INCPrompt: Task-Aware incremental Prompting for Rehearsal-Free Class-incremental Learning
Abstract
This paper introduces INCPrompt, an innovative continual learning solution that effectively addresses catastrophic forgetting. INCPrompt's key innovation lies in its use of adaptive key-learner and task-aware prompts that capture task-relevant information. This unique combination encapsulates general knowledge across tasks and encodes task-specific knowledge. Our comprehensive evaluation across multiple continual learning benchmarks demonstrates INCPrompt's superiority over existing algorithms, showing its effectiveness in mitigating catastrophic forgetting while maintaining high performance. These results highlight the significant impact of task-aware incremental prompting on continual learning performance.
Cite
@article{arxiv.2401.11667,
title = {INCPrompt: Task-Aware incremental Prompting for Rehearsal-Free Class-incremental Learning},
author = {Zhiyuan Wang and Xiaoyang Qu and Jing Xiao and Bokui Chen and Jianzong Wang},
journal= {arXiv preprint arXiv:2401.11667},
year = {2025}
}
Comments
Accepted by the 49th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2024)