{"id":"https://openalex.org/W4412876986","doi":"https://doi.org/10.1145/3711896.3737196","title":"Benchmarking and Advancing Large Language Models for Local Life Services","display_name":"Benchmarking and Advancing Large Language Models for Local Life Services","publication_year":2025,"publication_date":"2025-08-03","ids":{"openalex":"https://openalex.org/W4412876986","doi":"https://doi.org/10.1145/3711896.3737196"},"language":"en","primary_location":{"id":"doi:10.1145/3711896.3737196","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3711896.3737196","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3711896.3737196","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3711896.3737196","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5045832099","display_name":"Xiaochong Lan","orcid":"https://orcid.org/0000-0001-8960-4246"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaochong Lan","raw_affiliation_strings":["Department of Electronic Engineering, BNRist, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8960-4246","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, BNRist, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100668035","display_name":"Jie Feng","orcid":"https://orcid.org/0000-0003-3279-7117"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Feng","raw_affiliation_strings":["Department of Electronic Engineering, BNRist, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-3279-7117","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, BNRist, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035640074","display_name":"Jiahuan Lei","orcid":"https://orcid.org/0000-0002-5170-8645"},"institutions":[{"id":"https://openalex.org/I4210087373","display_name":"Meizu (China)","ror":"https://ror.org/0067g4302","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210087373"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiahuan Lei","raw_affiliation_strings":["Meituan, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-5170-8645","affiliations":[{"raw_affiliation_string":"Meituan, Beijing, China","institution_ids":["https://openalex.org/I4210087373"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014964385","display_name":"Xinlei Shi","orcid":"https://orcid.org/0000-0002-0733-5757"},"institutions":[{"id":"https://openalex.org/I4210087373","display_name":"Meizu (China)","ror":"https://ror.org/0067g4302","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210087373"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinlei Shi","raw_affiliation_strings":["Meituan, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0733-5757","affiliations":[{"raw_affiliation_string":"Meituan, Beijing, China","institution_ids":["https://openalex.org/I4210087373"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100355277","display_name":"Yong Li","orcid":"https://orcid.org/0000-0001-5617-1659"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Li","raw_affiliation_strings":["Department of Electronic Engineering, BNRist, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-5617-1659","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, BNRist, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5045832099"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.33188236,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4566","last_page":"4577"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11977","display_name":"Technology Use by Older Adults","score":0.9837999939918518,"subfield":{"id":"https://openalex.org/subfields/3317","display_name":"Demography"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11977","display_name":"Technology Use by Older Adults","score":0.9837999939918518,"subfield":{"id":"https://openalex.org/subfields/3317","display_name":"Demography"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11942","display_name":"Transportation and Mobility Innovations","score":0.9596999883651733,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9437000155448914,"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/benchmarking","display_name":"Benchmarking","score":0.8711984753608704},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5921429395675659},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3326886296272278},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.1807486116886139}],"concepts":[{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.8711984753608704},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5921429395675659},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3326886296272278},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.1807486116886139},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3711896.3737196","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3711896.3737196","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3711896.3737196","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3711896.3737196","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3711896.3737196","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3711896.3737196","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320322392","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412876986.pdf","grobid_xml":"https://content.openalex.org/works/W4412876986.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W2998617917","https://openalex.org/W3170739265","https://openalex.org/W4283768109","https://openalex.org/W4290944266","https://openalex.org/W4290973830","https://openalex.org/W4323655724","https://openalex.org/W4367678106","https://openalex.org/W4381930847","https://openalex.org/W4385474375","https://openalex.org/W4389636360","https://openalex.org/W4392846385","https://openalex.org/W4393065402","https://openalex.org/W4399205331","https://openalex.org/W4402671229","https://openalex.org/W4402684050","https://openalex.org/W4402901320","https://openalex.org/W4406800520","https://openalex.org/W4411119500","https://openalex.org/W4411735734","https://openalex.org/W6600120041","https://openalex.org/W6604197512","https://openalex.org/W6608504677","https://openalex.org/W6815166935","https://openalex.org/W6833494568"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4238897586","https://openalex.org/W435179959","https://openalex.org/W2619091065","https://openalex.org/W2059640416","https://openalex.org/W1490753184","https://openalex.org/W2284465472","https://openalex.org/W2291782699"],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2],"(LLMs)":[3],"have":[4],"exhibited":[5],"remarkable":[6],"capabilities":[7],"and":[8,46,77,105,114,127],"achieved":[9],"significant":[10],"breakthroughs":[11],"across":[12,54],"various":[13],"domains,":[14],"leading":[15],"to":[16,61,95],"their":[17,29,68],"widespread":[18],"adoption":[19],"in":[20,31,119],"recent":[21],"years.":[22],"Building":[23],"on":[24],"this":[25,39],"progress,":[26],"we":[27,41,70],"investigate":[28],"potential":[30],"the":[32,49,112],"realm":[33],"of":[34,51,58,116],"local":[35,62,130],"life":[36,63,131],"services.":[37,64],"In":[38],"study,":[40],"establish":[42],"a":[43,55,85,96],"comprehensive":[44],"benchmark":[45],"systematically":[47],"evaluate":[48],"performance":[50,92],"diverse":[52],"LLMs":[53,118],"wide":[56],"range":[57],"tasks":[59],"relevant":[60],"To":[65],"further":[66],"enhance":[67],"effectiveness,":[69],"explore":[71],"two":[72],"key":[73],"approaches:":[74],"model":[75,89,106],"fine-tuning":[76],"agent-based":[78],"workflows.":[79],"Our":[80],"findings":[81],"reveal":[82],"that":[83],"even":[84],"relatively":[86],"compact":[87],"7B":[88],"can":[90],"attain":[91],"levels":[93],"comparable":[94],"much":[97],"larger":[98],"72B":[99],"model,":[100],"effectively":[101],"balancing":[102],"inference":[103],"cost":[104],"capability.":[107],"This":[108],"optimization":[109],"greatly":[110],"enhances":[111],"feasibility":[113],"efficiency":[115],"deploying":[117],"real-world":[120],"online":[121],"services,":[122],"making":[123],"them":[124],"more":[125],"practical":[126],"accessible":[128],"for":[129],"applications.":[132],"Available":[133],"resources":[134],"are":[135],"at":[136],"https://github.com/tsinghua-fib-lab/LocalEval.":[137]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}