{"id":"https://openalex.org/W7128401262","doi":"https://doi.org/10.1145/3794858","title":"Generalizability of Large Language Model-Based Agents: A Comprehensive Survey","display_name":"Generalizability of Large Language Model-Based Agents: A Comprehensive Survey","publication_year":2026,"publication_date":"2026-02-07","ids":{"openalex":"https://openalex.org/W7128401262","doi":"https://doi.org/10.1145/3794858"},"language":"en","primary_location":{"id":"doi:10.1145/3794858","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3794858","pdf_url":null,"source":{"id":"https://openalex.org/S157921468","display_name":"ACM Computing Surveys","issn_l":"0360-0300","issn":["0360-0300","1557-7341"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Computing Surveys","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103119582","display_name":"Minxing Zhang","orcid":"https://orcid.org/0000-0002-5533-8514"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Minxing Zhang","raw_affiliation_strings":["Computer Science, Duke University"],"raw_orcid":"https://orcid.org/0000-0002-5533-8514","affiliations":[{"raw_affiliation_string":"Computer Science, Duke University","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125429596","display_name":"Yi Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yi Yang","raw_affiliation_strings":["Computer Science, Duke University"],"raw_orcid":"https://orcid.org/0009-0002-9957-2780","affiliations":[{"raw_affiliation_string":"Computer Science, Duke University","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125381075","display_name":"Roy Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Roy Xie","raw_affiliation_strings":["Computer Science, Duke University"],"raw_orcid":"https://orcid.org/0009-0001-1096-1820","affiliations":[{"raw_affiliation_string":"Computer Science, Duke University","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055033421","display_name":"Bhuwan Dhingra","orcid":"https://orcid.org/0000-0002-6874-9515"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bhuwan Dhingra","raw_affiliation_strings":["Computer Science, Duke University"],"raw_orcid":"https://orcid.org/0000-0002-6874-9515","affiliations":[{"raw_affiliation_string":"Computer Science, Duke University","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072549762","display_name":"S ZHOU","orcid":null},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shuyan Zhou","raw_affiliation_strings":["Computer Science, Duke University"],"raw_orcid":"https://orcid.org/0009-0006-7270-6194","affiliations":[{"raw_affiliation_string":"Computer Science, Duke University","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5125392598","display_name":"Jian Pei","orcid":null},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jian Pei","raw_affiliation_strings":["Duke University"],"raw_orcid":"https://orcid.org/0000-0002-2200-8711","affiliations":[{"raw_affiliation_string":"Duke University","institution_ids":["https://openalex.org/I170897317"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I170897317"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1367111,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"58","issue":"10","first_page":"1","last_page":"44"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.2303999960422516,"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/T10028","display_name":"Topic Modeling","score":0.2303999960422516,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.10249999910593033,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.06800000369548798,"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/generalizability-theory","display_name":"Generalizability theory","score":0.977400004863739},{"id":"https://openalex.org/keywords/categorization","display_name":"Categorization","score":0.5784000158309937},{"id":"https://openalex.org/keywords/foundation","display_name":"Foundation (evidence)","score":0.5063999891281128},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.4316999912261963}],"concepts":[{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.977400004863739},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7315999865531921},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.5784000158309937},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.5063999891281128},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.4316999912261963},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.42010000348091125},{"id":"https://openalex.org/C539667460","wikidata":"https://www.wikidata.org/wiki/Q2414942","display_name":"Management science","level":1,"score":0.3743000030517578},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3617999851703644},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.3140000104904175},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.2915000021457672},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.2567000091075897},{"id":"https://openalex.org/C74072328","wikidata":"https://www.wikidata.org/wiki/Q1142726","display_name":"Intelligent agent","level":2,"score":0.25519999861717224}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3794858","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3794858","pdf_url":null,"source":{"id":"https://openalex.org/S157921468","display_name":"ACM Computing Surveys","issn_l":"0360-0300","issn":["0360-0300","1557-7341"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Computing Surveys","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W2073708226","https://openalex.org/W2126316555","https://openalex.org/W2883445328","https://openalex.org/W2912694244","https://openalex.org/W3123742938","https://openalex.org/W4205181707","https://openalex.org/W4239236410","https://openalex.org/W4285796263","https://openalex.org/W4389518687","https://openalex.org/W4401043264","https://openalex.org/W4402671648","https://openalex.org/W4404781733","https://openalex.org/W4404783749","https://openalex.org/W4406800520","https://openalex.org/W4409635594","https://openalex.org/W4409985141","https://openalex.org/W4411120383","https://openalex.org/W4411550187","https://openalex.org/W4413918681","https://openalex.org/W4415796495","https://openalex.org/W4416035167"],"related_works":[],"abstract_inverted_index":{"Large":[0],"Language":[1],"Model":[2],"(LLM)-based":[3],"agents":[4,68,142,193],"have":[5],"recently":[6],"emerged":[7],"as":[8],"a":[9,185],"new":[10],"paradigm":[11],"that":[12,173,194],"extends":[13],"the":[14,37,55,62,83,96,120,133,160],"capabilities":[15],"of":[16,64,87,100,162],"LLMs":[17],"beyond":[18],"text":[19],"generation":[20],"to":[21,39,74,183],"dynamic":[22],"interaction":[23],"with":[24,177],"external":[25],"environments.":[26],"A":[27],"critical":[28],"challenge":[29],"lies":[30],"in":[31,66,89],"ensuring":[32],"their":[33,128],"g":[34,136,140],"eneralizability":[35],"\u2013":[36],"ability":[38],"maintain":[40],"consistently":[41],"high":[42],"performance":[43],"across":[44,197],"varied":[45],"instructions,":[46],"tasks,":[47],"environments,":[48],"and":[49,71,76,98,126,139,143,167,170],"domains,":[50],"especially":[51],"those":[52],"different":[53],"from":[54],"agent\u2019s":[56],"fine-tuning":[57],"data.":[58],"Despite":[59],"growing":[60],"interest,":[61],"concept":[63],"generalizability":[65,88,114],"LLM-based":[67,90,192],"remains":[69],"underdefined,":[70],"systematic":[72],"approaches":[73,172],"measure":[75],"improve":[77],"it":[78],"are":[79],"lacking.":[80],"We":[81,92,103,181],"provide":[82],"first":[84],"comprehensive":[85],"review":[86,105],"agents.":[91],"begin":[93],"by":[94],"clarifying":[95],"definition":[97],"boundaries":[99],"agent":[101,124,178],"generalizability.":[102,153],"then":[104],"existing":[106],"benchmarks.":[107],"Next,":[108],"we":[109,131,155],"categorize":[110],"strategies":[111],"for":[112,187],"improving":[113],"into":[115,151],"three":[116],"groups:":[117],"methods":[118],"targeting":[119,123,127],"backbone":[121],"LLM,":[122],"components,":[125],"interactions.":[129],"Furthermore,":[130],"introduce":[132],"distinction":[134],"between":[135],"eneralizable":[137,141],"frameworks":[138,147],"outline":[144],"how":[145],"generalizable":[146],"can":[148],"be":[149],"translated":[150],"agent-level":[152],"Finally,":[154],"identify":[156],"future":[157],"directions,":[158],"including":[159],"development":[161],"standardized":[163],"evaluation":[164],"frameworks,":[165],"variance-":[166],"cost-based":[168],"metrics,":[169],"hybrid":[171],"integrate":[174],"methodological":[175],"innovations":[176],"architecture-level":[179],"designs.":[180],"aim":[182],"establish":[184],"foundation":[186],"principled":[188],"research":[189],"on":[190],"building":[191],"generalize":[195],"reliably":[196],"diverse":[198],"real-world":[199],"applications.":[200]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2026-02-10T00:00:00"}