Neuro-symbolic models may improve robustness by combining learned representations with structured composition, but their behavior under adversarial perturbation remains underexplored. We study a hybrid pipeline that fuses ViT features with classical descriptors through Hyperdimensional Computing (HDC). Across CIFAR10 (Subset), COIL100, and ETH80 under FGSM and Genetic Attack, ViT + Classical HDC degrades more gracefully than Pure HDC and ViT + HDC baselines. It achieves higher normalized AURC, lower attack-time decision margins, and larger gains from partial adversarial retraining. These results suggest that classical-neural fusion within HDC is a promising direction for robustness under the evaluated threat models.
Hamza Errahmouni Barkam, Salaar Saraj, Zhen Ye et al.· International Symposium on L...· 0 citations
Autonomous systems operating in the open world require world models that are robust to uncertainty, capable of long-horizon reasoning, and able to generalize to novel scenarios. Vector Symbolic Architectures (VSA), particularly Fourier Holographic Reduced Representations (FHRR), learn robust, structured, and efficient interpretable world models for planning and control. In this work, we introduce a state-of-the-art, out-of-order vector processor to natively accelerate VSA world modeling for autonomous systems with a power envelope of less than 130 mW. We evaluate our hardware-software co-design, demonstrating a 4× reduction in energy per transition and a 2× improvement in roll-out throughput compared to GPU and CPU baselines while maintaining the model's accuracy. These gains are achieved by the vector processor's intrinsic support for element-wise unitary operations and parallel computation, which aligns perfectly with VSA algebra. By unifying a structured, generalizable world model with hardware-efficient vector processing, this work enables scalable and powerful autonomous systems.
Andrew Ding, William Youngwoo Chung, N. Bagherzadeh et al.· Proceedings of the ACM/IEEE...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
