{"id":"https://openalex.org/W7165643205","doi":"https://doi.org/10.48550/arxiv.2606.22803","title":"Towards Fast Domain Adaptation and Fine-Grained User Simulation for Evaluating Conversational Recommender Systems","display_name":"Towards Fast Domain Adaptation and Fine-Grained User Simulation for Evaluating Conversational Recommender Systems","publication_year":2026,"publication_date":"2026-06-22","ids":{"openalex":"https://openalex.org/W7165643205","doi":"https://doi.org/10.48550/arxiv.2606.22803"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.22803","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.22803","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":null,"license_id":null,"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.2606.22803","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139166877","display_name":"Yuanzi Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yuanzi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139178177","display_name":"Quanyu Dai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dai, Quanyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139168320","display_name":"Xueyang Feng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Feng, Xueyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139176803","display_name":"Zihang Tian","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tian, Zihang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139212161","display_name":"Junhao Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Junhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139214315","display_name":"Xu Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Xu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139184701","display_name":"Zhenhua Dong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dong, Zhenhua","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139214393","display_name":"Huifeng Guo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Huifeng","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/T10028","display_name":"Topic Modeling","score":0.43549999594688416,"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":0.43549999594688416,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.16500000655651093,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12128","display_name":"AI in Service Interactions","score":0.09309999644756317,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5975000262260437},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.586899995803833},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.5591999888420105},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5496000051498413},{"id":"https://openalex.org/keywords/user-modeling","display_name":"User modeling","score":0.49219998717308044},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.4260999858379364},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.4129999876022339}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.882099986076355},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5975000262260437},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.586899995803833},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.5591999888420105},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5496000051498413},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.5274999737739563},{"id":"https://openalex.org/C67712803","wikidata":"https://www.wikidata.org/wiki/Q7901853","display_name":"User modeling","level":3,"score":0.49219998717308044},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4383000135421753},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.4260999858379364},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.4129999876022339},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.40869998931884766},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.3853999972343445},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.3752000033855438},{"id":"https://openalex.org/C2781162219","wikidata":"https://www.wikidata.org/wiki/Q26250693","display_name":"Replicate","level":2,"score":0.3677999973297119},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.32710000872612},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30959999561309814},{"id":"https://openalex.org/C201025465","wikidata":"https://www.wikidata.org/wiki/Q11248500","display_name":"User experience design","level":2,"score":0.2962000072002411},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.2547000050544739}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.22803","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.22803","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.22803","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.22803","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.6076129674911499}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Conversational":[0],"Recommender":[1],"Systems":[2],"(CRSs)":[3],"enhance":[4],"user":[5,22],"experience":[6],"through":[7],"multi-turn":[8],"interactions,":[9],"yet":[10],"evaluating":[11,100],"their":[12],"performance":[13],"remains":[14],"challenging.":[15],"While":[16],"Large":[17],"Language":[18],"Model":[19],"(LLM)":[20],"based":[21],"simulators":[23,69],"are":[24],"effective,":[25],"they":[26],"suffer":[27],"from":[28],"three":[29,167],"key":[30],"limitations:":[31],"(1)":[32],"Lack":[33],"of":[34,185],"Domain":[35],"Adaptability:":[36],"Reliance":[37],"on":[38],"fixed":[39],"prompts":[40],"and":[41,61,76,88,107,116,125,169,182,188],"predefined":[42],"action":[43,119],"spaces":[44],"hinders":[45],"transfer":[46],"to":[47,55,71,121],"novel":[48,153],"domains;":[49],"(2)":[50],"Limited":[51],"User":[52,92],"Modeling:":[53],"Inability":[54],"accurately":[56],"replicate":[57],"subtle":[58],"linguistic":[59],"styles":[60],"dynamic":[62],"preferences;":[63],"(3)":[64],"Insufficient":[65],"Evaluation":[66],"Validity:":[67],"Existing":[68],"fail":[70],"adequately":[72],"assess":[73],"fundamental":[74],"capabilities":[75,187],"system":[77],"robustness.":[78,189],"To":[79],"overcome":[80],"these,":[81],"we":[82,132],"propose":[83],"AdaptSim,":[84],"an":[85,96,117],"Adaptive":[86],"domain":[87],"automatic":[89,113],"prompt":[90,114],"tuning":[91],"Simulator.":[93],"AdaptSim":[94,150,174],"offers":[95],"efficient":[97],"framework":[98,160],"for":[99,141,161],"CRSs":[101],"by":[102],"enabling":[103,178],"realistic":[104,176],"behavior":[105],"modeling":[106],"diverse":[108],"style":[109],"generation.":[110],"It":[111],"leverages":[112],"generation":[115,136],"open":[118],"mechanism":[120],"reduce":[122],"manual":[123],"effort":[124],"improve":[126],"cross-domain":[127],"flexibility.":[128],"For":[129,147],"response":[130],"generation,":[131],"employ":[133],"controlled":[134],"text":[135],"with":[137],"a":[138,152,179],"\"think-then-respond\"":[139],"strategy":[140],"fine-grained":[142],"control":[143],"over":[144],"language":[145],"style.":[146],"CRS":[148,186],"evaluation,":[149],"incorporates":[151],"Breadth-First":[154],"Search":[155],"(BFS)-based,":[156],"turn-level":[157],"pairwise":[158],"comparison":[159],"comprehensive":[162],"assessment.":[163],"Extensive":[164],"experiments":[165],"across":[166],"domains":[168],"four":[170],"LLMs":[171],"demonstrate":[172],"that":[173],"generates":[175],"dialogues,":[177],"highly":[180],"effective":[181],"reliable":[183],"evaluation":[184]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-24T00:00:00"}
