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Found 7 papers, 4 papers with code
Parameter-Level Soft-Masking for Continual Learning
Although several techniques have achieved learning with no CF, they attain it by letting each task monopolize a sub-network in a shared network, which seriously limits knowledge transfer (KT) and causes over-consumption of the network capacity, i. e., as more tasks are learned, the performance deteriorates.
Open-World Continual Learning: Unifying Novelty Detection and Continual Learning
The key theoretical result is that regardless of whether WP and OOD detection (or TP) are defined explicitly or implicitly by a CIL algorithm, good WP and good OOD detection are necessary and sufficient conditions for good CIL, which unifies novelty or OOD detection and continual learning (CIL, in particular).
Continual Pre-training of Language Models
A novel proxy is also proposed to preserve the general knowledge in the original LM.
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Continual Pretraining
on ACL-ARC
A Theoretical Study on Solving Continual Learning
Continual learning (CL) learns a sequence of tasks incrementally.
Partially Relaxed Masks for Lightweight Knowledge Transfer without Forgetting in Continual Learning
The goal of this work is to endow such systems with the additional ability to transfer knowledge among tasks when the tasks are similar and have shared knowledge to achieve higher accuracy.
Continual Learning Using Pseudo-Replay via Latent Space Sampling
PLS is not only simple and efficient but also does not invade data privacy due to the fact that it works in the latent feature space.
