3 papers
cs.AR2026
KANtize: Exploring Low-bit Quantization of Kolmogorov-Arnold Networks for Efficient Inference
Sohaib Errabii, Olivier Sentieys, Marcello Traiola
Kolmogorov-Arnold Networks (KANs) have gained attention for their potential to outperform Multi-Layer Perceptrons (MLPs) in terms of parameter efficiency and interpretability. Unli…
cs.AR2025
KAN-SAs: Efficient Acceleration of Kolmogorov-Arnold Networks on Systolic Arrays
Sohaib Errabii, Olivier Sentieys, Marcello Traiola
Kolmogorov-Arnold Networks (KANs) have garnered significant attention for their promise of improved parameter efficiency and explainability compared to traditional Deep Neural Netw…
cs.CR2025
Side-Channel Extraction of Dataflow AI Accelerator Hardware Parameters
Guillaume Lomet, Ruben Salvador, Brice Colombier +3
Dataflow neural network accelerators efficiently process AI tasks on FPGAs, with deployment simplified by ready-to-use frameworks and pre-trained models. However, this convenience…