{"id":"https://openalex.org/W7164881643","doi":"https://doi.org/10.48550/arxiv.2606.16461","title":"Privacy from Symmetry: Orthogonally Equivariant Transformers for LLM Inference","display_name":"Privacy from Symmetry: Orthogonally Equivariant Transformers for LLM Inference","publication_year":2026,"publication_date":"2026-06-15","ids":{"openalex":"https://openalex.org/W7164881643","doi":"https://doi.org/10.48550/arxiv.2606.16461"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.16461","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.16461","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.2606.16461","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136036839","display_name":"Alexander Yukhimchuk","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yukhimchuk, Alexander","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138715774","display_name":"Andrey Shulga","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shulga, Andrey","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016868056","display_name":"Mladen Kolar","orcid":"https://orcid.org/0000-0001-7353-3404"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kolar, Mladen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138691307","display_name":"Martin Tak\u00e1\u010d","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tak\u00e1\u010d, Martin","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/T10237","display_name":"Cryptography and Data Security","score":0.4503999948501587,"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/T10237","display_name":"Cryptography and Data Security","score":0.4503999948501587,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.3587000072002411,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.06800000369548798,"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/inference","display_name":"Inference","score":0.7027999758720398},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.6140999794006348},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5354999899864197},{"id":"https://openalex.org/keywords/obfuscation","display_name":"Obfuscation","score":0.4081000089645386},{"id":"https://openalex.org/keywords/cryptography","display_name":"Cryptography","score":0.4023999869823456},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.3944999873638153},{"id":"https://openalex.org/keywords/discrete-cosine-transform","display_name":"Discrete cosine transform","score":0.38040000200271606},{"id":"https://openalex.org/keywords/perplexity","display_name":"Perplexity","score":0.3476000130176544}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7027999758720398},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6230000257492065},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.6140999794006348},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5354999899864197},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4814000129699707},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46230000257492065},{"id":"https://openalex.org/C40305131","wikidata":"https://www.wikidata.org/wiki/Q2616305","display_name":"Obfuscation","level":2,"score":0.4081000089645386},{"id":"https://openalex.org/C178489894","wikidata":"https://www.wikidata.org/wiki/Q8789","display_name":"Cryptography","level":2,"score":0.4023999869823456},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.3944999873638153},{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.38040000200271606},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3596999943256378},{"id":"https://openalex.org/C100279451","wikidata":"https://www.wikidata.org/wiki/Q372193","display_name":"Perplexity","level":3,"score":0.3476000130176544},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.34709998965263367},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.305400013923645},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2962999939918518},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.2851000130176544},{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.2849000096321106},{"id":"https://openalex.org/C178009071","wikidata":"https://www.wikidata.org/wiki/Q93344","display_name":"Trigonometric functions","level":2,"score":0.2831999957561493},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.2676999866962433},{"id":"https://openalex.org/C200331156","wikidata":"https://www.wikidata.org/wiki/Q506041","display_name":"Jacobian matrix and determinant","level":2,"score":0.26660001277923584},{"id":"https://openalex.org/C92423082","wikidata":"https://www.wikidata.org/wiki/Q132146","display_name":"Zernike polynomials","level":3,"score":0.2603999972343445},{"id":"https://openalex.org/C3746660","wikidata":"https://www.wikidata.org/wiki/Q1068763","display_name":"Rule of inference","level":2,"score":0.2597000002861023},{"id":"https://openalex.org/C171036898","wikidata":"https://www.wikidata.org/wiki/Q256355","display_name":"Equivariant map","level":2,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.16461","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.16461","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.2606.16461","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.16461","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":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.7628288269042969}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Running":[0],"large":[1],"language":[2],"models":[3,127],"locally":[4],"is":[5,80],"often":[6],"impractical,":[7],"pushing":[8],"inference":[9,17,69,178],"on":[10,24,121,129],"sensitive":[11],"text":[12],"to":[13,148],"third-party":[14],"providers.":[15],"Split":[16],"partially":[18],"mitigates":[19],"this":[20],"by":[21,59,155],"keeping":[22],"tokens":[23],"the":[25,43,55,102,105,111,167],"client":[26,56],"and":[27,114,123,140],"sending":[28],"only":[29,156],"hidden":[30,118],"representations,":[31],"but":[32],"these":[33],"representations":[34],"can":[35,170],"still":[36],"be":[37],"recovered":[38],"via":[39,83],"nearest-neighbor":[40,138],"search":[41],"against":[42],"public":[44],"embedding":[45],"table.":[46],"We":[47],"propose":[48],"an":[49],"orthogonal":[50,62,93,133],"obfuscation":[51,134],"procedure":[52],"in":[53,110],"which":[54],"multiplies":[57],"embeddings":[58],"a":[60,76,84,100,172],"secret":[61],"matrix":[63],"before":[64],"transmission.":[65],"To":[66],"enable":[67],"correct":[68],"under":[70],"arbitrary":[71],"rotations,":[72],"we":[73],"introduce":[74],"ConjFormer,":[75],"transformer":[77],"variant":[78],"that":[79,132,163],"exactly":[81],"$\\mathrm{O}(d)$-equivariant":[82],"lightweight":[85],"normalization":[86],"change":[87],"(scalar":[88],"RMSNorm)":[89],"together":[90],"with":[91],"blockwise":[92],"conjugation":[94],"of":[95],"all":[96],"linear":[97],"weights.":[98],"As":[99],"result,":[101],"server":[103],"performs":[104],"full":[106],"forward":[107],"pass":[108],"entirely":[109],"rotated":[112],"basis":[113],"never":[115],"observes":[116],"unrotated":[117],"states.":[119],"Experiments":[120],"GPT-2":[122],"Llama":[124],"3.2":[125],"1B":[126],"fine-tuned":[128],"PubMed":[130],"show":[131],"eliminates":[135],"direct":[136],"cosine":[137],"inversion":[139],"reduces":[141],"token":[142],"recovery":[143],"from":[144],"over":[145],"35%":[146],"top-10":[147],"at":[149,166],"most":[150],"1.3%,":[151],"while":[152],"increasing":[153],"perplexity":[154],"0.4%":[157],"after":[158],"fine-tuning.":[159],"These":[160],"results":[161],"indicate":[162],"enforcing":[164],"symmetry":[165],"architectural":[168],"level":[169],"provide":[171],"practical":[173],"defense":[174],"for":[175],"privacy-preserving":[176],"LLM":[177],"without":[179],"noise":[180],"injection":[181],"or":[182],"heavy":[183],"cryptographic":[184],"machinery.":[185]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-17T00:00:00"}
