{"id":"https://openalex.org/W4412887853","doi":"https://doi.org/10.18653/v1/2025.findings-acl.1073","title":"SkyLLM: Cross-LLM-APIs Federation for Cost-effective Query Processing","display_name":"SkyLLM: Cross-LLM-APIs Federation for Cost-effective Query Processing","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412887853","doi":"https://doi.org/10.18653/v1/2025.findings-acl.1073"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2025.findings-acl.1073","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.1073","pdf_url":"https://aclanthology.org/2025.findings-acl.1073.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.1073.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062194603","display_name":"Heng Zhao","orcid":"https://orcid.org/0000-0002-8505-6649"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Heng Zhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5000882682","display_name":"Yifei Zhu","orcid":"https://orcid.org/0000-0003-4352-6507"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yifei Zhu","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":1.9814,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.83983359,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"20864","last_page":"20873"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10317","display_name":"Advanced Database Systems and Queries","score":0.9944999814033508,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10317","display_name":"Advanced Database Systems and Queries","score":0.9944999814033508,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10215","display_name":"Semantic Web and Ontologies","score":0.9689000248908997,"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/T10715","display_name":"Distributed and Parallel Computing Systems","score":0.9650999903678894,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/computer-science","display_name":"Computer science","score":0.7733524441719055},{"id":"https://openalex.org/keywords/query-optimization","display_name":"Query optimization","score":0.4544617533683777},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.39746028184890747}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7733524441719055},{"id":"https://openalex.org/C157692150","wikidata":"https://www.wikidata.org/wiki/Q2919848","display_name":"Query optimization","level":2,"score":0.4544617533683777},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.39746028184890747}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.findings-acl.1073","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.1073","pdf_url":"https://aclanthology.org/2025.findings-acl.1073.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.1073","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.1073","pdf_url":"https://aclanthology.org/2025.findings-acl.1073.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":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412887853.pdf","grobid_xml":"https://content.openalex.org/works/W4412887853.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2,26],"(LLMs)":[3],"have":[4],"demonstrated":[5],"exceptional":[6],"capabilities":[7],"across":[8],"a":[9,45,49,72,76,92,114,160],"wide":[10],"range":[11],"of":[12,52,75,78,95,112],"tasks,":[13],"from":[14,152],"text":[15],"generation":[16],"to":[17,24,39,98,102,138],"complex":[18,136],"problem-solving.LLM":[19],"APIs":[20,54,88,97],"provide":[21],"easy":[22],"access":[23],"these":[25,67,96],"by":[27,176],"streamlining":[28],"deployment":[29],"and":[30,62,80,89,106,147],"usage.Combining":[31],"LLMs":[32,131,146],"with":[33],"complementary":[34],"strengths":[35],"has":[36],"been":[37],"shown":[38],"yield":[40],"substantial":[41],"performance":[42,140],"gains":[43],"over":[44],"monolithic":[46],"LLM.However,":[47],"invoking":[48],"fixed":[50],"set":[51,77],"LLM":[53,87,116,121,150,172],"for":[55,134],"each":[56,99],"query":[57,100],"incurs":[58],"higher":[59],"API":[60,82],"costs":[61,175],"increased":[63],"inference":[64,103],"latency.To":[65],"address":[66],"limitations,":[68],"we":[69],"propose":[70],"SkyLLM,":[71],"system":[73],"composed":[74],"estimators":[79],"an":[81],"selector,":[83],"which":[84],"federates":[85],"multiple":[86,118,130],"dynamically":[90],"assigns":[91],"non-empty":[93],"subset":[94,110],"prior":[101],"under":[104,159],"cost":[105],"latency":[107],"budgets.The":[108],"selected":[109],"consists":[111],"either":[113],"single":[115,120],"or":[117],"LLMs.A":[119],"efficiently":[122],"handles":[123],"simple":[124],"queries":[125,137],"at":[126],"low":[127],"cost,":[128],"whereas":[129],"are":[132],"employed":[133],"more":[135],"overcome":[139],"limitations.We":[141],"evaluate":[142],"SkyLLM":[143],"against":[144],"individual":[145,171],"representative":[148],"ensemble":[149],"methods":[151],"the":[153,156,168],"literature.SkyLLM":[154],"achieves":[155],"highest":[157],"accuracy":[158],"high":[161],"budget.It":[162],"can":[163],"also":[164],"be":[165],"cost-effective,":[166],"matching":[167],"most":[169],"accurate":[170],"while":[173],"cutting":[174],"67.8%.":[177]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
