{"id":"https://openalex.org/W4412888904","doi":"https://doi.org/10.18653/v1/2025.findings-acl.40","title":"TestAgent: An Adaptive and Intelligent Expert for Human Assessment","display_name":"TestAgent: An Adaptive and Intelligent Expert for Human Assessment","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412888904","doi":"https://doi.org/10.18653/v1/2025.findings-acl.40"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2025.findings-acl.40","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.40","pdf_url":"https://aclanthology.org/2025.findings-acl.40.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.40.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5068741728","display_name":"Junhao Yu","orcid":"https://orcid.org/0000-0002-0810-5603"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Junhao Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100735881","display_name":"Yan Zhuang","orcid":"https://orcid.org/0000-0001-7351-377X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yan Zhuang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109752972","display_name":"Yuxuan Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuxuan Sun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103148987","display_name":"Weibo Gao","orcid":"https://orcid.org/0000-0003-0894-7023"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Weibo Gao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115597047","display_name":"Qi Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qi Liu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003782450","display_name":"Mingyue Cheng","orcid":"https://orcid.org/0000-0003-1243-5039"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mingyue Cheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085496384","display_name":"Zhenya Huang","orcid":"https://orcid.org/0000-0003-1661-0420"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhenya Huang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5048237545","display_name":"Enhong Chen","orcid":"https://orcid.org/0000-0002-4835-4102"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Enhong Chen","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":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"724","last_page":"747"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11357","display_name":"Risk and Safety Analysis","score":0.5554999709129333,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"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/T11357","display_name":"Risk and Safety Analysis","score":0.5554999709129333,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6928853392601013},{"id":"https://openalex.org/keywords/expert-system","display_name":"Expert system","score":0.4541482627391815},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3861854672431946},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3400210738182068}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6928853392601013},{"id":"https://openalex.org/C58328972","wikidata":"https://www.wikidata.org/wiki/Q184609","display_name":"Expert system","level":2,"score":0.4541482627391815},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3861854672431946},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3400210738182068}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.findings-acl.40","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.40","pdf_url":"https://aclanthology.org/2025.findings-acl.40.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.40","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.40","pdf_url":"https://aclanthology.org/2025.findings-acl.40.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":[{"id":"https://openalex.org/G3552964096","display_name":null,"funder_award_id":"62406303","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4862937960","display_name":null,"funder_award_id":"U23A20319","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6991849872","display_name":null,"funder_award_id":"62477044","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320334897","display_name":"Natural Science Foundation of Anhui Province","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412888904.pdf","grobid_xml":"https://content.openalex.org/works/W4412888904.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/W2389542812","https://openalex.org/W2390279801","https://openalex.org/W2381894592","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2030629278"],"abstract_inverted_index":{"Accurately":[0],"assessing":[1],"internal":[2],"human":[3,29],"states":[4],"is":[5,113],"key":[6],"to":[7,65,90,106],"understanding":[8],"preferences,":[9],"offering":[10],"personalized":[11,123],"services,":[12],"and":[13,31,41,68,80,129,131,142,159,166],"identifying":[14],"challenges":[15],"in":[16,37,119,163],"real-world":[17],"applications.Originating":[18],"from":[19,76],"psychometrics,":[20],"adaptive":[21,53,93,108,120],"testing":[22,54,94,109],"has":[23,32],"become":[24],"the":[25,47,114],"mainstream":[26],"method":[27],"for":[28],"measurement":[30],"now":[33],"been":[34],"widely":[35],"applied":[36],"education,":[38],"healthcare,":[39],"sports,":[40],"sociology.It":[42],"customizes":[43],"assessments":[44,74,144],"by":[45],"selecting":[46],"fewest":[48],"test":[49,82],"questions":[50,155],".However,":[51],"current":[52],"methods":[55],"face":[56],"several":[57],"challenges.The":[58],"mechanized":[59],"nature":[60],"of":[61,117],"most":[62],"algorithms":[63],"leads":[64],"guessing":[66],"behavior":[67],"difficulties":[69],"with":[70,152],"open-ended":[71],"questions.Additionally,":[72],"subjective":[73],"suffer":[75],"noisy":[77],"response":[78],"data":[79],"coarsegrained":[81],"outputs,":[83],"further":[84],"limiting":[85],"their":[86],"effectiveness.To":[87],"move":[88],"closer":[89],"an":[91],"ideal":[92],"process,":[95],"we":[96],"propose":[97],"TestAgent,":[98],"a":[99],"large":[100],"language":[101],"model":[102],"(LLM)-powered":[103],"agent":[104],"designed":[105],"enhance":[107],"through":[110,135],"interactive":[111],"engagement.This":[112],"first":[115],"application":[116],"LLMs":[118],"testing.TestAgent":[121],"supports":[122],"question":[124],"selection,":[125],"captures":[126],"test-takers'":[127],"responses":[128],"anomalies,":[130],"provides":[132],"precise":[133],"outcomes":[134],"dynamic,":[136],"conversational":[137],"interactions.Experiments":[138],"on":[139],"psychological,":[140],"educational,":[141],"lifestyle":[143],"show":[145],"our":[146],"approach":[147],"achieves":[148],"more":[149],"accurate":[150],"results":[151],"20%":[153],"fewer":[154],"than":[156],"state-of-the-art":[157],"baselines,":[158],"testers":[160],"preferred":[161],"it":[162],"speed,":[164],"smoothness,":[165],"other":[167],"dimensions.":[168]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
