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GAP-Prompt: Gated Adaptive Prompting for Efficient Continual Learning

arXiv · AI, language, vision and robotics · article · Aug 24, 2026 · UTC

Continual learning faces the persistent challenge of catastrophic forgetting, where sequential task updates degrade previously acquired knowledge. While prompt-based methods integrated with pre-trained models offer a compelling solution by freezing the backbone, they often rely on static, task-level prompting strategies that overlook fine-grained intra-task diversity. In this paper, we propose Gated Adaptive Prompting (GAP-Prompt), a novel method that introduces instance-level adaptability to the prompting process. GAP-Prompt consists of three synergistic modules: (1) instance-conditioned gati

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Evidence & attribution

First collected: 2026-09-21T10:22:00.206Z. This is not the publication date.