Apr 10, 2022 · We present a simple yet effective framework, DualPrompt, which learns a tiny set of parameters, called prompts, to properly instruct a pre-trained model to ...

In this paper, we present DualPrompt, a rehearsal-free continual learning approach to explicitly learn two sets of disjoint prompt spaces, G(eneral)-Prompt.

Nov 1, 2022 · We propose DualPrompt, a simple and effective rehearsal-free CL method, comprised of G-Prompt and E-Prompt for learning task-invariant and task- ...

DualPrompt presents a novel approach to attach complementary prompts to the pre-trained backbone, and then formulates the objective as learning task-invariant ...

L2P is a novel continual learning technique which learns to dynamically prompt a pre-trained model to learn tasks sequentially under different task transitions.

Wang, Zifeng, et al. "DualPrompt: Complementary Prompting for Rehearsal-free Continual Learning." ECCV. 2022. The official Jax implementation is here.

DualPrompt presents a novel approach to attach complementary prompts to the pre-trained backbone, and then formulates the objective as learning task-invariant ...

DualPrompt presents a novel approach to attach complementary prompts to the pre-trained backbone, and then formulates the objective as learning task-invariant ...

Our CPrompt consists of two complementary com- ponents: classifier consistency learning (CCL) and prompt consistency learning (PCL). CCL addresses the ...

Apr 12, 2022 · DualPrompt: Complementary Prompting for Rehearsal-free Continual Learning abs: https://arxiv.org/abs/2204.04799. Image. 1:51 AM · Apr 12, 2022.