{"id":"https://openalex.org/W4412888312","doi":"https://doi.org/10.18653/v1/2025.findings-acl.608","title":"Selecting Demonstrations for Many-Shot In-Context Learning via Gradient Matching","display_name":"Selecting Demonstrations for Many-Shot In-Context Learning via Gradient Matching","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412888312","doi":"https://doi.org/10.18653/v1/2025.findings-acl.608"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2025.findings-acl.608","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.608","pdf_url":"https://aclanthology.org/2025.findings-acl.608.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 2025","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.findings-acl.608.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5055364520","display_name":"Jianfei Zhang","orcid":"https://orcid.org/0000-0002-2664-5216"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jianfei Zhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107028150","display_name":"Bei Li","orcid":"https://orcid.org/0000-0001-7617-9041"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bei Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087193008","display_name":"Jun Bai","orcid":"https://orcid.org/0000-0002-5500-3976"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jun Bai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037808708","display_name":"Rumei Li","orcid":"https://orcid.org/0000-0001-7353-6242"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rumei Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101856072","display_name":"Yanmeng Wang","orcid":"https://orcid.org/0000-0002-5423-0990"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yanmeng Wang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024599321","display_name":"Chenghua Lin","orcid":"https://orcid.org/0000-0003-3454-2468"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chenghua Lin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5055420596","display_name":"Wenge Rong","orcid":"https://orcid.org/0000-0002-4229-7215"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wenge Rong","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":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"11686","last_page":"11704"},"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":0.992900013923645,"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":0.992900013923645,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.919700026512146,"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/shot","display_name":"Shot (pellet)","score":0.7375882863998413},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7030688524246216},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6594448089599609},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.6444075703620911},{"id":"https://openalex.org/keywords/one-shot","display_name":"One shot","score":0.5066645741462708},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4417073428630829},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.15201935172080994},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07516390085220337},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.07327431440353394},{"id":"https://openalex.org/keywords/mechanical-engineering","display_name":"Mechanical engineering","score":0.061785757541656494}],"concepts":[{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.7375882863998413},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7030688524246216},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6594448089599609},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6444075703620911},{"id":"https://openalex.org/C2992734406","wikidata":"https://www.wikidata.org/wiki/Q413267","display_name":"One shot","level":2,"score":0.5066645741462708},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4417073428630829},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15201935172080994},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07516390085220337},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.07327431440353394},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.061785757541656494},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.findings-acl.608","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.608","pdf_url":"https://aclanthology.org/2025.findings-acl.608.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 2025","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.findings-acl.608","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.608","pdf_url":"https://aclanthology.org/2025.findings-acl.608.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 2025","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4558726929","display_name":null,"funder_award_id":"62477001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"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/W4412888312.pdf","grobid_xml":"https://content.openalex.org/works/W4412888312.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2497720472","https://openalex.org/W4292659306","https://openalex.org/W3044321615","https://openalex.org/W2806221744","https://openalex.org/W2326937258","https://openalex.org/W394267150","https://openalex.org/W2773965352","https://openalex.org/W4294892107","https://openalex.org/W2357748469","https://openalex.org/W2392917037"],"abstract_inverted_index":{"In-Context":[0],"Learning":[1],"(ICL)":[2],"empowers":[3],"Large":[4],"Language":[5],"Models":[6],"(LLMs)":[7],"for":[8,36,54,63,173],"rapid":[9],"task":[10,94],"adaptation":[11],"without":[12],"Fine-Tuning":[13],"(FT),":[14],"but":[15],"its":[16,174],"reliance":[17],"on":[18,106,117,131,150,158],"demonstration":[19],"selection":[20,34,43,130,147],"remains":[21,39],"a":[22,74],"critical":[23],"challenge.While":[24],"many-shot":[25,37,168],"ICL":[26],"shows":[27],"promising":[28],"performance":[29],"through":[30],"scaled":[31],"demonstrations,":[32],"the":[33,47,60,87,92,96,103,107,112,171],"method":[35,126],"demonstrations":[38,81],"limited":[40],"to":[41,101,136],"random":[42,129,146],"in":[44],"existing":[45],"work.Since":[46],"conventional":[48],"instance-level":[49],"retrieval":[50],"is":[51],"not":[52],"suitable":[53],"manyshot":[55],"scenarios,":[56],"we":[57,72],"hypothesize":[58],"that":[59,79],"data":[61],"requirements":[62],"in-context":[64],"learning":[65,104],"and":[66,95,152,154,166],"finetuning":[67],"are":[68],"analogous.To":[69],"this":[70],"end,":[71],"introduce":[73],"novel":[75],"gradient":[76,115],"matching":[77,116],"approach":[78,102],"selects":[80],"by":[82,148,155],"aligning":[83],"fine-tuning":[84],"gradients":[85],"between":[86],"entire":[88,108],"training":[89,109],"set":[90,110],"of":[91],"target":[93],"selected":[97,113],"examples,":[98],"so":[99],"as":[100],"effect":[105],"within":[111],"examples.Through":[114],"relatively":[118],"small":[119],"models,":[120],"e.g.,":[121],"Qwen2.5-3B":[122],"or":[123],"Llama3-8B,":[124],"our":[125],"consistently":[127],"outperforms":[128],"larger":[132],"LLMs":[133],"from":[134],"4-shot":[135],"128-shot":[137],"scenarios":[138],"across":[139],"9":[140],"diverse":[141],"datasets.For":[142],"instance,":[143],"it":[144],"surpasses":[145],"4%":[149],"Qwen2.5-72B":[151],"Llama3-70B,":[153],"around":[156],"2%":[157],"5":[159],"closedsource":[160],"LLMs.This":[161],"work":[162],"unlocks":[163],"more":[164],"reliable":[165],"effective":[167],"ICL,":[169],"paving":[170],"way":[172],"broader":[175],"application.":[176]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}