{"id":"https://openalex.org/W4378711654","doi":"https://doi.org/10.48550/arxiv.2305.16397","title":"Are Diffusion Models Vision-And-Language Reasoners?","display_name":"Are Diffusion Models Vision-And-Language Reasoners?","publication_year":2023,"publication_date":"2023-05-25","ids":{"openalex":"https://openalex.org/W4378711654","doi":"https://doi.org/10.48550/arxiv.2305.16397"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2305.16397","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2305.16397","pdf_url":"https://arxiv.org/pdf/2305.16397","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2305.16397","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5073456064","display_name":"Benno Krojer","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Krojer, Benno","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078951239","display_name":"Elinor Poole-Dayan","orcid":"https://orcid.org/0009-0003-8217-0504"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Poole-Dayan, Elinor","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013102998","display_name":"Vikram Voleti","orcid":"https://orcid.org/0000-0003-0941-7227"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Voleti, Vikram","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075885606","display_name":"Christopher Pal","orcid":"https://orcid.org/0000-0001-6534-2114"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pal, Christopher","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5102886212","display_name":"Siva Reddy","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Reddy, Siva","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5073456064"],"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9918000102043152,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9918000102043152,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9897000193595886,"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/T10028","display_name":"Topic Modeling","score":0.9864000082015991,"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/discriminative-model","display_name":"Discriminative model","score":0.8517163991928101},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.798575758934021},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7770341038703918},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.6417324542999268},{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.5857425332069397},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5828191637992859},{"id":"https://openalex.org/keywords/principle-of-compositionality","display_name":"Principle of compositionality","score":0.5535755157470703},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5342532396316528},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5285567045211792},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4158293604850769},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41088947653770447},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1315860152244568}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8517163991928101},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.798575758934021},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7770341038703918},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.6417324542999268},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.5857425332069397},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5828191637992859},{"id":"https://openalex.org/C121375916","wikidata":"https://www.wikidata.org/wiki/Q936559","display_name":"Principle of compositionality","level":2,"score":0.5535755157470703},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5342532396316528},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5285567045211792},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4158293604850769},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41088947653770447},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1315860152244568},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2305.16397","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2305.16397","pdf_url":"https://arxiv.org/pdf/2305.16397","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},{"id":"doi:10.48550/arxiv.2305.16397","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2305.16397","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":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2305.16397","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2305.16397","pdf_url":"https://arxiv.org/pdf/2305.16397","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7300000190734863}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4281766347","https://openalex.org/W2093104230","https://openalex.org/W2987280934","https://openalex.org/W4390874210","https://openalex.org/W4384918963","https://openalex.org/W4365211920","https://openalex.org/W2128027845","https://openalex.org/W3014948380","https://openalex.org/W4386184937","https://openalex.org/W4241564561"],"abstract_inverted_index":{"Text-conditioned":[0],"image":[1],"generation":[2],"models":[3,29,52],"have":[4],"recently":[5],"shown":[6],"immense":[7],"qualitative":[8],"success":[9],"using":[10,64],"denoising":[11],"diffusion":[12,137],"processes.":[13],"However,":[14],"unlike":[15],"discriminative":[16,165],"vision-and-language":[17,82],"models,":[18,138],"it":[19],"is":[20,96],"a":[21,65,119],"non-trivial":[22],"task":[23,63],"to":[24,30],"subject":[25],"these":[26],"diffusion-based":[27,51],"generative":[28,128,167],"automatic":[31],"fine-grained":[32],"quantitative":[33],"evaluation":[34,85,169],"of":[35],"high-level":[36],"phenomena":[37],"such":[38],"as":[39],"compositionality.":[40],"Towards":[41],"this":[42],"goal,":[43],"we":[44,49,71],"perform":[45],"two":[46],"innovations.":[47],"First,":[48],"transform":[50],"(in":[53],"our":[54,157],"case,":[55],"Stable":[56,92,142,153],"Diffusion)":[57],"for":[58,146],"any":[59],"image-text":[60],"matching":[61],"(ITM)":[62],"novel":[66],"method":[67],"called":[68],"DiffusionITM.":[69],"Second,":[70],"introduce":[72],"the":[73,133,147],"Generative-Discriminative":[74],"Evaluation":[75],"Benchmark":[76],"(GDBench)":[77],"benchmark":[78,176],"with":[79,118],"7":[80],"complex":[81],"tasks,":[83],"bias":[84,135],"and":[86,101,110,139,166,175],"detailed":[87],"analysis.":[88],"We":[89,112,130,171],"find":[90,140],"that":[91,141],"Diffusion":[93,143,154],"+":[94],"DiffusionITM":[95],"competitive":[97],"on":[98,104,124],"many":[99],"tasks":[100,106],"outperforms":[102],"CLIP":[103],"compositional":[105,116],"like":[107,108],"CLEVR":[109],"Winoground.":[111],"further":[113],"boost":[114],"its":[115],"performance":[117],"transfer":[120],"setup":[121,177],"by":[122],"fine-tuning":[123],"MS-COCO":[125],"while":[126],"retaining":[127],"capabilities.":[129],"also":[131],"measure":[132],"stereotypical":[134],"in":[136,160],"2.1":[144],"is,":[145],"most":[148],"part,":[149],"less":[150],"biased":[151],"than":[152],"1.5.":[155],"Overall,":[156],"results":[158],"point":[159],"an":[161],"exciting":[162],"direction":[163],"bringing":[164],"model":[168],"closer.":[170],"will":[172],"release":[173],"code":[174],"soon.":[178]},"counts_by_year":[],"updated_date":"2025-11-06T06:51:31.235846","created_date":"2025-10-10T00:00:00"}