{"id":"https://openalex.org/W7160391089","doi":"https://doi.org/10.48550/arxiv.2605.03706","title":"SAM-NER: Semantic Archetype Mediation for Zero-Shot Named Entity Recognition","display_name":"SAM-NER: Semantic Archetype Mediation for Zero-Shot Named Entity Recognition","publication_year":2026,"publication_date":"2026-05-05","ids":{"openalex":"https://openalex.org/W7160391089","doi":"https://doi.org/10.48550/arxiv.2605.03706"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.03706","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.03706","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.2605.03706","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076948208","display_name":"Ruichu Cai","orcid":"https://orcid.org/0000-0001-8972-167X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cai, Ruichu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041267268","display_name":"\u5e72\u9a8f\u6d9b","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gan, Juntao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004188678","display_name":"Miao Mai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mai, Miao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135422254","display_name":"Zhifeng Hao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hao, Zhifeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135482688","display_name":"Boyan Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Boyan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"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/T10028","display_name":"Topic Modeling","score":0.9057000279426575,"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/T10028","display_name":"Topic Modeling","score":0.9057000279426575,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.01510000042617321,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.0142000000923872,"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/entity-linking","display_name":"Entity linking","score":0.5907999873161316},{"id":"https://openalex.org/keywords/named-entity-recognition","display_name":"Named-entity recognition","score":0.5457000136375427},{"id":"https://openalex.org/keywords/archetype","display_name":"Archetype","score":0.5392000079154968},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5266000032424927},{"id":"https://openalex.org/keywords/schema","display_name":"Schema (genetic algorithms)","score":0.5023999810218811},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4325999915599823},{"id":"https://openalex.org/keywords/semantic-role-labeling","display_name":"Semantic role labeling","score":0.3953000009059906},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.3894999921321869}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.815500020980835},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.7639999985694885},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6725999712944031},{"id":"https://openalex.org/C96711827","wikidata":"https://www.wikidata.org/wiki/Q17012245","display_name":"Entity linking","level":3,"score":0.5907999873161316},{"id":"https://openalex.org/C2779135771","wikidata":"https://www.wikidata.org/wiki/Q403574","display_name":"Named-entity recognition","level":3,"score":0.5457000136375427},{"id":"https://openalex.org/C49848784","wikidata":"https://www.wikidata.org/wiki/Q131714","display_name":"Archetype","level":2,"score":0.5392000079154968},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5266000032424927},{"id":"https://openalex.org/C52146309","wikidata":"https://www.wikidata.org/wiki/Q7431116","display_name":"Schema (genetic algorithms)","level":2,"score":0.5023999810218811},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4325999915599823},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.40400001406669617},{"id":"https://openalex.org/C67277372","wikidata":"https://www.wikidata.org/wiki/Q7449085","display_name":"Semantic role labeling","level":3,"score":0.3953000009059906},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3894999921321869},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.3490000069141388},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.33570000529289246},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.303600013256073},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.27730000019073486},{"id":"https://openalex.org/C202708506","wikidata":"https://www.wikidata.org/wiki/Q7449050","display_name":"Semantic compression","level":5,"score":0.27399998903274536},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.27390000224113464},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.26600000262260437},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.2635999917984009},{"id":"https://openalex.org/C3746660","wikidata":"https://www.wikidata.org/wiki/Q1068763","display_name":"Rule of inference","level":2,"score":0.26089999079704285},{"id":"https://openalex.org/C112313634","wikidata":"https://www.wikidata.org/wiki/Q7886648","display_name":"Complement (music)","level":5,"score":0.2540999948978424}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.03706","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.03706","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.2605.03706","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.03706","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Zero-shot":[0],"Named":[1],"Entity":[2],"Recognition":[3],"(ZS-NER)":[4],"remains":[5],"brittle":[6],"under":[7],"domain":[8],"and":[9,81,110],"schema":[10],"shifts,":[11],"where":[12],"unseen":[13],"label":[14],"definitions":[15],"often":[16],"misalign":[17],"with":[18,126],"a":[19,28,55,98,127],"large":[20],"language":[21],"model's":[22],"(LLM's)":[23],"intrinsic":[24],"semantic":[25,41,103],"organization.":[26],"As":[27],"result,":[29],"directly":[30],"mapping":[31],"entity":[32,88],"mentions":[33],"to":[34,84,115],"fine-grained":[35],"target":[36,45],"labels":[37],"can":[38],"induce":[39],"systematic":[40],"drift,":[42],"especially":[43],"when":[44],"schemas":[46],"are":[47],"novel":[48],"or":[49],"semantically":[50],"overlapping.":[51],"We":[52],"propose":[53],"\\textbf{SAM-NER},":[54],"three-stage":[56],"framework":[57],"based":[58],"on":[59,131],"\\emph{Semantic":[60,113],"Archetype":[61],"Mediation}":[62,93],"that":[63,136],"stabilizes":[64],"cross-domain":[65,145],"transfer":[66],"through":[67,122],"an":[68],"intermediate,":[69],"domain-invariant":[70],"archetype":[71],"space.":[72],"SAM-NER:":[73],"(i)":[74],"performs":[75],"\\emph{Entity":[76],"Discovery}":[77],"via":[78],"cooperative":[79],"extraction":[80],"consensus-based":[82],"denoising":[83],"obtain":[85],"high-coverage,":[86],"high-fidelity":[87],"spans;":[89],"(ii)":[90],"conducts":[91],"\\emph{Abstract":[92],"by":[94],"projecting":[95],"entities":[96],"into":[97,119],"compact":[99],"set":[100],"of":[101],"universal":[102],"archetypes":[104],"distilled":[105],"from":[106],"high-level":[107],"ontological":[108],"abstractions;":[109],"(iii)":[111],"applies":[112],"Calibration}":[114],"resolve":[116],"archetype-level":[117],"predictions":[118],"target-domain":[120],"types":[121],"constrained,":[123],"definition-aligned":[124],"inference":[125],"frozen":[128],"LLM.":[129],"Experiments":[130],"the":[132],"CrossNER":[133],"benchmark":[134],"show":[135],"SAM-NER":[137],"consistently":[138],"outperforms":[139],"strong":[140],"prior":[141],"ZS-NER":[142],"baselines":[143],"in":[144],"settings.":[146],"Our":[147],"implementation":[148],"will":[149],"be":[150],"open-sourced":[151],"at":[152],"https://github.com/DMIRLAB-Group/SAM-NER.":[153]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-07T00:00:00"}
