{"id":"https://openalex.org/W7162139440","doi":"https://doi.org/10.48550/arxiv.2605.22564","title":"SynAE: A Framework for Measuring the Quality of Synthetic Data for Tool-Calling Agent Evaluations","display_name":"SynAE: A Framework for Measuring the Quality of Synthetic Data for Tool-Calling Agent Evaluations","publication_year":2026,"publication_date":"2026-05-21","ids":{"openalex":"https://openalex.org/W7162139440","doi":"https://doi.org/10.48550/arxiv.2605.22564"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.22564","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.22564","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.22564","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101447378","display_name":"Shuaiqi Wang","orcid":"https://orcid.org/0000-0003-4962-7501"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Shuaiqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136700234","display_name":"Aadyaa Maddi","orcid":"https://orcid.org/0000-0003-1493-2055"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Maddi, Aadyaa","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101422411","display_name":"Zinan Lin","orcid":"https://orcid.org/0000-0002-8421-2662"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Zinan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136799564","display_name":"Giulia Fanti","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fanti, Giulia","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":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10743","display_name":"Software Testing and Debugging Techniques","score":0.23109999299049377,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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/T10743","display_name":"Software Testing and Debugging Techniques","score":0.23109999299049377,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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/T10456","display_name":"Multi-Agent Systems and Negotiation","score":0.06960000097751617,"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/T12203","display_name":"Mobile Agent-Based Network Management","score":0.053300000727176666,"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/synthetic-data","display_name":"Synthetic data","score":0.82669997215271},{"id":"https://openalex.org/keywords/replicate","display_name":"Replicate","score":0.7753000259399414},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5985999703407288},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5504999756813049},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.5224000215530396},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.45820000767707825},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4560999870300293},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4334000051021576}],"concepts":[{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.82669997215271},{"id":"https://openalex.org/C2781162219","wikidata":"https://www.wikidata.org/wiki/Q26250693","display_name":"Replicate","level":2,"score":0.7753000259399414},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7515000104904175},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5985999703407288},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5784000158309937},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5504999756813049},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.5224000215530396},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.45820000767707825},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4560999870300293},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4334000051021576},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.4235999882221222},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4180999994277954},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.41130000352859497},{"id":"https://openalex.org/C2778348673","wikidata":"https://www.wikidata.org/wiki/Q739302","display_name":"Production (economics)","level":2,"score":0.337799996137619},{"id":"https://openalex.org/C55037315","wikidata":"https://www.wikidata.org/wiki/Q5421151","display_name":"Experimental data","level":2,"score":0.3109000027179718},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30979999899864197},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.28279998898506165},{"id":"https://openalex.org/C92446256","wikidata":"https://www.wikidata.org/wiki/Q3306762","display_name":"Data validation","level":2,"score":0.27489998936653137},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.26499998569488525},{"id":"https://openalex.org/C3020493868","wikidata":"https://www.wikidata.org/wiki/Q55631277","display_name":"Real world data","level":2,"score":0.26440000534057617},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.2556000053882599}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.22564","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.22564","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.22564","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.22564","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Today,":[0],"tool-calling":[1,101],"agents":[2,102],"are":[3,27,59],"commonly":[4],"evaluated":[5],"or":[6,30,40,43,62],"tested":[7],"on":[8],"static":[9],"datasets":[10,26,65,82],"of":[11,108,119,190,198],"execution":[12],"traces,":[13],"including":[14],"input":[15],"commands,":[16],"agent":[17,147,194],"responses,":[18,131],"and":[19,83,104,117,129,138,149,158,170,172],"associated":[20],"tool":[21,133],"calls.":[22],"However,":[23],"internal":[24],"production":[25],"often":[28],"insufficient":[29],"unusable":[31],"for":[32,34,69,93,99,193],"testing;":[33],"example,":[35],"they":[36,44],"may":[37,45],"contain":[38],"sensitive":[39],"proprietary":[41],"data,":[42],"be":[46],"too":[47],"sparse":[48],"to":[49,180],"support":[50],"comprehensive":[51],"testing":[52],"(especially":[53],"pre-deployment).":[54],"In":[55],"these":[56,80],"settings,":[57],"practitioners":[58],"increasingly":[60],"replacing":[61],"augmenting":[63],"real":[64,85,109],"with":[66,204],"synthetic":[67,81,97,120,152,183,191],"ones":[68],"evaluation":[70,91,189],"purposes.":[71],"A":[72,196],"key":[73],"challenge":[74],"is":[75,178,200],"quantifying":[76],"the":[77,84,106,114],"relation":[78],"between":[79],"data.":[86],"We":[87,142],"introduce":[88],"SynAE,":[89],"an":[90],"framework":[92],"assessing":[94],"how":[95],"well":[96],"benchmarks":[98,148],"multi-turn,":[100],"replicate":[103],"augment":[105],"characteristics":[107],"data":[110,121,153,167,184,192],"trajectories.":[111],"SynAE":[112,144,162,199],"assesses":[113],"validity,":[115,168],"fidelity,":[116],"diversity":[118],"across":[122],"four":[123],"metric":[124,177],"categories:":[125],"(i)":[126],"task":[127],"instructions":[128],"intermediate":[130],"(ii)":[132],"calls,":[134],"(iii)":[135],"final":[136],"outputs,":[137],"(iv)":[139],"downstream":[140],"evaluation.":[141],"evaluate":[143],"using":[145],"recent":[146],"test":[150],"common":[151],"failure":[154],"modes":[155],"via":[156],"realistic":[157],"controlled":[159],"generation":[160],"schemes.":[161],"detects":[163],"fine-grained":[164],"variations":[165],"in":[166],"fidelity":[169],"diversity,":[171],"shows":[173],"that":[174],"no":[175],"single":[176],"sufficient":[179],"fully":[181],"characterize":[182],"quality,":[185],"motivating":[186],"a":[187],"multi-axis":[188],"testing.":[195],"demo":[197],"available":[201],"at":[202,206],"https://synae-2026-synae-demo.static.hf.space/index.html,":[203],"code":[205],"https://github.com/wsqwsq/SynAE.":[207]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-23T00:00:00"}
