{"id":"https://openalex.org/W4400023192","doi":"https://doi.org/10.18653/v1/2026.findings-acl.314","title":"Label Words as Local Task Vectors in In-Context Learning","display_name":"Label Words as Local Task Vectors in In-Context Learning","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W4400023192","doi":"https://doi.org/10.18653/v1/2026.findings-acl.314"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2026.findings-acl.314","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.314","pdf_url":"https://aclanthology.org/2026.findings-acl.314.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: ACL 2026","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2026.findings-acl.314.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5050833745","display_name":"Bowen Zheng","orcid":"https://orcid.org/0000-0002-2762-4441"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bowen Zheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100527546","display_name":"Ming Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ming Ma","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041057969","display_name":"Zhongqiao Lin","orcid":"https://orcid.org/0000-0003-2516-0230"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhongqiao Lin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100719213","display_name":"Tianming Yang","orcid":"https://orcid.org/0000-0003-3700-0912"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tianming Yang","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":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.00175551,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"6319","last_page":"6332"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9527999758720398,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9527999758720398,"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/key","display_name":"Key (lock)","score":0.6803675889968872},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.6459993124008179},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6419085264205933},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5638121366500854},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3584197461605072},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.32084542512893677},{"id":"https://openalex.org/keywords/epistemology","display_name":"Epistemology","score":0.0961885154247284},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.09073719382286072},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08399662375450134}],"concepts":[{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.6803675889968872},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.6459993124008179},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6419085264205933},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5638121366500854},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3584197461605072},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.32084542512893677},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0961885154247284},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.09073719382286072},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08399662375450134},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.18653/v1/2026.findings-acl.314","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.314","pdf_url":"https://aclanthology.org/2026.findings-acl.314.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: ACL 2026","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2406.16007","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2406.16007","pdf_url":"https://arxiv.org/pdf/2406.16007","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,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2406.16007","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2406.16007","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,"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:10.18653/v1/2026.findings-acl.314","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.314","pdf_url":"https://aclanthology.org/2026.findings-acl.314.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: ACL 2026","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4400023192.pdf","grobid_xml":"https://content.openalex.org/works/W4400023192.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2382997850","https://openalex.org/W2390968135","https://openalex.org/W2382213751","https://openalex.org/W2351750670","https://openalex.org/W1597848696","https://openalex.org/W2354715126","https://openalex.org/W2388563748","https://openalex.org/W2375179084","https://openalex.org/W2366646518","https://openalex.org/W3204019825"],"abstract_inverted_index":{"Large":[0],"Language":[1],"Models":[2],"(LLMs)":[3],"have":[4],"demonstrated":[5],"remarkable":[6],"abilities,":[7],"one":[8],"of":[9,175],"the":[10,21,34,39,58,61,71,121,142,161,179,186],"most":[11],"important":[12],"being":[13],"in-context":[14],"learning":[15],"(ICL).With":[16],"ICL,":[17],"LLMs":[18,76],"can":[19,52,66,110],"derive":[20],"underlying":[22,188],"rule":[23],"from":[24,114,178],"a":[25,42,92,136,172],"few":[26],"demonstrations":[27],"and":[28,65,134],"provide":[29],"answers":[30],"that":[31,38,90,105,109,167],"comply":[32],"with":[33,81,141],"rule.Previous":[35],"work":[36],"hypothesized":[37],"network":[40],"creates":[41],"task":[43,50,63,73,94,138,154,163,169],"vector":[44,51,74,95,139],"in":[45,99,103,148,157,190],"specific":[46],"positions":[47],"during":[48],"ICL.The":[49],"be":[53,68,112,196],"computed":[54],"by":[55,124],"averaging":[56],"across":[57],"dataset.It":[59],"conveys":[60],"overall":[62],"information":[64,122,200],"thus":[67],"considered":[69],"global.Patching":[70],"global":[72,93,162],"allows":[75],"to":[77,85,130],"achieve":[78],"zeroshot":[79],"performance":[80],"dummy":[82],"inputs":[83],"comparable":[84],"few-shot":[86],"learning.However,":[87],"we":[88],"find":[89],"such":[91,117],"does":[96],"not":[97,147],"exist":[98],"all":[100,151],"tasks,":[101,150],"especially":[102],"tasks":[104,145],"rely":[106],"on":[107],"rules":[108,176],"only":[111],"inferred":[113],"multiple":[115],"demonstrations,":[116],"as":[118],"categorization":[119,149],"tasks.Instead,":[120],"provided":[123],"each":[125],"demonstration":[126],"is":[127],"first":[128],"transmitted":[129],"its":[131],"answer":[132],"position":[133],"forms":[135],"local":[137,153,168],"associated":[140],"demonstration.In":[143],"some":[144],"but":[146],"demonstrations'":[152],"vectors":[155,170],"converge":[156],"later":[158],"layers,":[159],"forming":[160],"vector.We":[164],"further":[165],"show":[166],"encode":[171],"high-level":[173],"abstraction":[174],"extracted":[177],"demonstrations.Our":[180],"study":[181],"provides":[182],"novel":[183],"insights":[184],"into":[185],"mechanism":[187],"ICL":[189,194],"LLMs,":[191],"demonstrating":[192],"how":[193],"may":[195],"achieved":[197],"through":[198],"an":[199],"aggregation":[201],"mechanism.":[202]},"counts_by_year":[],"updated_date":"2026-07-31T08:31:51.225901","created_date":"2025-10-10T00:00:00"}