{"id":"https://openalex.org/W7125380908","doi":"https://doi.org/10.48550/arxiv.2601.14610","title":"Learning Consistent Taxonomic Classification through Hierarchical Reasoning","display_name":"Learning Consistent Taxonomic Classification through Hierarchical Reasoning","publication_year":2026,"publication_date":"2026-01-21","ids":{"openalex":"https://openalex.org/W7125380908","doi":"https://doi.org/10.48550/arxiv.2601.14610"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2601.14610","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.14610","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2601.14610","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5123574263","display_name":"Zhenghong Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Li, Zhenghong","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087247298","display_name":"Kecheng Zheng","orcid":"https://orcid.org/0000-0002-3450-400X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Kecheng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5122941675","display_name":"Haibin Ling","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ling, Haibin","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5123574263"],"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.25940001010894775,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.25940001010894775,"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/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.17149999737739563,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"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/T10895","display_name":"Species Distribution and Climate Change","score":0.14910000562667847,"subfield":{"id":"https://openalex.org/subfields/2302","display_name":"Ecological Modeling"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental 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":0.7301999926567078},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6901000142097473},{"id":"https://openalex.org/keywords/grasp","display_name":"GRASP","score":0.65829998254776},{"id":"https://openalex.org/keywords/taxonomy","display_name":"Taxonomy (biology)","score":0.5065000057220459},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4185999929904938},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.39469999074935913}],"concepts":[{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.7301999926567078},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6901000142097473},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6646999716758728},{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.65829998254776},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6416000127792358},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6098999977111816},{"id":"https://openalex.org/C58642233","wikidata":"https://www.wikidata.org/wiki/Q8269924","display_name":"Taxonomy (biology)","level":2,"score":0.5065000057220459},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4185999929904938},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.39469999074935913},{"id":"https://openalex.org/C144986985","wikidata":"https://www.wikidata.org/wiki/Q871236","display_name":"Hierarchical database model","level":2,"score":0.36489999294281006},{"id":"https://openalex.org/C48702757","wikidata":"https://www.wikidata.org/wiki/Q8269924","display_name":"Biological classification","level":2,"score":0.3343999981880188},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.32330000400543213},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.30309998989105225},{"id":"https://openalex.org/C189592816","wikidata":"https://www.wikidata.org/wiki/Q427626","display_name":"Taxonomic rank","level":3,"score":0.2775999903678894},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26350000500679016},{"id":"https://openalex.org/C2779714256","wikidata":"https://www.wikidata.org/wiki/Q25305062","display_name":"Multiple Models","level":2,"score":0.2581000030040741}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2601.14610","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.14610","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2601.14610","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.14610","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"While":[0],"Vision-Language":[1],"Models":[2],"(VLMs)":[3],"excel":[4],"at":[5],"visual":[6],"understanding,":[7],"they":[8],"often":[9],"fail":[10],"to":[11,17,44,61,79,93,109,117],"grasp":[12],"hierarchical":[13,46,67,151],"knowledge.":[14],"This":[15],"leads":[16],"common":[18],"errors":[19],"where":[20],"VLMs":[21],"misclassify":[22],"coarser":[23],"taxonomic":[24,70,99],"levels":[25],"even":[26],"when":[27],"correctly":[28],"identifying":[29],"the":[30,97,119,136,157],"most":[31],"specific":[32],"level":[33],"(leaf":[34],"level).":[35],"Existing":[36],"approaches":[37],"largely":[38],"overlook":[39],"this":[40,50,89,161],"issue":[41],"by":[42,114,144,166,181],"failing":[43],"model":[45],"reasoning.":[47],"To":[48],"address":[49],"gap,":[51],"we":[52],"propose":[53],"VL-Taxon,":[54],"a":[55,76,128,170],"two-stage,":[56],"hierarchy-based":[57],"reasoning":[58,121],"framework":[59],"designed":[60],"improve":[62],"both":[63,148],"leaf-level":[64,81,91,149],"accuracy":[65,153],"and":[66,122,150],"consistency":[68,95,152],"in":[69,147],"classification.":[71],"The":[72,84],"first":[73],"stage":[74,86,102],"employs":[75],"top-down":[77],"process":[78],"enhance":[80],"classification":[82],"accuracy.":[83],"second":[85],"then":[87],"leverages":[88],"accurate":[90],"output":[92],"ensure":[94],"throughout":[96],"entire":[98],"hierarchy.":[100],"Each":[101],"is":[103],"initially":[104],"trained":[105],"with":[106],"supervised":[107],"fine-tuning":[108,167],"instill":[110],"taxonomy":[111],"knowledge,":[112],"followed":[113],"reinforcement":[115],"learning":[116],"refine":[118],"model's":[120],"generalization":[123],"capabilities.":[124],"Extensive":[125],"experiments":[126],"reveal":[127],"remarkable":[129],"result:":[130],"our":[131],"VL-Taxon":[132],"framework,":[133],"implemented":[134],"on":[135,154,156,168,177],"Qwen2.5-VL-7B":[137],"model,":[138],"outperforms":[139],"its":[140],"original":[141],"72B":[142],"counterpart":[143],"over":[145],"10%":[146],"average":[155],"iNaturalist-2021":[158],"dataset.":[159],"Notably,":[160],"significant":[162],"gain":[163],"was":[164],"achieved":[165],"just":[169],"small":[171],"subset":[172],"of":[173],"data,":[174],"without":[175],"relying":[176],"any":[178],"examples":[179],"generated":[180],"other":[182],"VLMs.":[183]},"counts_by_year":[],"updated_date":"2026-01-23T23:24:52.574035","created_date":"2026-01-23T00:00:00"}
