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cvpr 2026 workshop home dates speakers organizers call challenge sponsors committee the 6th workshop of adversarial machine learning on computer vision safety of vision language agents the ieee cvf conference on computer vision and pattern recognition cvpr 2026 wed june 3 sun june 7 2026 denver co usa advml workshop june 4 room 708 overview over the past few years foundation models have fundamentally transformed the landscape of computer vision enabling large scale visual understanding generation and multimodal reasoning building upon these advances vision language agents embodied or digital systems powered by multimodal foundation models are rapidly emerging as a central paradigm for intelligent perception decision making and human ai interaction these agents integrate perception vision cognition language and reasoning and action planning and control within a unified framework thereby bridging the gap between visual recognition and autonomous behavior however the growing autonomy and complexity of such agents have also amplified their susceptibility to adversarial and safety critical risks beyond traditional pixel level perturbations new attack surfaces arise from adversarial prompts instruction injections and jailbreak manipulations which can disrupt reasoning chains mislead perception or induce harmful actions these vulnerabilities highlight fundamental challenges in building safe robust and trustworthy vision language agents for real world applications from autonomous driving and embodied robotics to interactive medical or industrial systems addressing these challenges demands a deeper understanding of multimodal robustness causal reasoning and secure perception action coupling in complex environments the 6th workshop on adversarial machine learning in computer vision 6th advml cv safety of vision language agents aims to bring together researchers and practitioners from computer vision multimodal learning and ai safety communities to advance the frontier of robust and trustworthy vision language agents continuing the success of the previous five cvpr advml cv workshops which have attracted thousands of submissions participants and widespread attention the 2026 edition will feature keynote talks by leading experts contributed papers and an international challenge on adversarial robustness for multimodal agents through this workshop we aim to foster cross disciplinary collaboration inspire new research directions and catalyze the development of secure reliable and ethically aligned vision language agents that can safely operate in dynamic and human centered environments new poster presentation location board 248 255 in exhibit hall a 15 00 18 00 new the phase 2 dataset of challenge is now available new phase 2 of the challenge has begun important the submission deadline has been extended to mar 7 2026 23 59 utc 0 important dates timeline workshop schedule google callendar event start time end time opening remarks 9 00 9 15 invited talk 1 prof bo li 9 15 9 45 invited talk 2 prof chaowei xiao 9 45 10 15 contributed talk 1 10 15 10 30 coffee break 10 30 10 45 invited talk 3 prof aditi raghunathan 10 45 11 15 invited talk 4 prof florian tramèr 11 15 11 45 contributed talk 2 11 45 12 00 lunch 12 00 13 30 invited talk 5 dr nouha dziri 13 30 14 00 invited talk 6 dr jingwei yi 14 00 14 30 invited talk 7 prof ziwei liu 14 30 15 00 contributed talk 3 15 00 15 10 challenge session 15 10 15 40 poster session 15 00 17 00 proposed speakers ziwei liu nanyang technological university chaowei xiao johns hopkins university nouha dziri cohere labs florian tramèr eth zürich jingwei yi baai aditi raghunathan carnegie mellon university bo li university of illinois at urbana champaign aishan liu beihang university organizers jin hu zhongguancun laboratory tianyuan zhang beihang university aishan liu beihang university jiakai wang zhongguancun laboratory ruikai li beihang university julia karbing university of oxford yinpeng dong tsinghua university zhenfei yin university of oxford shao jing shanghai ai laboratory xia hu shanghai ai laboratory jingyi xu beihang university juntao dai baai xinyun chen meta xianglong liu beihang university vishal m patel johns hopkins university dawn song uc berkeley alan yuille johns hopkins university philip h s torr oxford university dacheng tao nanyang technological university call for papers vision language agents embodied or digital systems powered by multimodal foundation models are rapidly emerging as a central paradigm for intelligent perception decision making and human ai interaction these agents integrate perception vision cognition language and reasoning and action planning and control within a unified framework thereby bridging the gap between visual recognition and autonomous behavior however beyond traditional pixel level perturbations new attack surfaces arise from adversarial prompts instruction injections and jailbreak manipulations which can disrupt reasoning chains mislead perception or induce harmful actions to foster the development of safe robust and trustworthy vision language agents for real world applications we invite submissions on both theoretical and practical aspects of adversarial machine learning with a specific focus on the safety of vision language agents we welcome research contributions related to the following but not limited to topics attack and defense on vision language agents datasets and benchmarks that could evaluate vision language agents adversarial jailbreak attacks on vision language agents improving the robustness of agents or deep learning systems interpreting and understanding model robustness especially agentic ai adversarial attacks for social good alignment of vision language agents format submissions papers pdf format must use the cvpr 2026 author kit for latex word zip file and be anonymized and follow cvpr 2026 author instructions the workshop considers two types of submissions 1 long paper papers are limited to 8 pages excluding references 2 extended abstract papers are limited to 4 pages including references accepted papers have the option to be included in the cvf and ieee xplore proceedings submission site https openreview net group id thecvf com cvpr 2026 workshop advml submission due both paper and supplementary material march 7 2026 11 59 pm utc 0 accepted papers title paper supplementary authors arms adaptive red teaming agent against multimodal models with plug and play attacks distinguished paper contribute talk 1 pdf zhaorun chen xun liu mintong kang jiawei zhang minzhou pan shuang yang bo li mirrorcheck efficient adversarial defense for vision language models distinguished paper contribute talk 2 pdf supplementary samar fares toluwani aremu klea ziu nikita durasov martin takáč pascal fua karthik nandakumar ivan laptev skillject automating stealthy skill based prompt injection for coding agents with trace driven closed loop refinement distinguished paper contribute talk 3 pdf supplementary xiaojun jia jie liao simeng qin jindong gu wenqi ren xiaochun cao yang liu philip torr safegrpo self rewarded multimodal safety alignment via rule governed policy optimization pdf supplementary xuankun rong wenke huang tingfeng wang daiguo zhou bo du mang ye robustness of vision foundation models to common perturbations pdf supplementary hongbin liu zhengyuan jiang cheng hong neil zhenqiang gong sasa sequence aware shadow attacks via attention alignment for traffic sign recognition pdf amir salarpour pedram mohajeransari david fernandez mert d pesé interpretable adversarial prompt tuning via semantic concepts pdf pedram mohajeransari zongxi liu yi zhu amir salarpour mert d pesé auditing traffic sign robustness via ddim inversion do diffusion latents preserve shadow attacks pdf ashton b mcentarffer amir salarpour pedram mohajeransari mert d pesé evaluating vulnerabilities in vision language models impact of behavior induced interference pdf yuwei chen shiyong chu atac augmentation based test time adversarial correction for clip pdf supplementary linxiang su andrás balogh challenge with the rapid development of multimodal foundation models and vision language agents vlas their safety and security risks have become important concerns for both academia and industry in safety critical domains such as autonomous driving vlas are expected to understand complex driving scenes and generate reliable responses for driving related reasoning and decision making ensuring their robustness and safety is therefore essential to systematically explore the potential threats inherent in these systems and strengthen their practical safety we are initiating this security challenge focused on adversarial multimodal attacks against vlas this initiative seeks to engage global developers researchers and security experts in designing and submitting adversarial inputs that reveal vulnerabilities in vlas particularly in autonomous driving scenarios based on drivelm https github com opendrivelab drivelm participants are encouraged to design adversarial attacks that could induce unsafe harmful or misleading outputs including but not limited to incorrect traffic understanding unsafe driving related reasoning and misleading responses to driving questions through this collaborative effort we aim to promote the development of comprehensive vulnerability evaluation frameworks advance defensive paradigm innovation and shape more secure development standards for next generation vlas by proactively identifying and addressing these risks this challenge contributes to building safer more trustworthy ai systems capable of meeting the ethical and functional demands of their increasingly critical roles in society challenge site https challenge aisafety org cn competitiondetail id 24 timeline delayed challenge timeline mar 19 2026 competition starts mar 24 2026 phase 1 data release mar 27 2026 phase 1 starts april 20 2026 phase 1 ends april 27 2026 phase 2 data release april 27 2026 phase 2 starts may 16 2026 phase 2 ends may 30 2026 results will be released and participants will be selected to present june 2026 awards and presentation award list rank team score mr cas 76 63 team_tong 75 93 wzbc_abeliuxl 71 19 4 jnu_advml 69 26 5 team_hymeng 60 63 6 diamond_ai 54 58 7 team_yzh_0 0 54 23 8 suibianwanwan 52 47 challenge chair tianyuan zhang beihang university jin hu zhongguancun laboratory zonglei jing beihang university jiangfan liu beihang university hainan li data space research institute zhilei zhu data space research institute xianglong kong data space research institute zonghao ying beihang university yisong xiao beihang university lei chen tsinghua university haotong qin eth zürich jiakai wang zhongguancun laboratory xianglong liu beihang university sponsors program committee akshayvarun subramanya umbc alexander robey upenn ali shahin shamsabadi qmul angtian wang jhu aniruddha saha umbc anshuman suri uva bernhard egger mit chenglin yang jhu chirag agarwal harvard gaurang sriramanan iisc jiachen sun msu jieru mei jhu jun guo buaa ju he jhu kibok lee msu lifeng huang sysu maura pintor university of cagliari muhammad awais qmul and betterdata muzammal naseer anu nataniel ruiz bu qihang yu jhu qing jin neu rajkumar theagarajan ucr ruihao gong buaa shiyu tang buaa shunchang liu ethz sravanti addepalli iisc tianlin li ntu wenxiao wang thu hang yu buaa won park msu xiangning chen ucla xiaohui zeng u of t xingjun ma dku xinwei zhao du yulong cao msu yutong bai jhu zihao xiao jhu zixin yin buaa siyang wu zgclab haojie hao buaa zhengquan sun buaa for any further questions you can contact jin hu and tianyuan zhang