{"id":"https://openalex.org/W7166527248","doi":"https://doi.org/10.48550/arxiv.2606.27786","title":"SHIFT: Gate-Modulated Activation Steering for Knowledge Conflict Mitigation in Retrieval-Augmented Generation","display_name":"SHIFT: Gate-Modulated Activation Steering for Knowledge Conflict Mitigation in Retrieval-Augmented Generation","publication_year":2026,"publication_date":"2026-06-26","ids":{"openalex":"https://openalex.org/W7166527248","doi":"https://doi.org/10.48550/arxiv.2606.27786"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.27786","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.27786","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2606.27786","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017008500","display_name":"Ruochang Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Ruochang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139589442","display_name":"Pengcheng Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Pengcheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139572026","display_name":"Zhenghao Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Zhenghao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139578106","display_name":"Yukun Yan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yan, Yukun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139587757","display_name":"Huiyuan Xie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Huiyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139608942","display_name":"Yu Gu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gu, Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139619121","display_name":"Ge Yu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Ge","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139614429","display_name":"Maosong Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Maosong","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":0.42800000309944153,"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":0.42800000309944153,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.19130000472068787,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.13210000097751617,"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/leverage","display_name":"Leverage (statistics)","score":0.6995000243186951},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5828999876976013},{"id":"https://openalex.org/keywords/unintended-consequences","display_name":"Unintended consequences","score":0.5216000080108643},{"id":"https://openalex.org/keywords/compromise","display_name":"Compromise","score":0.4499000012874603},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4203999936580658},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.3986999988555908}],"concepts":[{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6995000243186951},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5828999876976013},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5663999915122986},{"id":"https://openalex.org/C2776889888","wikidata":"https://www.wikidata.org/wiki/Q1135789","display_name":"Unintended consequences","level":2,"score":0.5216000080108643},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.45820000767707825},{"id":"https://openalex.org/C46355384","wikidata":"https://www.wikidata.org/wiki/Q726686","display_name":"Compromise","level":2,"score":0.4499000012874603},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4203999936580658},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.3986999988555908},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.362199991941452},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.31700000166893005},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.2937000095844269},{"id":"https://openalex.org/C195094911","wikidata":"https://www.wikidata.org/wiki/Q14167904","display_name":"Process management","level":1,"score":0.2865999937057495},{"id":"https://openalex.org/C28427503","wikidata":"https://www.wikidata.org/wiki/Q13580300","display_name":"Internal model","level":3,"score":0.2685999870300293},{"id":"https://openalex.org/C2777877512","wikidata":"https://www.wikidata.org/wiki/Q1116097","display_name":"Common ground","level":2,"score":0.2655999958515167},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.2621000111103058}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.27786","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.27786","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.27786","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.27786","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.42006948590278625,"display_name":"Peace, Justice and strong institutions"}],"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],"enhances":[3],"LLMs":[4,51,106,120],"by":[5],"incorporating":[6],"external":[7],"knowledge":[8,20,113],"to":[9,38,46,52,107,149],"support":[10],"response":[11],"generation.":[12,58],"However,":[13,59],"conflicts":[14],"between":[15],"retrieved":[16],"context":[17],"and":[18,40,86,126,153,175],"parametric":[19,154],"have":[21,36],"emerged":[22],"as":[23,75,101],"a":[24,94,122],"critical":[25],"challenge":[26],"in":[27,167],"RAG":[28],"systems.":[29],"To":[30],"mitigate":[31],"such":[32],"conflicts,":[33],"numerous":[34],"studies":[35],"attempted":[37],"identify":[39],"edit":[41],"knowledge-related":[42],"internal":[43,110,147],"neurons,":[44],"aiming":[45],"improve":[47],"the":[48,70,76,135,141,145,162],"ability":[49],"of":[50,73,164],"rely":[53],"on":[54,158],"contextual":[55,152],"evidence":[56],"during":[57],"these":[60],"neuron-level":[61,99],"approaches":[62],"may":[63],"introduce":[64,92],"unintended":[65],"cascading":[66],"effects":[67],"that":[68,97],"compromise":[69],"general":[71],"capabilities":[72],"LLMs,":[74],"modified":[77],"neurons":[78],"are":[79,177],"often":[80],"entangled":[81],"with":[82,121,169],"broader":[83],"model":[84,137],"behaviors":[85],"functionalities.":[87],"In":[88],"this":[89],"paper,":[90],"we":[91],"SHIFT,":[93],"novel":[95],"framework":[96],"reformulates":[98],"modification":[100],"learnable":[102],"gate":[103,124,142],"modulation,":[104],"allowing":[105],"adaptively":[108,150],"regulate":[109],"activations":[111],"for":[112],"conflict":[114],"resolution.":[115],"Technically,":[116],"our":[117,165],"SHIFT":[118,166],"equips":[119],"lightweight":[123],"module":[125,143],"optimizes":[127],"fewer":[128],"than":[129],"0.01%":[130],"trainable":[131],"parameters":[132],"while":[133],"keeping":[134],"backbone":[136],"frozen.":[138],"During":[139],"generation,":[140],"adjusts":[144],"model's":[146],"representations":[148],"leverage":[151],"knowledge.":[155],"Extensive":[156],"experiments":[157],"six":[159],"datasets":[160,174],"validate":[161],"effectiveness":[163],"comparison":[168],"various":[170],"competing":[171],"baselines.":[172],"All":[173],"code":[176],"available":[178],"at":[179],"https://github.com/OpenBMB/SHIFT.":[180]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-30T00:00:00"}
