activity
20242026
collaborators

8 papers

cs.NE2026

UniSpike: Accelerating Spiking Neural Networks on Neuromorphic Systems via Eliminating Address Redundancy

Qinghui Xing, Zhuo Chen, Xin Du +6

Many-core neuromorphic systems accelerate Spiking Neural Networks (SNNs), yet their packet-based spike communication can spend substantial traffic and energy repeatedly transmittin…

cs.MA2026

DRAMA: Next-Gen Dynamic Orchestration for Resilient Multi-Agent Ecosystems in Flux

Xinkui Zhao, Yifan Zhang, Sai Liu +6

Multi-agent systems (MAS) have demonstrated significant effectiveness in addressing complex problems through coordinated collaboration among heterogeneous agents. However, real-wor…

cs.NE2026

Frequency Matching in Spiking Neural Networks for mmWave Sensing

Di Yu, Zhenyu Liao, Changze Lv +7

Millimeter-wave (mmWave) sensing enables privacy-preserving, always-on edge perception, but its measurements are often sparse, temporally irregular, and corrupted by high-frequency…

cs.LG2026

SAFA-SNN: Sparsity-Aware On-Device Few-Shot Class-Incremental Learning with Fast-Adaptive Structure of Spiking Neural Network

Huijing Zhang, Muyang Cao, Linshan Jiang +4

Continuous learning of novel classes is crucial for edge devices to preserve data privacy and maintain reliable performance in dynamic environments. However, the scenario becomes p…

cs.DC2025

Edge Intelligence with Spiking Neural Networks

Shuiguang Deng, Di Yu, Changze Lv +10

The convergence of artificial intelligence and edge computing has spurred growing interest in enabling intelligent services directly on resource-constrained devices. While traditio…

cs.LG2025

Exploiting Label Skewness for Spiking Neural Networks in Federated Learning

Di Yu, Xin Du, Linshan Jiang +2

The energy efficiency of deep spiking neural networks (SNNs) aligns with the constraints of resource-limited edge devices, positioning SNNs as a promising foundation for intelligen…