155 citations · 156 across the 11 of their papers we have counts for
7 papers · 1 filter
WMAttack: Automated Attack Search for Adversarial Evaluation of World-Model Agents
Zhixiang Guo, Siyuan Liang, Shi Fu +4
Despite the growing use of world models as decision-making agents, their adversarial robustness remains underexplored due to the lack of dedicated automated evaluation methods. A k…
When World Models Dream Wrong: Physical-Conditioned Adversarial Attacks against World Models
Zhixiang Guo, Siyuan Liang, Andras Balogh +4
Generative world models (WMs) are increasingly used to synthesize controllable, sensor-conditioned driving videos, yet their reliance on physical priors exposes novel attack surfac…
Verification of the Implicit World Model in a Generative Model via Adversarial Sequences
András Balogh, Márk Jelasity
Generative sequence models are typically trained on sample sequences from natural or formal languages. It is a crucial question whether -- or to what extent -- sample-based trainin…
Detecting Semantic Backdoors in a Mystery Shopping Scenario
Arpad Berta, Gabor Danner, Istvan Hegedus +1
Detecting semantic backdoors in classification models--where some classes can be activated by certain natural, but out-of-distribution inputs--is an important problem that has rece…
No Soundness in the Real World: On the Challenges of the Verification of Deployed Neural Networks
Attila Szász, Balázs Bánhelyi, Márk Jelasity
The ultimate goal of verification is to guarantee the safety of deployed neural networks. Here, we claim that all the state-of-the-art verifiers we are aware of fail to reach this…
How not to Stitch Representations to Measure Similarity: Task Loss Matching versus Direct Matching
András Balogh, Márk Jelasity
Measuring the similarity of the internal representations of deep neural networks is an important and challenging problem. Model stitching has been proposed as a possible approach,…
Gossip Learning with Linear Models on Fully Distributed Data
Róbert Ormándi, István Hegedüs, Márk Jelasity
Machine learning over fully distributed data poses an important problem in peer-to-peer (P2P) applications. In this model we have one data record at each network node, but without…