{"id":"https://openalex.org/W4415480955","doi":"https://doi.org/10.1145/3704413.3765300","title":"Validating Safety Guarantees of LSTM Models in MR Context","display_name":"Validating Safety Guarantees of LSTM Models in MR Context","publication_year":2025,"publication_date":"2025-10-23","ids":{"openalex":"https://openalex.org/W4415480955","doi":"https://doi.org/10.1145/3704413.3765300"},"language":null,"primary_location":{"id":"doi:10.1145/3704413.3765300","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3704413.3765300","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-sixth International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072113393","display_name":"Kaiming Huang","orcid":"https://orcid.org/0000-0003-3665-2687"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kaiming Huang","raw_affiliation_strings":["The Pennsylvania State University, State College, Pennsylvania, USA"],"raw_orcid":"https://orcid.org/0000-0003-3665-2687","affiliations":[{"raw_affiliation_string":"The Pennsylvania State University, State College, Pennsylvania, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101478680","display_name":"Peng Wu","orcid":"https://orcid.org/0000-0001-7117-3804"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Peng Wu","raw_affiliation_strings":["Northeastern University, Boston, Massachusetts, USA"],"raw_orcid":"https://orcid.org/0000-0001-7117-3804","affiliations":[{"raw_affiliation_string":"Northeastern University, Boston, Massachusetts, USA","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017741575","display_name":"Mahdi Imani","orcid":"https://orcid.org/0000-0001-9570-9909"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mahdi Imani","raw_affiliation_strings":["Northeastern University, Boston, Massachusetts, USA"],"raw_orcid":"https://orcid.org/0000-0001-9570-9909","affiliations":[{"raw_affiliation_string":"Northeastern University, Boston, Massachusetts, USA","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018464968","display_name":"Tian Lan","orcid":"https://orcid.org/0000-0003-3010-8090"},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tian Lan","raw_affiliation_strings":["George Washington University, Washington, D.C., USA"],"raw_orcid":"https://orcid.org/0000-0003-3010-8090","affiliations":[{"raw_affiliation_string":"George Washington University, Washington, D.C., USA","institution_ids":["https://openalex.org/I193531525"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010830558","display_name":"Gang Tan","orcid":"https://orcid.org/0000-0001-6109-6091"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gang Tan","raw_affiliation_strings":["The Pennsylvania State University, State College, Pennsylvania, USA"],"raw_orcid":"https://orcid.org/0000-0001-6109-6091","affiliations":[{"raw_affiliation_string":"The Pennsylvania State University, State College, Pennsylvania, USA","institution_ids":["https://openalex.org/I130769515"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.26390628,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"507","last_page":"508"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9980999827384949,"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":0.9980999827384949,"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/T11242","display_name":"Nuclear Materials and Properties","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6585000157356262},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.636900007724762},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5982999801635742},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.46889999508857727},{"id":"https://openalex.org/keywords/gas-meter-prover","display_name":"Gas meter prover","score":0.4584999978542328},{"id":"https://openalex.org/keywords/system-safety","display_name":"System safety","score":0.36980000138282776},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.3549000024795532}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7468000054359436},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6585000157356262},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.636900007724762},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5982999801635742},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5042999982833862},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.46889999508857727},{"id":"https://openalex.org/C159718280","wikidata":"https://www.wikidata.org/wiki/Q5526353","display_name":"Gas meter prover","level":3,"score":0.4584999978542328},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40880000591278076},{"id":"https://openalex.org/C132835097","wikidata":"https://www.wikidata.org/wiki/Q7663745","display_name":"System safety","level":2,"score":0.36980000138282776},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3549000024795532},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33959999680519104},{"id":"https://openalex.org/C110251889","wikidata":"https://www.wikidata.org/wiki/Q1569697","display_name":"Model checking","level":2,"score":0.2989000082015991},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.2935999929904938},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.2896000146865845},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.2879999876022339},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.27410000562667847},{"id":"https://openalex.org/C111498074","wikidata":"https://www.wikidata.org/wiki/Q173326","display_name":"Formal verification","level":2,"score":0.2694000005722046},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2572000026702881}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3704413.3765300","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3704413.3765300","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-sixth International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":1,"referenced_works":["https://openalex.org/W2900153411"],"related_works":[],"abstract_inverted_index":{"Ensuring":[0],"the":[1],"safety":[2,32,50,85],"of":[3,19,33,62],"neural":[4],"network":[5],"(NN)":[6],"models":[7],"in":[8],"mixed":[9],"reality":[10],"(MR)":[11],"systems":[12],"is":[13],"challenging":[14],"due":[15],"to":[16,30,66],"adversarial":[17],"manipulation":[18],"system":[20],"parameters.":[21],"We":[22],"present":[23],"PolySafe,":[24],"which":[25],"extends":[26],"DeepPoly":[27],"and":[28,47,83],"Prover":[29],"validate":[31],"LSTM-based":[34],"MR":[35,74],"models.":[36],"PolySafe":[37,80],"unrolls":[38],"temporal":[39],"dependencies,":[40],"introduces":[41],"multi-plane":[42],"abstractions":[43],"for":[44,69,87],"tighter":[45],"bounds,":[46],"establishes":[48],"probabilistic":[49],"guarantees.":[51],"It":[52],"further":[53],"includes":[54],"an":[55,73],"adaptive":[56],"search":[57],"that":[58,79],"identifies":[59],"minimal":[60],"sets":[61],"critical":[63],"parameters":[64],"required":[65],"be":[67],"constrained":[68],"defense.":[70],"Evaluation":[71],"on":[72],"engagement":[75],"prediction":[76],"model":[77],"shows":[78],"provides":[81],"rigorous":[82],"actionable":[84],"assurances":[86],"deployment.":[88]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-23T00:00:00"}