{"id":"https://openalex.org/W4403792158","doi":"https://doi.org/10.1145/3664647.3680616","title":"Exploring the Robustness of Decision-Level Through Adversarial Attacks on LLM-Based Embodied Models","display_name":"Exploring the Robustness of Decision-Level Through Adversarial Attacks on LLM-Based Embodied Models","publication_year":2024,"publication_date":"2024-10-26","ids":{"openalex":"https://openalex.org/W4403792158","doi":"https://doi.org/10.1145/3664647.3680616"},"language":"en","primary_location":{"id":"doi:10.1145/3664647.3680616","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3664647.3680616","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"article","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/A5030762613","display_name":"Shuyuan Liu","orcid":"https://orcid.org/0009-0000-3300-396X"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shuyuan Liu","raw_affiliation_strings":["Shanghai Key Laboratory of Multidimensional Information Processing, East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Multidimensional Information Processing, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089745750","display_name":"Jiawei Chen","orcid":"https://orcid.org/0009-0003-1712-8027"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiawei Chen","raw_affiliation_strings":["Shanghai Key Laboratory of Multidimensional Information Processing, East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Multidimensional Information Processing, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048633696","display_name":"Shouwei Ruan","orcid":"https://orcid.org/0009-0007-0481-5855"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shouwei Ruan","raw_affiliation_strings":["Institute of Artificial Intelligence, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Artificial Intelligence, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100341885","display_name":"Hang Su","orcid":"https://orcid.org/0000-0001-8294-6315"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hang Su","raw_affiliation_strings":["Dept. of Comp. Sci. & Tech., Institute for AI, BNRist Center, THBI Lab, Tsinghua-Bosch Joint ML Center, Tsinghua University & Zhongguancun Laboratory, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Dept. of Comp. Sci. & Tech., Institute for AI, BNRist Center, THBI Lab, Tsinghua-Bosch Joint ML Center, Tsinghua University & Zhongguancun Laboratory, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035489942","display_name":"Zhaoxia Yin","orcid":"https://orcid.org/0000-0003-0387-4806"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaoxia Yin","raw_affiliation_strings":["Shanghai Key Laboratory of Multidimensional Information Processing, East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Multidimensional Information Processing, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5030762613"],"corresponding_institution_ids":["https://openalex.org/I66867065"],"apc_list":null,"apc_paid":null,"fwci":3.066,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.9262049,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"8120","last_page":"8128"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9986000061035156,"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":0.9986000061035156,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9905999898910522,"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9889000058174133,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/robustness","display_name":"Robustness (evolution)","score":0.8052117824554443},{"id":"https://openalex.org/keywords/embodied-cognition","display_name":"Embodied cognition","score":0.7567290663719177},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6895612478256226},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.660625159740448},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35179591178894043}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.8052117824554443},{"id":"https://openalex.org/C100609095","wikidata":"https://www.wikidata.org/wiki/Q1335050","display_name":"Embodied cognition","level":2,"score":0.7567290663719177},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6895612478256226},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.660625159740448},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35179591178894043},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3664647.3680616","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3664647.3680616","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7200000286102295,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2101746535","https://openalex.org/W2147277317","https://openalex.org/W3199332348","https://openalex.org/W4212774754","https://openalex.org/W4306179311","https://openalex.org/W4379645258","https://openalex.org/W4388720459","https://openalex.org/W4390872429","https://openalex.org/W4390874280","https://openalex.org/W4392239625","https://openalex.org/W4393160097"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2502115930","https://openalex.org/W2380179524","https://openalex.org/W4283365723","https://openalex.org/W2963001125","https://openalex.org/W2091233881","https://openalex.org/W2352366064","https://openalex.org/W4250820896"],"abstract_inverted_index":{"Embodied":[0,112],"intelligence":[1],"empowers":[2],"agents":[3],"with":[4,19,30,87],"a":[5,15,33,92,138,169,193,216,227],"profound":[6],"sense":[7],"of":[8,67,95,104,140,185,230],"perception,":[9],"enabling":[10],"them":[11],"to":[12,51,75,135,152],"respond":[13],"in":[14,36,61,64,161,189,233],"manner":[16],"closely":[17],"aligned":[18],"real-world":[20],"situations.":[21],"Large":[22],"Language":[23],"Models":[24],"(LLMs)":[25],"delve":[26],"into":[27],"language":[28],"instructions":[29],"depth,":[31],"serving":[32],"crucial":[34],"role":[35],"generating":[37],"plans":[38],"for":[39,99,120,195],"intricate":[40],"tasks.":[41],"Thus,":[42],"LLM-based":[43,105,164,223],"embodied":[44,106,165,224],"models":[45],"further":[46],"enhance":[47],"the":[48,65,102,111,145,149,163,176,180,186,206],"agent's":[49],"capacity":[50],"comprehend":[52],"and":[53,132,182],"process":[54],"information.":[55],"However,":[56],"this":[57,88],"amalgamation":[58],"also":[59],"ushers":[60],"new":[62,170],"challenges":[63],"pursuit":[66],"heightened":[68],"intelligence.":[69],"Specifically,":[70],"attackers":[71],"can":[72],"manipulate":[73],"LLMs":[74],"produce":[76],"irrelevant":[77],"or":[78],"even":[79],"malicious":[80],"outputs":[81],"by":[82],"altering":[83],"their":[84],"prompts.":[85],"Confronted":[86],"challenge,":[89],"we":[90,109,167,191],"observe":[91],"notable":[93],"absence":[94],"multi-modal":[96],"datasets":[97],"essential":[98],"comprehensively":[100],"evaluating":[101],"robustness":[103,121,232],"models.":[107,235],"Consequently,":[108],"construct":[110],"Intelligent":[113],"Robot":[114],"Attack":[115],"Dataset":[116],"(EIRAD),":[117],"tailored":[118],"specifically":[119],"evaluation.":[122],"Additionally,":[123],"two":[124],"attack":[125,142,150,171,218],"strategies":[126],"are":[127],"devised,":[128],"including":[129],"untargeted":[130],"attacks":[131],"targeted":[133],"attacks,":[134,190],"effectively":[136],"simulate":[137],"range":[139],"diverse":[141],"scenarios.":[143],"At":[144],"same":[146],"time,":[147],"during":[148],"process,":[151],"more":[153],"accurately":[154],"ascertain":[155],"whether":[156],"our":[157,213],"method":[158,174,214],"is":[159],"successful":[160],"attacking":[162],"model,":[166],"devise":[168,192],"success":[172,219],"evaluation":[173],"utilizing":[175],"BLIP2":[177],"model.":[178],"Recognizing":[179],"time":[181],"cost-intensive":[183],"nature":[184],"GCG":[187],"algorithm":[188],"scheme":[194],"prompt":[196],"suffix":[197],"initialization":[198],"based":[199],"on":[200],"various":[201],"target":[202],"tasks,":[203],"thus":[204],"expediting":[205],"convergence":[207],"process.":[208],"Experimental":[209],"results":[210],"demonstrate":[211],"that":[212],"exhibits":[215],"superior":[217],"rate":[220],"when":[221],"targeting":[222],"models,":[225],"indicating":[226],"lower":[228],"level":[229],"decision-level":[231],"these":[234]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}