{"id":"https://openalex.org/W7160898754","doi":"https://doi.org/10.48550/arxiv.2605.08898","title":"LLM-Agnostic Semantic Representation Attack","display_name":"LLM-Agnostic Semantic Representation Attack","publication_year":2026,"publication_date":"2026-05-09","ids":{"openalex":"https://openalex.org/W7160898754","doi":"https://doi.org/10.48550/arxiv.2605.08898"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.08898","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.08898","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.2605.08898","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135962587","display_name":"Jiawei Lian","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lian, Jiawei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135986326","display_name":"Jianhong Pan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pan, Jianhong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135937981","display_name":"Lefan Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Lefan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135948847","display_name":"Yi Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135944979","display_name":"Tairan Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Tairan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067207818","display_name":"Shaohui Mei","orcid":"https://orcid.org/0000-0002-8018-596X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mei, Shaohui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135919214","display_name":"Lap-Pui Chau","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chau, Lap-Pui","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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9368000030517578,"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":0.9368000030517578,"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":0.010400000028312206,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.00559999980032444,"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/interpretability","display_name":"Interpretability","score":0.6902999877929688},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.550599992275238},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.5493000149726868},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.46219998598098755},{"id":"https://openalex.org/keywords/heuristics","display_name":"Heuristics","score":0.4496000111103058},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.445499986410141},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4422999918460846},{"id":"https://openalex.org/keywords/coherence","display_name":"Coherence (philosophical gambling strategy)","score":0.35850000381469727}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7605000138282776},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.6902999877929688},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.550599992275238},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.5493000149726868},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5292999744415283},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.46219998598098755},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.4496000111103058},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.445499986410141},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4422999918460846},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.43459999561309814},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.41269999742507935},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.35850000381469727},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.35760000348091125},{"id":"https://openalex.org/C2778493491","wikidata":"https://www.wikidata.org/wiki/Q7449072","display_name":"Semantic matching","level":3,"score":0.3553999960422516},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3409000039100647},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.3124000132083893},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.3061999976634979},{"id":"https://openalex.org/C511149849","wikidata":"https://www.wikidata.org/wiki/Q7449051","display_name":"Semantic computing","level":3,"score":0.3059000074863434},{"id":"https://openalex.org/C166423231","wikidata":"https://www.wikidata.org/wiki/Q1891170","display_name":"Semantic search","level":3,"score":0.30320000648498535},{"id":"https://openalex.org/C37926939","wikidata":"https://www.wikidata.org/wiki/Q7449061","display_name":"Semantic equivalence","level":4,"score":0.30169999599456787},{"id":"https://openalex.org/C65856478","wikidata":"https://www.wikidata.org/wiki/Q3991682","display_name":"Attack model","level":2,"score":0.28949999809265137},{"id":"https://openalex.org/C2775955345","wikidata":"https://www.wikidata.org/wiki/Q7449071","display_name":"Semantic mapping","level":2,"score":0.2849999964237213},{"id":"https://openalex.org/C204806902","wikidata":"https://www.wikidata.org/wiki/Q2333581","display_name":"Semantic security","level":5,"score":0.27709999680519104},{"id":"https://openalex.org/C9354725","wikidata":"https://www.wikidata.org/wiki/Q286017","display_name":"Operationalization","level":2,"score":0.26930001378059387},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.26440000534057617}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.08898","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.08898","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.2605.08898","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.08898","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":"No poverty","score":0.6884350180625916,"id":"https://metadata.un.org/sdg/1"}],"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],"(LLMs)":[3],"increasingly":[4],"employ":[5],"alignment":[6],"techniques":[7],"to":[8,79],"prevent":[9],"harmful":[10],"outputs.":[11],"Despite":[12],"these":[13,40,58],"safeguards,":[14],"attackers":[15],"can":[16],"circumvent":[17],"them":[18],"by":[19],"crafting":[20],"adversarial":[21,73,131],"prompts.":[22],"Predominant":[23],"token-level":[24],"optimization":[25],"methods":[26],"primarily":[27],"rely":[28],"on":[29],"optimizing":[30],"for":[31],"exact":[32,76],"affirmative":[33],"templates":[34],"(e.g.,":[35],"``\\textit{Sure,":[36],"here":[37],"is...}'').":[38],"However,":[39],"paradigms":[41],"frequently":[42],"encounter":[43],"bottlenecks":[44],"such":[45],"as":[46],"suboptimal":[47],"convergence,":[48],"compromised":[49],"prompt":[50],"naturalness,":[51],"and":[52,90,107,126,159],"poor":[53],"cross-model":[54],"generalization.":[55],"To":[56],"address":[57],"limitations,":[59],"we":[60,84,111],"propose":[61],"Semantic":[62,94,117],"Representation":[63,118],"Attack":[64],"(SRA),":[65],"a":[66,92,146],"novel":[67],"LLM-agnostic":[68],"paradigm":[69],"that":[70,98,142],"fundamentally":[71],"reconceptualizes":[72],"objectives":[74],"from":[75],"textual":[77],"targeting":[78],"malicious":[80],"semantic":[81,87,100,105],"representations.":[82],"Theoretically,":[83],"establish":[85],"the":[86,116,130],"Coherence-Convergence":[88],"Relationship":[89],"derive":[91],"Cross-Model":[93],"Generalization":[95],"bound,":[96],"proving":[97],"maintaining":[99],"coherence":[101,128],"guarantees":[102],"both":[103],"white-box":[104],"convergence":[106],"black-box":[108],"transferability.":[109],"Technically,":[110],"operationalize":[112],"this":[113],"framework":[114,144],"via":[115],"Heuristic":[119],"Search":[120],"(SRHS)":[121],"algorithm,":[122],"which":[123],"preserves":[124],"interpretability":[125],"structural":[127],"of":[129],"prompts":[132],"during":[133],"incremental":[134],"discrete":[135],"token":[136],"chunk":[137],"expansion.":[138],"Extensive":[139],"evaluations":[140],"demonstrate":[141],"our":[143],"achieves":[145],"99.71%":[147],"average":[148],"attack":[149],"success":[150],"rate":[151],"across":[152],"26":[153],"open-source":[154],"LLMs,":[155],"with":[156],"strong":[157],"transferability":[158],"stealth.":[160]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-13T00:00:00"}
