{"id":"https://openalex.org/W4393147428","doi":"https://doi.org/10.1609/aaai.v38i10.29003","title":"Data Shunt: Collaboration of Small and Large Models for Lower Costs and Better Performance","display_name":"Data Shunt: Collaboration of Small and Large Models for Lower Costs and Better Performance","publication_year":2024,"publication_date":"2024-03-24","ids":{"openalex":"https://openalex.org/W4393147428","doi":"https://doi.org/10.1609/aaai.v38i10.29003"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v38i10.29003","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/29003/29904","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true},"type":"article","type_crossref":"journal-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/29003/29904","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5111358918","display_name":"Chen Dong","orcid":"https://orcid.org/0009-0001-5224-3093"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Chen","raw_affiliation_strings":["Zhejiang University"],"affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008666077","display_name":"Yueting Zhuang","orcid":"https://orcid.org/0000-0001-9017-2508"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yueting Zhuang","raw_affiliation_strings":["Zhejiang University"],"affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100450341","display_name":"Shuo Zhang","orcid":"https://orcid.org/0000-0001-7251-2943"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuo Zhang","raw_affiliation_strings":["Zhejiang University"],"affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010674530","display_name":"Jinfeng Liu","orcid":"https://orcid.org/0000-0002-6444-9427"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jinfeng Liu","raw_affiliation_strings":["Ant Group"],"affiliations":[{"raw_affiliation_string":"Ant Group","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104257263","display_name":"Dong Su","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Su Dong","raw_affiliation_strings":["Ant Group"],"affiliations":[{"raw_affiliation_string":"Ant Group","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063062444","display_name":"Siliang Tang","orcid":"https://orcid.org/0000-0002-7356-9711"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Siliang Tang","raw_affiliation_strings":["Zhejiang University"],"affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"fulltext_origin":"pdf","cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":83},"biblio":{"volume":"38","issue":"10","first_page":"11249","last_page":"11257"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11986","display_name":"Scientific Computing and Data Management","score":0.5379,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11986","display_name":"Scientific Computing and Data Management","score":0.5379,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[],"concepts":[{"id":"https://openalex.org/C2780968331","wikidata":"https://www.wikidata.org/wiki/Q1890115","display_name":"Shunt (medical)","level":2,"score":0.6123767},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.54118603},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2480579},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.186277}],"mesh":[],"locations_count":1,"locations":[{"is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v38i10.29003","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/29003/29904","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v38i10.29003","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/29003/29904","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.45}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":35,"referenced_works":["https://openalex.org/W1514535095","https://openalex.org/W1832693441","https://openalex.org/W1861492603","https://openalex.org/W2027731328","https://openalex.org/W2033178790","https://openalex.org/W2060277733","https://openalex.org/W2194775991","https://openalex.org/W2469885745","https://openalex.org/W2562607067","https://openalex.org/W2781292787","https://openalex.org/W2792765514","https://openalex.org/W2896457183","https://openalex.org/W3011722050","https://openalex.org/W3033186130","https://openalex.org/W3034368386","https://openalex.org/W3098649723","https://openalex.org/W3185341429","https://openalex.org/W3195577433","https://openalex.org/W4221167110","https://openalex.org/W4224308101","https://openalex.org/W4225323055","https://openalex.org/W4225591000","https://openalex.org/W4226278401","https://openalex.org/W4226479682","https://openalex.org/W4229005866","https://openalex.org/W4283026156","https://openalex.org/W4292779060","https://openalex.org/W4313066313","https://openalex.org/W4318718936","https://openalex.org/W4322631505","https://openalex.org/W4324321325","https://openalex.org/W4376122773","https://openalex.org/W4385714029","https://openalex.org/W4386075647","https://openalex.org/W4389072004"],"related_works":["https://openalex.org/W4391913857","https://openalex.org/W2748952813","https://openalex.org/W2530322880","https://openalex.org/W2478288626","https://openalex.org/W2390279801","https://openalex.org/W2382290278","https://openalex.org/W2376932109","https://openalex.org/W2358668433","https://openalex.org/W2350741829","https://openalex.org/W2001405890"],"abstract_inverted_index":{"Pretrained":[0,20],"large":[1,4,21,39,60,89,142,154,191,202,241],"models,":[2,6,61,90,203],"particularly":[3],"language":[5],"have":[7,13,41],"garnered":[8],"increasing":[9],"attention,":[10],"as":[11,26],"they":[12],"demonstrated":[14],"remarkable":[15,226],"abilities":[16],"through":[17],"contextual":[18],"learning.":[19],"models":[22,40,86,97,110,155],"are":[23,92,278],"increasingly":[24],"recognized":[25],"fundamental":[27],"tools":[28],"for":[29,137,274,280],"solving":[30],"various":[31],"tasks.":[32],"However,":[33],"the":[34,56,76,80,149,165,170,177,185,196,199,234,237,264,275],"substantial":[35],"computational":[36],"demands":[37],"of":[38,59,84,139,173,198,236,249,261],"dissuaded":[42],"most":[43],"product":[44,71],"teams":[45,72],"and":[46,73,141,201,209,222,231,256],"individuals":[47],"from":[48],"running":[49],"them.":[50],"In":[51],"such":[52],"scenarios,":[53],"to":[54,88,121,125,190,219,269],"leverage":[55,195],"exceptional":[57],"performance":[58,83,227],"one":[62],"must":[63],"solely":[64],"depend":[65],"on":[66,251],"costly":[67],"APIs,":[68],"further":[69,194],"burdening":[70],"individuals.":[74],"On":[75],"other":[77],"hand,":[78],"despite":[79],"overall":[81,160],"inferior":[82],"small":[85,96,109,140,174,200],"compared":[87],"there":[91],"certain":[93,122],"distributions":[94],"where":[95],"can":[98],"achieve":[99],"comparable":[100],"or":[101],"even":[102],"superior":[103,126],"results.":[104],"For":[105,243],"instance,":[106,244],"during":[107],"training,":[108],"may":[111],"become":[112],"trapped":[113],"in":[114],"a":[115,134,182],"local":[116],"optimum":[117],"that":[118],"is":[119,188],"unique":[120],"distributions,":[123],"leading":[124,218],"performance.":[127,161],"Hence,":[128],"we":[129,204],"propose":[130],"Data":[131],"Shunt":[132],"(DS),":[133],"general":[135],"paradigm":[136],"collaboration":[138],"models.":[143,175,192,242],"DS":[144,163,239,257],"not":[145],"only":[146,270],"substantially":[147],"reduces":[148],"cost":[150,265],"associated":[151],"with":[152],"deploying":[153],"but":[156],"also":[157],"effectively":[158],"enhances":[159],"Specifically,":[162],"determines":[164],"shunting":[166],"direction":[167],"by":[168],"evaluating":[169],"confidence":[171,178],"level":[172,179],"When":[176],"falls":[180],"below":[181],"specific":[183],"threshold,":[184],"input":[186],"data":[187],"forwarded":[189],"To":[193],"advantages":[197],"introduce":[205],"Prompt":[206],"Pruning":[207],"(PP)":[208],"2-Stage":[210],"Confidence":[211],"Distillation":[212],"(2CD),":[213],"which":[214],"facilitate":[215],"mutual":[216],"collaboration,":[217],"better":[220],"results":[221],"less":[223],"cost.":[224],"The":[225,272],"across":[228],"diverse":[229],"modalities":[230],"tasks":[232],"demonstrates":[233],"superiority":[235],"proposed":[238,276],"over":[240],"ChatGPT":[245],"achieves":[246,258],"an":[247,259],"accuracy":[248,260],"94.43%":[250],"Amazon":[252],"Product":[253],"sentiment":[254],"analysis,":[255],"95.64%,":[262],"while":[263],"has":[266],"been":[267],"reduced":[268],"31.18%.":[271],"code":[273],"method":[277],"provided":[279],"research":[281],"purposes":[282],"https://github.com/Anfeather/Data-Shunt.":[283]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4393147428","counts_by_year":[],"updated_date":"2025-01-17T11:40:52.634749","created_date":"2024-03-26"}