FlyPrompt: Brain-Inspired Random-Expanded Routing with Temporal-Ensemble Experts for General Continual Learning
Published in The Fourteenth International Conference on Learning Representations, 2026, 2026
Recommended citation: Hongwei Yan, Guanglong Sun, Kanglei Zhou, Qian Li, Liyuan Wang, Yi Zhong. "FlyPrompt: Brain-Inspired Random-Expanded Routing with Temporal-Ensemble Experts for General Continual Learning." The Fourteenth International Conference on Learning Representations, 2026 https://arxiv.org/abs/2602.01976
General continual learning (GCL) challenges intelligent systems to learn from single-pass, non-stationary data streams without clear task boundaries. We propose FlyPrompt, a brain-inspired framework with a randomly expanded analytic router for instance-level expert activation and a temporal ensemble of output heads, achieving strong gains on CIFAR-100, ImageNet-R, and CUB-200.
Recommended citation: Hongwei Yan, Guanglong Sun, Kanglei Zhou, Qian Li, Liyuan Wang, Yi Zhong. “FlyPrompt: Brain-Inspired Random-Expanded Routing with Temporal-Ensemble Experts for General Continual Learning.” The Fourteenth International Conference on Learning Representations, 2026