{"id":"https://openalex.org/W7161683657","doi":"https://doi.org/10.48550/arxiv.2605.17301","title":"ConflictRAG: Detecting and Resolving Knowledge Conflicts in Retrieval Augmented Generation","display_name":"ConflictRAG: Detecting and Resolving Knowledge Conflicts in Retrieval Augmented Generation","publication_year":2026,"publication_date":"2026-05-17","ids":{"openalex":"https://openalex.org/W7161683657","doi":"https://doi.org/10.48550/arxiv.2605.17301"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.17301","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.17301","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.2605.17301","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136498347","display_name":"Chenyu Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Chenyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136491492","display_name":"Yingmin Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yueyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136491492","display_name":"Yingmin Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yingmin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Shu, Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shu, Yang","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":0.5533000230789185,"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":0.5533000230789185,"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/T11147","display_name":"Misinformation and Its Impacts","score":0.2386000007390976,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.03099999949336052,"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/correctness","display_name":"Correctness","score":0.7696999907493591},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6297000050544739},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.6151000261306763},{"id":"https://openalex.org/keywords/credibility","display_name":"Credibility","score":0.6082000136375427},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.5475999712944031},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.45559999346733093},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.3490000069141388}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7897999882698059},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.7696999907493591},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6297000050544739},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6151000261306763},{"id":"https://openalex.org/C2780224610","wikidata":"https://www.wikidata.org/wiki/Q1530061","display_name":"Credibility","level":2,"score":0.6082000136375427},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.5475999712944031},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5074999928474426},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.49399998784065247},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.45559999346733093},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4309000074863434},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.3490000069141388},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.336899995803833},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.3100000023841858},{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.28630000352859497},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C93361087","wikidata":"https://www.wikidata.org/wiki/Q4426698","display_name":"Data consistency","level":2,"score":0.26750001311302185},{"id":"https://openalex.org/C148524875","wikidata":"https://www.wikidata.org/wiki/Q6975395","display_name":"F1 score","level":2,"score":0.2581000030040741},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.25679999589920044}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.17301","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.17301","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.2605.17301","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.17301","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Retrieval-Augmented":[0],"Generation":[1],"(RAG)":[2],"systems":[3],"implicitly":[4],"assume":[5],"mutual":[6],"consistency":[7],"among":[8],"retrieved":[9],"documents":[10],"--":[11],"an":[12,69],"assumption":[13],"that":[14,26],"frequently":[15],"fails":[16],"in":[17],"practice.":[18],"We":[19],"present":[20],"ConflictRAG,":[21],"a":[22,43,49,87],"conflict-aware":[23,117],"RAG":[24,89],"framework":[25,38,71],"detects,":[27],"classifies,":[28],"and":[29,85,109],"resolves":[30],"knowledge":[31],"conflicts":[32],"prior":[33],"to":[34],"answer":[35],"generation.":[36],"The":[37],"introduces":[39],"three":[40,100],"contributions:":[41],"(1)":[42],"two-stage":[44],"conflict":[45],"detection":[46,66],"module":[47],"combining":[48],"lightweight":[50],"embedding-based":[51],"MLP":[52],"classifier":[53],"with":[54,119],"selective":[55],"LLM":[56],"refinement,":[57],"reducing":[58],"API":[59],"costs":[60],"by":[61,80],"62%":[62],"while":[63],"maintaining":[64],"90.8%":[65],"accuracy;":[67],"(2)":[68],"Entropy-TOPSIS":[70],"for":[72,92],"data-driven":[73],"source":[74],"credibility":[75],"assessment,":[76],"improving":[77],"selection":[78],"accuracy":[79],"7.1%":[81],"over":[82,114],"manual":[83],"heuristics;":[84],"(3)":[86],"Conflict-Aware":[88],"Score":[90],"(CARS)":[91],"diagnostic":[93],"evaluation":[94],"of":[95],"conflict-handling":[96],"capabilities.":[97],"Experiments":[98],"on":[99],"benchmarks":[101],"against":[102],"six":[103],"baselines":[104],"demonstrate":[105],"88.7%":[106],"conflict-detection":[107],"F1":[108],"consistent":[110],"5.3--6.1%":[111],"correctness":[112],"gains":[113],"the":[115,120],"strongest":[116],"baseline,":[118],"pipeline":[121],"transferring":[122],"effectively":[123],"across":[124],"backbone":[125],"LLMs.":[126]},"counts_by_year":[],"updated_date":"2026-07-21T08:15:58.654021","created_date":"2026-05-20T00:00:00"}
