{"id":"https://openalex.org/W7164038197","doi":"https://doi.org/10.48550/arxiv.2606.08397","title":"TrustMargin: Training-Free Arbitration between Parametric Memory and Retrieved Evidence in Large Language Models","display_name":"TrustMargin: Training-Free Arbitration between Parametric Memory and Retrieved Evidence in Large Language Models","publication_year":2026,"publication_date":"2026-06-07","ids":{"openalex":"https://openalex.org/W7164038197","doi":"https://doi.org/10.48550/arxiv.2606.08397"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.08397","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.08397","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.2606.08397","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5081869985","display_name":"Jingyan Xu","orcid":"https://orcid.org/0000-0002-4093-855X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Jingyan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138245797","display_name":"Hong Shi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shi, Hong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138217528","display_name":"Yi Shan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shan, Yi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101645402","display_name":"Penghui Liu","orcid":"https://orcid.org/0000-0003-4928-6874"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Penghui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138214439","display_name":"Yunhao Bai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bai, Yunhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138286012","display_name":"Ningyuan Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Ningyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138205067","display_name":"Xueyang Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Xueyang","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":0.7857000231742859,"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":0.7857000231742859,"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":0.03539999946951866,"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":0.0284000001847744,"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/salience","display_name":"Salience (neuroscience)","score":0.5848000049591064},{"id":"https://openalex.org/keywords/oracle","display_name":"Oracle","score":0.5838000178337097},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.483599990606308},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.38850000500679016},{"id":"https://openalex.org/keywords/arbitration","display_name":"Arbitration","score":0.3612000048160553},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.3610999882221222}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7106999754905701},{"id":"https://openalex.org/C108154423","wikidata":"https://www.wikidata.org/wiki/Q1469792","display_name":"Salience (neuroscience)","level":2,"score":0.5848000049591064},{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.5838000178337097},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5378999710083008},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.483599990606308},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43309998512268066},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.38850000500679016},{"id":"https://openalex.org/C160151201","wikidata":"https://www.wikidata.org/wiki/Q207946","display_name":"Arbitration","level":2,"score":0.3612000048160553},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.3610999882221222},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.30329999327659607},{"id":"https://openalex.org/C2985998994","wikidata":"https://www.wikidata.org/wiki/Q3644502","display_name":"Source model","level":2,"score":0.29899999499320984},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.29409998655319214},{"id":"https://openalex.org/C12186640","wikidata":"https://www.wikidata.org/wiki/Q6815743","display_name":"Memory model","level":3,"score":0.2856999933719635},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.27469998598098755},{"id":"https://openalex.org/C2779848117","wikidata":"https://www.wikidata.org/wiki/Q1187201","display_name":"International arbitration","level":3,"score":0.2678000032901764},{"id":"https://openalex.org/C191072391","wikidata":"https://www.wikidata.org/wiki/Q17043235","display_name":"Retrievability","level":3,"score":0.25920000672340393},{"id":"https://openalex.org/C2985957978","wikidata":"https://www.wikidata.org/wiki/Q492","display_name":"Human memory","level":3,"score":0.25279998779296875}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.08397","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.08397","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.2606.08397","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.08397","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":"Peace, Justice and strong institutions","score":0.6530138850212097,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2],"answer":[3],"knowledge-intensive":[4],"questions":[5],"using":[6],"both":[7],"parametric":[8],"memory":[9,83],"and":[10,43,96,104,115,127,136],"retrieved":[11,86],"evidence,":[12],"but":[13],"neither":[14],"source":[15,39,53],"is":[16],"uniformly":[17],"reliable.":[18],"Retrieval":[19],"can":[20],"fill":[21],"knowledge":[22],"gaps,":[23],"yet":[24],"distracting":[25],"passages":[26],"may":[27],"override":[28],"correct":[29],"closed-book":[30],"answers.":[31],"We":[32,56],"study":[33],"this":[34],"post-generation":[35],"conflict":[36],"as":[37],"answer-level":[38],"arbitration:":[40],"given":[41],"Direct":[42,103,125],"RAG":[44,105,141],"answers":[45],"from":[46],"the":[47,66,71,85,132],"same":[48],"frozen":[49],"model,":[50],"decide":[51],"which":[52,80,92],"to":[54,138],"trust.":[55],"propose":[57],"TRUSTMARGIN,":[58],"a":[59,77],"training-free,":[60],"plug-and-play":[61],"arbitration":[62],"layer":[63],"that":[64],"scores":[65],"two":[67],"existing":[68],"candidates":[69],"with":[70,88,117],"model's":[72],"own":[73],"likelihoods.":[74],"It":[75],"combines":[76],"parametric-prior":[78],"margin,":[79,91],"tests":[81],"whether":[82],"accepts":[84],"answer,":[87],"an":[89],"evidence-binding":[90],"discounts":[93],"passage-only":[94],"salience":[95],"measures":[97],"question-specific":[98],"support.":[99],"TRUSTMARGIN":[100,121],"selects":[101],"between":[102],"without":[106],"fine-tuning,":[107],"external":[108],"judges,":[109],"or":[110],"additional":[111],"generation.":[112],"Across":[113],"2WIKIMQA":[114],"CWQA":[116],"three":[118],"LLaMA":[119],"scales,":[120],"consistently":[122],"improves":[123],"over":[124],"generation":[126],"BM25-RAG,":[128],"recovers":[129],"part":[130],"of":[131],"Direct/RAG":[133],"oracle":[134],"gap,":[135],"generalizes":[137],"multiple":[139],"training-free":[140],"pipelines.":[142]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-10T00:00:00"}