{"id":"https://openalex.org/W7130581703","doi":"https://doi.org/10.1109/fllm67465.2025.11391196","title":"Analyzing Recursiveness in Multimodal Generative Artificial Intelligence: Stability or Divergence?","display_name":"Analyzing Recursiveness in Multimodal Generative Artificial Intelligence: Stability or Divergence?","publication_year":2025,"publication_date":"2025-11-25","ids":{"openalex":"https://openalex.org/W7130581703","doi":"https://doi.org/10.1109/fllm67465.2025.11391196"},"language":null,"primary_location":{"id":"doi:10.1109/fllm67465.2025.11391196","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fllm67465.2025.11391196","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 3rd International Conference on Foundation and Large Language Models (FLLM)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5126417182","display_name":"Javier Conde","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Javier Conde","raw_affiliation_strings":["Universidad Politécnica de Madrid"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universidad Politécnica de Madrid","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126427675","display_name":"Tobias Cheung","orcid":null},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Tobias Cheung","raw_affiliation_strings":["University of Edinburgh"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Edinburgh","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126415371","display_name":"Gonzalo Mart\u00ednez","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gonzalo Mart\u00ednez","raw_affiliation_strings":["Universidad Politécnica de Madrid"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universidad Politécnica de Madrid","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080322790","display_name":"Pedro Reviriego","orcid":"https://orcid.org/0000-0003-2540-5234"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pedro Reviriego","raw_affiliation_strings":["Universidad Politécnica de Madrid"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universidad Politécnica de Madrid","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023629712","display_name":"Rik Sarkar","orcid":"https://orcid.org/0000-0001-7804-4351"},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Rik Sarkar","raw_affiliation_strings":["University of Edinburgh"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Edinburgh","institution_ids":["https://openalex.org/I98677209"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"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":"968","last_page":"975"},"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":0.1720999926328659,"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":0.1720999926328659,"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":0.0820000022649765,"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/T11147","display_name":"Misinformation and Its Impacts","score":0.0632999986410141,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.5946000218391418},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.590399980545044},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5684999823570251},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.5109000205993652},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.48730000853538513},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.4799000024795532},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.44290000200271606},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.44290000200271606}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6643999814987183},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6255000233650208},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.5946000218391418},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.590399980545044},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5684999823570251},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.5109000205993652},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.48730000853538513},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.4799000024795532},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.44290000200271606},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.44290000200271606},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36309999227523804},{"id":"https://openalex.org/C2778152352","wikidata":"https://www.wikidata.org/wiki/Q5165061","display_name":"Content (measure theory)","level":2,"score":0.3303999900817871},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.33000001311302185},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.31189998984336853},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3012999892234802},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.2912999987602234},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.2833999991416931},{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.265500009059906},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2614000141620636},{"id":"https://openalex.org/C2777299769","wikidata":"https://www.wikidata.org/wiki/Q3707858","display_name":"Type (biology)","level":2,"score":0.2605000138282776}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fllm67465.2025.11391196","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fllm67465.2025.11391196","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 3rd International Conference on Foundation and Large Language Models (FLLM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W2144211451","https://openalex.org/W2962785568","https://openalex.org/W4312933868","https://openalex.org/W4367595583","https://openalex.org/W4387968438","https://openalex.org/W4391094120","https://openalex.org/W4392385810","https://openalex.org/W4392507474","https://openalex.org/W4395044357","https://openalex.org/W4400187139","https://openalex.org/W4400668000","https://openalex.org/W4404356490","https://openalex.org/W4411542047"],"related_works":[],"abstract_inverted_index":{"One":[0],"of":[1,60,137,173,192],"the":[2,58,69,102,110,135,154,158,171,176],"latest":[3],"trends":[4],"in":[5,43,123],"generative":[6],"Artificial":[7],"Intelligence":[8],"(AI)":[9],"involves":[10],"multimodality":[11],"with":[12,85,163],"models":[13,177,193],"that":[14,93,153],"are":[15],"able":[16],"to":[17,29,33,40,45,57,95,109],"generate":[18,96],"images":[19],"from":[20,24,51,157],"text":[21,23,94],"and":[22,32,49,65,100,143,146,148,167,175,189],"images.":[25],"It":[26],"is":[27,55],"important":[28],"investigate":[30],"whether":[31],"what":[34],"extent":[35],"such":[36],"modality":[37,80,139],"changes":[38],"lead":[39],"information":[41,47,124],"loss":[42,48],"order":[44],"prevent":[46],"bias":[50],"models.":[52],"This":[53],"process":[54,155],"analogous":[56],"game":[59],"telephone,":[61],"where":[62],"iterative":[63],"descriptions":[64],"representations":[66],"can":[67,75],"distort":[68],"original":[70,111,159],"content.":[71],"In":[72,126],"AI,":[73],"this":[74,127],"be":[76],"tested":[77],"through":[78],"recursive":[79,138],"changes,":[81],"for":[82,184],"examples,":[83],"starting":[84],"an":[86,131],"image,":[87,99],"generating":[88],"a":[89,97],"textual":[90],"description,":[91],"using":[92,141],"new":[98],"repeating":[101],"cycle.":[103],"Ideally,":[104],"embeddings":[105],"would":[106],"remain":[107],"close":[108],"across":[112],"iterations,":[113,162],"preserving":[114],"content":[115,185],"integrity.":[116],"However,":[117],"increasing":[118],"divergence":[119],"may":[120],"occur,":[121],"resulting":[122],"degradation.":[125],"paper,":[128],"we":[129],"present":[130],"empirical":[132],"study":[133],"on":[134,170],"effects":[136],"transformations":[140],"GPT-4o":[142],"DALL-E":[144],"3":[145],"Flux.1":[147],"Phi-3.5.":[149],"Our":[150],"findings":[151],"show":[152],"diverges":[156],"image":[160,174],"over":[161],"no":[164],"stable":[165],"convergence,":[166],"varies":[168],"depending":[169],"type":[172],"used.":[178],"These":[179],"results":[180],"have":[181],"significant":[182],"implications":[183],"generation,":[186],"model":[187],"hallucinations,":[188],"future":[190],"version":[191],"trained":[194],"by":[195],"artificial":[196],"data.":[197]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-02-20T00:00:00"}