{"id":"https://openalex.org/W7140455302","doi":"https://doi.org/10.48550/arxiv.2603.23822","title":"How Vulnerable Are Edge LLMs?","display_name":"How Vulnerable Are Edge LLMs?","publication_year":2026,"publication_date":"2026-03-25","ids":{"openalex":"https://openalex.org/W7140455302","doi":"https://doi.org/10.48550/arxiv.2603.23822"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.23822","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.23822","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.23822","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063156681","display_name":"Ao Ding","orcid":"https://orcid.org/0000-0001-5649-0879"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ding, Ao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081924890","display_name":"Hongzong Li","orcid":"https://orcid.org/0000-0002-5774-7557"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Hongzong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104035702","display_name":"Zi Liang","orcid":"https://orcid.org/0009-0003-1418-9537"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liang, Zi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130668752","display_name":"Zhanpeng Shi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shi, Zhanpeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130674114","display_name":"Shuxin Zhuang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhuang, Shuxin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130657704","display_name":"Shiqin Tang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tang, Shiqin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130668661","display_name":"Rong Feng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Feng, Rong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5130679214","display_name":"Ping Lu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Ping","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":8,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.2264000028371811,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.2264000028371811,"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/T14347","display_name":"Big Data and Digital Economy","score":0.07779999822378159,"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/T10028","display_name":"Topic Modeling","score":0.07580000162124634,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.7896999716758728},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.6208999752998352},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5023000240325928},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.3580999970436096},{"id":"https://openalex.org/keywords/vector-quantization","display_name":"Vector quantization","score":0.32330000400543213},{"id":"https://openalex.org/keywords/security-community","display_name":"Security community","score":0.28529998660087585}],"concepts":[{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.7896999716758728},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.680400013923645},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.6208999752998352},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5023000240325928},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3959999978542328},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3686000108718872},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.3580999970436096},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3497999906539917},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.34060001373291016},{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.32330000400543213},{"id":"https://openalex.org/C2778062554","wikidata":"https://www.wikidata.org/wiki/Q3404031","display_name":"Security community","level":2,"score":0.28529998660087585},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.2736000120639801},{"id":"https://openalex.org/C140547941","wikidata":"https://www.wikidata.org/wiki/Q7797194","display_name":"Threat model","level":2,"score":0.2727000117301941},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.27160000801086426},{"id":"https://openalex.org/C3018263672","wikidata":"https://www.wikidata.org/wiki/Q1296251","display_name":"Efficient algorithm","level":2,"score":0.2531999945640564},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2529999911785126}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.23822","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.23822","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.23822","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.23822","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":"article"},"sustainable_development_goals":[],"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":[2,85],"(LLMs)":[3],"are":[4],"increasingly":[5],"deployed":[6],"on":[7,82],"edge":[8],"devices":[9],"under":[10,31,103],"strict":[11],"computation":[12],"and":[13,35,97],"quantization":[14,39,110],"constraints,":[15],"yet":[16],"their":[17],"security":[18,124],"implications":[19],"remain":[20],"unclear.":[21],"We":[22],"study":[23],"query-based":[24,118],"knowledge":[25],"extraction":[26,102],"from":[27],"quantized":[28,83],"edge-deployed":[29,127],"LLMs":[30],"realistic":[32],"query":[33,71],"budgets":[34],"show":[36],"that,":[37],"although":[38],"introduces":[40],"noise,":[41],"it":[42],"does":[43,112],"not":[44,113],"remove":[45],"the":[46],"underlying":[47],"semantic":[48,76],"knowledge,":[49],"allowing":[50],"substantial":[51],"behavioral":[52],"recovery":[53],"through":[54],"carefully":[55],"designed":[56],"queries.":[57],"To":[58],"systematically":[59],"analyze":[60],"this":[61],"risk,":[62],"we":[63],"propose":[64],"\\textbf{CLIQ}":[65],"(\\textbf{Cl}ustered":[66],"\\textbf{I}nstruction":[67],"\\textbf{Q}uerying),":[68],"a":[69,121],"structured":[70],"construction":[72],"framework":[73],"that":[74,88,109],"improves":[75],"coverage":[77],"while":[78],"reducing":[79],"redundancy.":[80],"Experiments":[81],"Qwen":[84],"(INT8/INT4)":[86],"demonstrate":[87],"CLIQ":[89],"consistently":[90],"outperforms":[91],"original":[92],"queries":[93],"across":[94],"BERTScore,":[95],"BLEU,":[96],"ROUGE,":[98],"enabling":[99],"more":[100],"efficient":[101],"limited":[104],"budgets.":[105],"These":[106],"results":[107],"indicate":[108],"alone":[111],"provide":[114],"effective":[115],"protection":[116],"against":[117],"extraction,":[119],"highlighting":[120],"previously":[122],"underexplored":[123],"risk":[125],"in":[126],"LLMs.":[128]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-27T00:00:00"}