{"id":"https://openalex.org/W7129081929","doi":"https://doi.org/10.1145/3773966.3777996","title":"Mixture of Adaptive Retrieval Experts for Veracity Assessment in the Human\u2013LLM Mixed Generation Paradigm","display_name":"Mixture of Adaptive Retrieval Experts for Veracity Assessment in the Human\u2013LLM Mixed Generation Paradigm","publication_year":2026,"publication_date":"2026-02-16","ids":{"openalex":"https://openalex.org/W7129081929","doi":"https://doi.org/10.1145/3773966.3777996"},"language":null,"primary_location":{"id":"doi:10.1145/3773966.3777996","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3773966.3777996","pdf_url":null,"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 Nineteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3773966.3777996","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5051511394","display_name":"Ruohan Zong","orcid":"https://orcid.org/0000-0002-6499-3406"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ruohan Zong","raw_affiliation_strings":["School of Information Sciences, University of Illinois Urbana-Champaign, Champaign, IL, USA"],"affiliations":[{"raw_affiliation_string":"School of Information Sciences, University of Illinois Urbana-Champaign, Champaign, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012273910","display_name":"Y. Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I83328450","display_name":"Miami University","ror":"https://ror.org/05nbqxr67","country_code":"US","type":"education","lineage":["https://openalex.org/I83328450"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yang Zhang","raw_affiliation_strings":["Department of Computer Science and Software Engineering, Miami University, Oxford, OH, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Software Engineering, Miami University, Oxford, OH, USA","institution_ids":["https://openalex.org/I83328450"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048013870","display_name":"Zhenrui Yue","orcid":"https://orcid.org/0000-0002-0309-2065"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhenrui Yue","raw_affiliation_strings":["School of Information Sciences, University of Illinois Urbana-Champaign, Champaign, IL, USA"],"affiliations":[{"raw_affiliation_string":"School of Information Sciences, University of Illinois Urbana-Champaign, Champaign, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5126137896","display_name":"Dong Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dong Wang","raw_affiliation_strings":["School of Information Sciences, University of Illinois Urbana-Champaign, Champaign, IL, USA"],"affiliations":[{"raw_affiliation_string":"School of Information Sciences, University of Illinois Urbana-Champaign, Champaign, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5051511394"],"corresponding_institution_ids":["https://openalex.org/I157725225"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.44908788,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1047","last_page":"1057"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.5365999937057495,"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":0.5365999937057495,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.2549000084400177,"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/T13274","display_name":"Expert finding and Q&A systems","score":0.053300000727176666,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.675599992275238},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.4348999857902527},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.41589999198913574},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3407999873161316},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.335099995136261},{"id":"https://openalex.org/keywords/adaptive-learning","display_name":"Adaptive learning","score":0.326200008392334}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8208000063896179},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.675599992275238},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5218999981880188},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.45249998569488525},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43849998712539673},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.4348999857902527},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.41589999198913574},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3407999873161316},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.335099995136261},{"id":"https://openalex.org/C125014702","wikidata":"https://www.wikidata.org/wiki/Q4680749","display_name":"Adaptive learning","level":2,"score":0.326200008392334},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.29829999804496765},{"id":"https://openalex.org/C2993807640","wikidata":"https://www.wikidata.org/wiki/Q103709453","display_name":"Attention network","level":2,"score":0.29670000076293945},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.28279998898506165},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.27869999408721924},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.2759000062942505},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.2678999900817871}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3773966.3777996","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3773966.3777996","pdf_url":null,"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 Nineteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3773966.3777996","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3773966.3777996","pdf_url":null,"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 Nineteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.801421582698822,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2970641574","https://openalex.org/W3013655557","https://openalex.org/W3174306305","https://openalex.org/W3174408325","https://openalex.org/W3196268181","https://openalex.org/W3217305727","https://openalex.org/W4221148143","https://openalex.org/W4321485409","https://openalex.org/W4385570777","https://openalex.org/W4389518708","https://openalex.org/W4389518895","https://openalex.org/W4389519118","https://openalex.org/W4401042753","https://openalex.org/W4401213616","https://openalex.org/W4402669975","https://openalex.org/W4402671841","https://openalex.org/W4404534210","https://openalex.org/W4404782031","https://openalex.org/W4404783049","https://openalex.org/W4407953208"],"related_works":[],"abstract_inverted_index":{"The":[0],"growing":[1],"prevalence":[2],"of":[3,98,107,147],"false":[4,36],"information":[5,37],"originating":[6],"from":[7],"human\u2013LLM":[8,155],"mixed":[9,156],"generation":[10,20,53,100,150],"sources":[11,21],"presents":[12],"new":[13],"challenges":[14],"for":[15,56,65,124],"veracity":[16,57,139],"assessment,":[17],"as":[18],"different":[19,99],"(e.g.,":[22],"human":[23],"or":[24,87],"LLM)":[25],"exhibit":[26],"distinct":[27,92],"semantic":[28,93],"patterns":[29],"and":[30,43,95,118,142],"retrieval":[31,63,96],"needs.":[32],"In":[33],"particular,":[34],"LLM-generated":[35],"is":[38],"often":[39,59],"more":[40],"fluent,":[41],"persuasive,":[42],"difficult":[44],"to":[45,73,116,122,137],"detect":[46],"than":[47],"traditional":[48],"human-written":[49],"content.":[50],"Existing":[51],"retrieval-augmented":[52],"(RAG)":[54],"methods":[55,80],"assessment":[58,140],"use":[60],"a":[61,105,129],"uniform":[62],"strategy":[64],"all":[66],"inputs,":[67],"limiting":[68],"their":[69],"flexibility":[70],"in":[71],"adapting":[72],"varying":[74],"content":[75],"characteristics.":[76],"Current":[77],"adaptive":[78],"RAG":[79,163],"primarily":[81],"focus":[82],"on":[83,153],"general":[84],"input":[85],"difficulty":[86],"model":[88],"confidence,":[89],"overlooking":[90],"the":[91,148],"characteristics":[94],"needs":[97],"sources.":[101],"We":[102],"propose":[103],"MoARE,":[104],"Mixture":[106],"Adaptive":[108],"Retrieval":[109],"Experts":[110],"framework":[111],"that":[112,159],"dynamically":[113],"determines":[114],"whether":[115],"retrieve":[117,123],"how":[119],"much":[120],"evidence":[121],"each":[125],"post.":[126],"MoARE":[127,160],"leverages":[128],"Mixture-of-Experts":[130],"(MoE)":[131],"network":[132],"trained":[133],"via":[134],"reinforcement":[135],"learning":[136],"balance":[138],"accuracy":[141,167],"time":[143,170],"cost\u2014without":[144],"requiring":[145],"knowledge":[146],"input's":[149],"source.":[151],"Experiments":[152],"recent":[154],"datasets":[157],"demonstrate":[158],"outperforms":[161],"state-of-the-art":[162],"baselines,":[164],"achieving":[165],"higher":[166],"with":[168],"lower":[169],"cost.":[171]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2026-02-17T00:00:00"}
