.":[79],"This":[80],"paper":[81],"proposes":[82],"Lookahead":[83],"Objective":[84],"Reweighting":[85],"Intervention":[86],"Optimization":[87],"(LORIO),":[88],"conceptual":[90],"framework":[91,136],"that":[92,218,234],"selects":[93,125],"objective-weight":[94,114],"configurations":[95],"their":[98],"predicted":[99,129],"downstream":[100,222],"outcomes.":[102],"At":[103],"each":[104,122],"step,":[106],"LORIO":[107],"constructs":[108],"candidate":[110,174],"set":[111],"of":[112,121,221],"feasible":[113],"configurations,":[115],"estimates":[116],"multi-objective":[119,148],"consequences":[120,223],"candidate,":[123],"using":[128],"utility,":[130],"uncertainty,":[131],"cost.":[134],"The":[135,187,213],"supports":[137],"both":[138],"discrete":[139],"continuous":[141],"weight":[142,164,169],"spaces,":[143],"phase-dependent":[144],"priorities,":[146],"constrained":[147],"optimization,":[149,259],"optional":[151],"Pareto-aware":[152],"decision-making.":[153],"Three":[154],"principal":[155,214],"are":[157,185,208],"distinguished:":[158],"weighting,":[161,232,261],"direct":[162,230],"state-conditioned":[163],"prediction,":[165],"explicit":[167,219],"lookahead-based":[168],"selection.":[170],"A":[171],"mathematical":[172],"formulation,":[173],"evaluation":[175],"mechanism,":[176],"training":[177],"inference":[179],"algorithm,":[180],"controlled":[182],"experimental":[183,206],"protocol":[184],"presented.":[186],"proposed":[188],"method":[189],"is":[190,217,237,245],"intended":[191],"operate":[193],"with":[194,256],"pretrained":[195],"diffusion":[196],"compatible":[199],"inference-time":[200],"reward-conditioned":[203],"mechanisms.":[204],"No":[205],"results":[207],"claimed":[209],"this":[211],"paper.":[212],"research":[215],"hypothesis":[216],"prediction":[220],"can":[224],"improve":[225],"quality\u2013efficiency":[227],"trade-off":[228],"beyond":[229],"provided":[233],"evaluator":[236],"sufficiently":[238],"accurate":[239],"additional":[242],"cost":[244],"controlled.":[246],"Novelty":[247],"effectiveness":[249],"must":[250],"be":[251],"established":[252],"systematic":[254],"comparison":[255],"existing":[257],"multi-reward":[258],"phase-aware":[260],"preference-conditioned":[262],"generation,":[263],"methods.":[267]},"counts_by_year":[],"updated_date":"2026-10-30T12:39:25.321706","created_date":"2026-10-29T00:00:00"}