{"id":"https://openalex.org/W7165640400","doi":"https://doi.org/10.48550/arxiv.2606.21838","title":"Beyond Flat Labels: Level-Restricted Contrastive Learning for Hierarchical Fine-Grained Vision Classification","display_name":"Beyond Flat Labels: Level-Restricted Contrastive Learning for Hierarchical Fine-Grained Vision Classification","publication_year":2026,"publication_date":"2026-06-20","ids":{"openalex":"https://openalex.org/W7165640400","doi":"https://doi.org/10.48550/arxiv.2606.21838"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.21838","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.21838","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.2606.21838","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5086404134","display_name":"Zhiyuan Tao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tao, Zhiyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089378935","display_name":"Srikumar Sastry","orcid":"https://orcid.org/0000-0002-4646-9416"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sastry, Srikumar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139178587","display_name":"Matthew J Thompson","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Thompson, Matthew J","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139179030","display_name":"Elizabeth G Campolongo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Campolongo, Elizabeth G","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079215061","display_name":"Net Zhang","orcid":"https://orcid.org/0000-0003-2664-451X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Net","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139138313","display_name":"Ziheng Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Ziheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005484581","display_name":"Hilmar Lapp","orcid":"https://orcid.org/0000-0001-9107-0714"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lapp, Hilmar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139153265","display_name":"Yu Su","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Su, Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136478548","display_name":"Tanya Berger-Wolf","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Berger-Wolf, Tanya","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139213598","display_name":"Nathan Jacobs","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jacobs, Nathan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139138192","display_name":"Wei-Lun Chao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chao, Wei-Lun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5044808270","display_name":"Jianyang Gu","orcid":"https://orcid.org/0000-0002-4060-7427"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gu, Jianyang","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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.8726000189781189,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.8726000189781189,"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/T12859","display_name":"Cell Image Analysis Techniques","score":0.020099999383091927,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.0142000000923872,"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/consistency","display_name":"Consistency (knowledge bases)","score":0.7085999846458435},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4523000121116638},{"id":"https://openalex.org/keywords/hierarchical-database-model","display_name":"Hierarchical database model","score":0.398499995470047},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.38600000739097595},{"id":"https://openalex.org/keywords/taxonomy","display_name":"Taxonomy (biology)","score":0.3564000129699707},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.31839999556541443}],"concepts":[{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.7085999846458435},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6897000074386597},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5924000144004822},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4523000121116638},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.44359999895095825},{"id":"https://openalex.org/C144986985","wikidata":"https://www.wikidata.org/wiki/Q871236","display_name":"Hierarchical database model","level":2,"score":0.398499995470047},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.38600000739097595},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3749000132083893},{"id":"https://openalex.org/C58642233","wikidata":"https://www.wikidata.org/wiki/Q8269924","display_name":"Taxonomy (biology)","level":2,"score":0.3564000129699707},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.31839999556541443},{"id":"https://openalex.org/C129782007","wikidata":"https://www.wikidata.org/wiki/Q162886","display_name":"Euclidean geometry","level":2,"score":0.3142000138759613},{"id":"https://openalex.org/C124527596","wikidata":"https://www.wikidata.org/wiki/Q17029359","display_name":"Hierarchical control system","level":3,"score":0.29760000109672546},{"id":"https://openalex.org/C2777629044","wikidata":"https://www.wikidata.org/wiki/Q614959","display_name":"Contrastive analysis","level":2,"score":0.29269999265670776},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.26899999380111694},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2619999945163727}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.21838","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.21838","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.2606.21838","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.21838","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":[{"display_name":"Quality Education","score":0.4967183768749237,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Multimodal":[0],"contrastive":[1,59,72],"learning":[2],"has":[3],"enabled":[4],"zero-shot":[5,166],"visual":[6],"classification":[7,106,128],"by":[8,156],"aligning":[9],"images":[10],"with":[11,117],"textual":[12],"categories.":[13],"However,":[14],"in":[15,138],"hierarchically":[16],"structured":[17],"label":[18],"spaces,":[19],"existing":[20],"methods":[21],"often":[22],"produce":[23],"predictions":[24],"that":[25],"are":[26],"inconsistent":[27],"across":[28,125,154],"taxonomic":[29,63,79,90],"levels.":[30,64],"For":[31],"example,":[32],"a":[33,37,85,96],"model":[34,116,132],"may":[35],"predict":[36],"fine-grained":[38],"category":[39,42],"whose":[40],"parent":[41],"contradicts":[43],"its":[44,162],"simultaneously":[45],"predicted":[46],"higher-level":[47],"label.":[48],"By":[49],"analysis,":[50],"the":[51,77,98,131,159],"issue":[52],"originates":[53],"from":[54,108],"false":[55],"negative":[56],"labels":[57],"when":[58],"comparison":[60],"involves":[61],"multiple":[62,126],"To":[65],"this":[66],"end,":[67],"we":[68,83],"propose":[69],"to":[70,74,110],"restrict":[71],"comparisons":[73],"categories":[75],"within":[76],"same":[78],"level.":[80],"In":[81],"addition,":[82],"adopt":[84],"group-balanced":[86],"design,":[87],"ensuring":[88],"each":[89],"level":[91],"receives":[92],"adequate":[93],"optimization.":[94],"As":[95],"result,":[97],"proposed":[99],"framework":[100],"improves":[101,151],"both":[102,139],"hierarchical":[103,127,136,165],"consistency":[104,137],"and":[105,122,141],"accuracy":[107,153],"coarse":[109],"fine":[111],"granularity.":[112],"We":[113],"train":[114],"our":[115,149],"TreeOfLife-10M":[118],"based":[119],"on":[120,145],"BioCLIP":[121],"evaluate":[123],"it":[124],"benchmarks,":[129],"where":[130],"demonstrates":[133],"significantly":[134],"improved":[135],"Euclidean":[140],"hyperbolic":[142],"spaces.":[143],"Notably,":[144],"iNaturalist":[146],"2021":[147],"(iNat21),":[148],"method":[150],"average":[152],"levels":[155],"30.47%":[157],"over":[158],"baseline,":[160],"highlighting":[161],"effectiveness":[163],"for":[164],"classification.":[167]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-24T00:00:00"}
