Grow-Prune-Freeze Networks: Adaptive & Continual Learning Technique for Olfactory Navigation 事件

Grow-Prune-Freeze Networks: Adaptive & Continual Learning Technique for Olfactory Navigation arXiv:2605.25170v1 Announce Type: cross Abstract: Training data for olfaction is scattered through disparate, non-standardized datasets that limit the ability to build representative world models. Olfactory navigation is a highly dynamic and non-stationary task that benefits from real-time continual learning. We introduce an adaptive framework called Grow-Prune-Freeze (GPF) networks that enable an agent