4 citations · 13 across the 14 of their papers we have counts for
4 papers · 1 filter
Pushing the Limits of Distillation-Based Continual Learning via Classifier-Proximal Lightweight Plugins
Zhiming Xu, Baile Xu, Jian Zhao +2
Continual learning requires models to learn continuously while preserving prior knowledge under evolving data streams. Distillation-based methods are appealing for retaining past k…
Physics-inspired Energy Transition Neural Network for Sequence Learning
Zhou Wu, Junyi An, Baile Xu +2
Recently, the superior performance of Transformers has made them a more robust and scalable solution for sequence modeling than traditional recurrent neural networks (RNNs). Howeve…
Interactive Instance Annotation with Siamese Networks
Xiang Xu, Ruotong Li, Mengjun Yi +3
Annotating instance masks is time-consuming and labor-intensive. A promising solution is to predict contours using a deep learning model and then allow users to refine them. Howeve…
Multiple Queries with Multiple Keys: A Precise Prompt Matching Paradigm for Prompt-based Continual Learning
Dunwei Tu, Huiyu Yi, Yuchi Wang +3
Continual learning requires machine learning models to continuously acquire new knowledge in dynamic environments while avoiding the forgetting of previous knowledge. Prompt-based…