{"id":"https://openalex.org/W7160820931","doi":"https://doi.org/10.48550/arxiv.2605.07078","title":"Test-Time Compositional Generalization in Diffusion Models via Concept Discovery","display_name":"Test-Time Compositional Generalization in Diffusion Models via Concept Discovery","publication_year":2026,"publication_date":"2026-05-08","ids":{"openalex":"https://openalex.org/W7160820931","doi":"https://doi.org/10.48550/arxiv.2605.07078"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.07078","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.07078","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":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.2605.07078","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135874125","display_name":"Zekun Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Zekun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135878298","display_name":"Anant Gupta","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gupta, Anant","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135902500","display_name":"Tianyi Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Tianyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135832096","display_name":"Christopher J. MacLellan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"MacLellan, Christopher J.","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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.3181999921798706,"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"}},"topics":[{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.3181999921798706,"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"}},{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.20509999990463257,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.08070000261068344,"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/generalization","display_name":"Generalization","score":0.808899998664856},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6668999791145325},{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.6212999820709229},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5386999845504761},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5343999862670898},{"id":"https://openalex.org/keywords/submodular-set-function","display_name":"Submodular set function","score":0.5239999890327454},{"id":"https://openalex.org/keywords/translation","display_name":"Translation (biology)","score":0.34529998898506165}],"concepts":[{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.808899998664856},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6668999791145325},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.6212999820709229},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6074000000953674},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5386999845504761},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5343999862670898},{"id":"https://openalex.org/C178621042","wikidata":"https://www.wikidata.org/wiki/Q7631710","display_name":"Submodular set function","level":2,"score":0.5239999890327454},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.48089998960494995},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47780001163482666},{"id":"https://openalex.org/C149364088","wikidata":"https://www.wikidata.org/wiki/Q185917","display_name":"Translation (biology)","level":4,"score":0.34529998898506165},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.328000009059906},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.3093999922275543},{"id":"https://openalex.org/C55128770","wikidata":"https://www.wikidata.org/wiki/Q5275440","display_name":"Diffusion map","level":4,"score":0.3059000074863434},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.3005000054836273},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2953000068664551},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.29330000281333923},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2912999987602234},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.27459999918937683},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.2687999904155731},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.26820001006126404},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.263700008392334}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.07078","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.07078","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":"doi:10.48550/arxiv.2605.07078","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.07078","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":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Compositional":[0],"generalization":[1],"requires":[2],"models":[3],"to":[4,78,123],"produce":[5],"novel":[6],"configurations":[7],"from":[8,42,142],"familiar":[9],"parts.":[10],"In":[11],"diffusion":[12,36,172],"models,":[13],"prior":[14],"compositional":[15,181],"generation":[16,182],"methods":[17],"typically":[18],"assume":[19],"that":[20,165,178],"the":[21,43,49,147,152,166,171],"relevant":[22,91],"concepts":[23,41,177],"or":[24,121],"conditioning":[25],"signals":[26],"are":[27],"already":[28],"available.":[29],"We":[30],"instead":[31],"ask":[32],"whether":[33],"a":[34,60,94,102,125,130,184],"pretrained":[35],"model":[37,106,113,155,173],"can":[38,114],"discover":[39],"query-specific":[40],"time-indexed":[44,167],"scores":[45],"it":[46],"learns":[47],"for":[48,128],"noisy":[50],"marginals":[51],"$p_t(x_t)$":[52],"and":[53,98,134,144,151,158],"compose":[54],"them":[55,100],"at":[56,74],"test":[57],"time.":[58],"Given":[59],"single":[61],"out-of-distribution":[62],"query,":[63],"our":[64],"method":[65],"performs":[66],"gradient":[67],"ascent":[68],"on":[69],"$s_\u03b8(x_t,t)":[70],"\\approx":[71],"\\nabla_{x_t}\\log":[72],"p_t(x_t)$":[73],"multiple":[75],"noising":[76],"timesteps":[77],"recover":[79],"local":[80],"density":[81],"modes,":[82],"maps":[83],"these":[84],"modes":[85],"into":[86,101],"clean-space":[87],"Gaussians,":[88],"greedily":[89],"selects":[90],"prototypes":[92],"with":[93,107],"submodular":[95],"likelihood":[96],"objective,":[97],"combines":[99],"product-of-experts":[103],"(PoE)":[104],"teacher":[105,112],"an":[108],"analytic":[109,148],"score.":[110],"This":[111],"be":[115],"sampled":[116],"directly":[117],"through":[118],"classifier-free":[119],"guidance":[120],"used":[122],"generate":[124],"sample":[126],"pool":[127],"training":[129],"new":[131],"class":[132],"embedding":[133],"low-rank":[135,153],"adapter.":[136],"On":[137],"held-out":[138],"composition":[139],"benchmarks":[140],"built":[141],"ColorMNIST":[143],"CelebA,":[145],"both":[146],"PoE":[149],"sampler":[150],"adapted":[154],"outperform":[156],"query-only":[157],"nearest":[159],"trained-class":[160],"baselines.":[161],"These":[162],"results":[163],"suggest":[164],"score":[168],"geometry":[169],"of":[170],"contains":[174],"reusable":[175],"density-mode":[176],"support":[179],"test-time":[180],"without":[183],"predefined":[185],"concept":[186],"library.":[187]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-12T00:00:00"}
