{"id":"https://openalex.org/W7204874473","doi":"https://doi.org/10.18653/2026.emnlp-main.1488","title":"Weaving Visual Narratives: Agentic Image Bundle Composition Beyond Atomic Visual Matching","display_name":"Weaving Visual Narratives: Agentic Image Bundle Composition Beyond Atomic Visual Matching","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7204874473","doi":"https://doi.org/10.18653/2026.emnlp-main.1488"},"language":"en","primary_location":{"id":"doi:10.18653/2026.emnlp-main.1488","doi":"https://doi.org/10.18653/2026.emnlp-main.1488","is_oa":true,"landing_page_url":"https://doi.org/10.18653/2026.emnlp-main.1488","pdf_url":"https://aclanthology.org/2026.emnlp-main.1488.pdf","source":{"id":"https://openalex.org/S4363608991","display_name":"Conference on Empirical Methods in Natural Language Processing (EMNLP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://aclanthology.org/2026.emnlp-main.1488.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133617871","display_name":"Rong Shan","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]},{"id":"https://openalex.org/I4405279436","display_name":"Shanghai Innovation Institute","ror":"https://ror.org/01fatbw66","country_code":"CN","type":"education","lineage":["https://openalex.org/I4405279436"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rong Shan","raw_affiliation_strings":["Shanghai Innovation Institute ,","Shanghai Jiao Tong University ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Innovation Institute ,","institution_ids":["https://openalex.org/I4405279436"]},{"raw_affiliation_string":"Shanghai Jiao Tong University ,","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125535678","display_name":"Tianyi Xu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianyi Xu","raw_affiliation_strings":["Shanghai Jiao Tong University ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University ,","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125928066","display_name":"Congmin Zheng","orcid":"https://orcid.org/0009-0006-5821-154X","observed_orcids":["https://orcid.org/0009-0006-5821-154X"]},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Congmin Zheng","raw_affiliation_strings":["Shanghai Jiao Tong University ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University ,","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125512038","display_name":"Wenteng Chen","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenteng Chen","raw_affiliation_strings":["Shanghai Jiao Tong University ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University ,","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127981821","display_name":"Jiachen Zhu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiachen Zhu","raw_affiliation_strings":["Shanghai Jiao Tong University ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University ,","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127988021","display_name":"Junjie Wu","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Junjie Wu","raw_affiliation_strings":["OPPO"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"OPPO","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065428641","display_name":"Dun Zeng","orcid":"https://orcid.org/0000-0002-4517-5379","observed_orcids":["https://orcid.org/0000-0002-4517-5379"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dun Zeng","raw_affiliation_strings":["OPPO"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"OPPO","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160115427","display_name":"Teng Wang","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Teng Wang","raw_affiliation_strings":["OPPO"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"OPPO","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160079402","display_name":"Weiwen Liu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiwen Liu","raw_affiliation_strings":["Shanghai Jiao Tong University ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University ,","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5148887357","display_name":"Weinan Zhang","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Changwang Zhang","raw_affiliation_strings":["OPPO"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"OPPO","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160082210","display_name":"Weinan Zhang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weinan Zhang","raw_affiliation_strings":["Shanghai Jiao Tong University ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University ,","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160149761","display_name":"Jun Wang","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jun Wang","raw_affiliation_strings":["OPPO"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"OPPO","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5160136525","display_name":"Jianghao Lin","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianghao Lin","raw_affiliation_strings":["Shanghai Jiao Tong University ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University ,","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.6944735,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"34025","last_page":"34050"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.5321999788284302,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.5321999788284302,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.3230000138282776,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.11940000206232071,"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/personal-photo-collections","display_name":"personal photo collections","score":0.6460000276565552},{"id":"https://openalex.org/keywords/visual-narrative","display_name":"visual narrative","score":0.4950000047683716},{"id":"https://openalex.org/keywords/agentic-retrieval","display_name":"agentic retrieval","score":0.5049999952316284},{"id":"https://openalex.org/keywords/large-language-models","display_name":"large language models","score":0.6830000281333923},{"id":"https://openalex.org/keywords/vision-language-models","display_name":"vision-language models","score":0.9819999933242798},{"id":"https://openalex.org/keywords/combinatorial-search","display_name":"combinatorial search","score":0.5490000247955322}],"concepts":[{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.7565000057220459},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6628999710083008},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6243000030517578},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6172999739646912},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5771999955177307},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5311999917030334},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5304999947547913},{"id":"https://openalex.org/C2778134712","wikidata":"https://www.wikidata.org/wiki/Q1047307","display_name":"Bundle","level":2,"score":0.5238000154495239},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5216000080108643},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.5001000165939331},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","level":2,"score":0.4717000126838684},{"id":"https://openalex.org/C54525549","wikidata":"https://www.wikidata.org/wiki/Q2553445","display_name":"Weaving","level":2,"score":0.438400000333786},{"id":"https://openalex.org/C40231798","wikidata":"https://www.wikidata.org/wiki/Q1333743","display_name":"Composition (language)","level":2,"score":0.4074999988079071},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.40290001034736633},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.34869998693466187},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33230000734329224},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32710000872612},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.289900004863739},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.289900004863739},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.2874999940395355},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.28110000491142273},{"id":"https://openalex.org/C21308566","wikidata":"https://www.wikidata.org/wiki/Q7169365","display_name":"Permutation (music)","level":2,"score":0.27149999141693115},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.26499998569488525},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.2639999985694885},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25440001487731934}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.18653/2026.emnlp-main.1488","doi":"https://doi.org/10.18653/2026.emnlp-main.1488","is_oa":true,"landing_page_url":"https://doi.org/10.18653/2026.emnlp-main.1488","pdf_url":"https://aclanthology.org/2026.emnlp-main.1488.pdf","source":{"id":"https://openalex.org/S4363608991","display_name":"Conference on Empirical Methods in Natural Language Processing (EMNLP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2608.28695","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.28695","pdf_url":"https://arxiv.org/pdf/2608.28695","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2608.28695","doi":"https://doi.org/10.48550/arxiv.2608.28695","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2608.28695","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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"}],"best_oa_location":{"id":"doi:10.18653/2026.emnlp-main.1488","doi":"https://doi.org/10.18653/2026.emnlp-main.1488","is_oa":true,"landing_page_url":"https://doi.org/10.18653/2026.emnlp-main.1488","pdf_url":"https://aclanthology.org/2026.emnlp-main.1488.pdf","source":{"id":"https://openalex.org/S4363608991","display_name":"Conference on Empirical Methods in Natural Language Processing (EMNLP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7204874473.pdf","grobid_xml":"https://content.openalex.org/works/W7204874473.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7204462922","https://openalex.org/W7133297602","https://openalex.org/W7128684882","https://openalex.org/W7128486624","https://openalex.org/W7204097176","https://openalex.org/W7168133181","https://openalex.org/W4396910060","https://openalex.org/W7117164440","https://openalex.org/W4379806362","https://openalex.org/W4403791707"],"abstract_inverted_index":{"Image":[0,55],"retrieval":[1],"has":[2],"traditionally":[3],"been":[4],"formulated":[5],"as":[6,134],"a":[7,59,77,89,120,140,153],"point-wise":[8],"matching":[9],"problem,":[10],"where":[11,35],"each":[12],"candidate":[13],"image":[14,74],"is":[15],"scored":[16],"in":[17],"isolation.However,":[18],"this":[19,51,101],"atomic":[20,191],"paradigm":[21,61],"fails":[22],"to":[23,70,144,193],"capture":[24],"the":[25,64,106,162,186],"complexity":[26],"of":[27,188],"human":[28],"search":[29,146],"intent":[30],"within":[31],"personal":[32],"photo":[33,80],"collections,":[34],"users":[36],"often":[37],"seek":[38],"compact":[39],"visual":[40],"stories":[41],"bound":[42],"by":[43],"structural":[44],"relations":[45],"rather":[46],"than":[47],"isolated":[48],"snapshots.To":[49],"address":[50],"limitation,":[52],"we":[53,103,124],"introduce":[54],"Bundle":[56],"Composition":[57],"(IBC),":[58],"novel":[60],"that":[62,131,167],"shifts":[63],"objective":[65],"from":[66,76,177,190],"ranking":[67],"individual":[68],"images":[69,113],"dynamically":[71],"composing":[72],"cohesive":[73],"bundles":[75,83],"massive,":[78],"unstructured":[79],"pool.Since":[81],"target":[82],"are":[84,200],"not":[85],"predefined,":[86],"IBC":[87,108,133],"presents":[88],"severe":[90],"combinatorial":[91,163],"explosion":[92],"challenge":[93],"and":[94,114,151,172,198],"demands":[95],"modeling":[96],"non-decomposable":[97],"joint":[98],"relevance.To":[99],"establish":[100],"paradigm,":[102],"construct":[104],"IBCBench,":[105],"first":[107],"benchmark":[109],"dataset":[110,197],"containing":[111],"109,467":[112],"667":[115],"verified":[116],"queries,":[117],"built":[118],"via":[119],"semi-automated":[121],"verification":[122],"pipeline.Furthermore,":[123],"propose":[125],"BundleWeaver":[126,159,180],",":[127],"an":[128],"agentic":[129],"framework":[130],"reformulates":[132],"queryconditioned":[135],"incremental":[136],"hyperedge":[137],"discovery.By":[138],"employing":[139],"Large":[141],"Language":[142],"Model":[143,155],"adaptively":[145],"for":[147,156],"missing":[148],"relational":[149,178,195],"roles":[150],"utilizing":[152],"Vision-Language":[154],"whole-bundle":[157],"verification,":[158],"effectively":[160],"navigates":[161],"space.Extensive":[164],"experiments":[165],"demonstrate":[166],"while":[168],"state-of-the-art":[169],"embedding":[170],"models":[171],"static":[173],"decompose-and-rerank":[174],"paradigms":[175],"suffer":[176],"blindness,":[179],"achieves":[181],"substantial":[182],"performance":[183],"gains,":[184],"highlighting":[185],"necessity":[187],"shifting":[189],"scoring":[192],"dynamic":[194],"composition.Our":[196],"code":[199],"available.":[201]},"counts_by_year":[],"updated_date":"2026-11-01T11:40:01.658920","created_date":"2026-09-02T00:00:00"}
