5 papers
Key-Value Pair-Free Continual Learner via Task-Specific Prompt-Prototype
Haihua Luo, Xuming Ran, Zhengji Li +6
Continual learning aims to enable models to acquire new knowledge while retaining previously learned information. Prompt-based methods have shown remarkable performance in this dom…
AVM: Towards Structure-Preserving Neural Response Modeling in the Visual Cortex Across Stimuli and Individuals
Qi Xu, Shuai Gong, Xuming Ran +2
While deep learning models have shown strong performance in simulating neural responses, they often fail to clearly separate stable visual encoding from condition-specific adaptati…
Distillation-Guided Structural Transfer for Continual Learning Beyond Sparse Distributed Memory
Huiyan Xue, Xuming Ran, Yaxin Li +4
Sparse neural systems are gaining traction for efficient continual learning due to their modularity and low interference. Architectures such as Sparse Distributed Memory Multi-Laye…
Efficient ANN-SNN Conversion with Error Compensation Learning
Chang Liu, Jiangrong Shen, Xuming Ran +4
Artificial neural networks (ANNs) have demonstrated outstanding performance in numerous tasks, but deployment in resource-constrained environments remains a challenge due to their…
Brain-inspired continual pre-trained learner via silent synaptic consolidation
Xuming Ran, Juntao Yao, Yusong Wang +2
Pre-trained models have demonstrated impressive generalization capabilities, yet they remain vulnerable to catastrophic forgetting when incrementally trained on new tasks. Existing…