{"id":"https://openalex.org/W7163449358","doi":"https://doi.org/10.48550/arxiv.2606.03179","title":"HyperPatch: Sequential Knowledge Editing Under n-ary Structural Drift","display_name":"HyperPatch: Sequential Knowledge Editing Under n-ary Structural Drift","publication_year":2026,"publication_date":"2026-06-02","ids":{"openalex":"https://openalex.org/W7163449358","doi":"https://doi.org/10.48550/arxiv.2606.03179"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.03179","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.03179","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2606.03179","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5126273060","display_name":"Yu-Kai Chan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chan, Yu-Kai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076507451","display_name":"Wen-Sheng Lien","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lien, Wen-Sheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054615641","display_name":"Dong-Ting Yao","orcid":"https://orcid.org/0009-0005-8203-6609"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yao, Dong-Ting","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088821614","display_name":"Bo-Kai Ruan","orcid":"https://orcid.org/0000-0002-9847-3628"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ruan, Bo-Kai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137799985","display_name":"Kwan-Yeung Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Kwan-Yeung","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040050806","display_name":"Hong-Han Shuai","orcid":"https://orcid.org/0000-0003-2216-077X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shuai, Hong-Han","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137720709","display_name":"Meng-Fen Chiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chiang, Meng-Fen","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/T11273","display_name":"Advanced Graph Neural Networks","score":0.8129000067710876,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.8129000067710876,"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/T10028","display_name":"Topic Modeling","score":0.07199999690055847,"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":0.040300000458955765,"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/embedding","display_name":"Embedding","score":0.5730999708175659},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.5313000082969666},{"id":"https://openalex.org/keywords/binary-relation","display_name":"Binary relation","score":0.46790000796318054},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.45980000495910645},{"id":"https://openalex.org/keywords/hypergraph","display_name":"Hypergraph","score":0.4512999951839447},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.4169999957084656},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.415800005197525},{"id":"https://openalex.org/keywords/topology","display_name":"Topology (electrical circuits)","score":0.39419999718666077},{"id":"https://openalex.org/keywords/observability","display_name":"Observability","score":0.3864000141620636}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6309999823570251},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5730999708175659},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5313000082969666},{"id":"https://openalex.org/C65180967","wikidata":"https://www.wikidata.org/wiki/Q130901","display_name":"Binary relation","level":2,"score":0.46790000796318054},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.45980000495910645},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4528000056743622},{"id":"https://openalex.org/C2781221856","wikidata":"https://www.wikidata.org/wiki/Q840247","display_name":"Hypergraph","level":2,"score":0.4512999951839447},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.42989999055862427},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.4169999957084656},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.415800005197525},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41040000319480896},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.39419999718666077},{"id":"https://openalex.org/C36299963","wikidata":"https://www.wikidata.org/wiki/Q1369844","display_name":"Observability","level":2,"score":0.3864000141620636},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.33329999446868896},{"id":"https://openalex.org/C9376300","wikidata":"https://www.wikidata.org/wiki/Q168817","display_name":"Algebraic number","level":2,"score":0.33309999108314514},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.3156000077724457},{"id":"https://openalex.org/C40506919","wikidata":"https://www.wikidata.org/wiki/Q7452469","display_name":"Sequence learning","level":2,"score":0.2858999967575073},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.2840999960899353},{"id":"https://openalex.org/C2776960227","wikidata":"https://www.wikidata.org/wiki/Q2586354","display_name":"Knowledge transfer","level":2,"score":0.28119999170303345},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.2809999883174896},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.2793999910354614},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.27489998936653137},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2687000036239624},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.2578999996185303},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.2533999979496002},{"id":"https://openalex.org/C115908005","wikidata":"https://www.wikidata.org/wiki/Q2668364","display_name":"Combinatorial explosion","level":2,"score":0.2515999972820282}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.03179","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.03179","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2606.03179","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.03179","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"Language":[1],"Models":[2],"(LLMs)":[3],"rely":[4],"on":[5,104],"Knowledge":[6,51],"Editing":[7],"(KE)":[8],"to":[9,27,110,135,199,202],"maintain":[10],"temporal":[11],"validity,":[12],"yet":[13],"real-world":[14],"knowledge":[15],"is":[16],"inherently":[17],"n-ary.":[18],"We":[19],"demonstrate":[20,181],"that":[21,74,122],"in":[22,166],"non-stationary":[23],"environments,":[24],"sequential":[25,76],"updates":[26],"complex":[28],"relations":[29],"induce":[30],"N-ary":[31],"Structural":[32,93],"Drift,":[33],"a":[34,54,71,79,97,105,119],"phenomenon":[35],"where":[36],"the":[37,58,157,175,190],"binary":[38],"reification":[39],"of":[40,57,170,197],"n-ary":[41,186],"events":[42],"into":[43],"triples":[44],"fractures":[45],"relational":[46],"atomicity.":[47],"This":[48],"precipitates":[49],"Structure-Conditioned":[50,143],"Transfer":[52],"Failure,":[53],"systematic":[55],"mis-grounding":[56],"retriever":[59],"frequently":[60],"misdiagnosed":[61],"as":[62,78],"parametric":[63],"hallucination.":[64],"To":[65],"tackle":[66],"this,":[67],"we":[68],"propose":[69],"HyperPatch,":[70],"parameter-preserving":[72],"framework":[73],"reformulates":[75],"KE":[77],"stability":[80],"problem":[81],"over":[82,174],"hypergraph":[83],"manifolds.":[84,155],"HyperPatch":[85,162],"preserves":[86],"event":[87],"integrity":[88],"through":[89],"three":[90],"phases:":[91],"(i)":[92],"Prior":[94],"Initialization,":[95],"establishing":[96],"topology-aware":[98],"embedding":[99],"space":[100],"via":[101],"contrastive":[102],"learning":[103],"Hypergraph":[106],"Neural":[107],"Network":[108],"(HGNN)":[109],"capture":[111],"high-order":[112],"correlations;":[113],"(ii)":[114],"Sequential":[115],"Topology":[116],"Editing,":[117],"utilizing":[118],"dual-stage":[120],"mechanism":[121],"employs":[123],"SimHash-based":[124],"Topological":[125,132],"Alignment":[126],"for":[127],"rapid":[128],"conflict":[129],"resolution":[130],"and":[131,141,153,159,172],"LoRA":[133],"Adaptation":[134],"track":[136],"drift":[137],"without":[138],"backbone":[139],"retraining;":[140],"(iii)":[142],"Reasoning,":[144],"which":[145],"integrates":[146],"globally":[147],"consistent":[148],"evidence":[149],"from":[150],"fused":[151],"linguistic":[152],"structural":[154,203],"On":[156],"MQuAKE-CF":[158],"MQuAKE-T":[160],"benchmarks,":[161],"achieves":[163],"relative":[164],"gains":[165],"Hop-wise":[167],"Accuracy":[168],"(H-Acc)":[169],"96.24%":[171],"21.06%":[173],"strongest":[176],"baseline,":[177],"respectively.":[178],"Further":[179],"ablations":[180],"superior":[182],"reliability":[183],"under":[184],"continuous":[185],"update":[187],"streams,":[188],"whereas":[189],"standard":[191],"KG-based":[192],"variant":[193],"suffers":[194],"H-Acc":[195],"collapses":[196],"up":[198],"88.3%":[200],"due":[201],"misalignment.":[204]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-04T00:00:00"}