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cs.LG2025
Active Learning for Continual Learning: Keeping the Past Alive in the Present
Jaehyun Park, Dongmin Park, Jae-Gil Lee
Continual learning (CL) enables deep neural networks to adapt to ever-changing data distributions. In practice, there may be scenarios where annotation is costly, leading to active…
cs.LG2023
Adaptive Shortcut Debiasing for Online Continual Learning
Doyoung Kim, Dongmin Park, Yooju Shin +3
We propose a novel framework DropTop that suppresses the shortcut bias in online continual learning (OCL) while being adaptive to the varying degree of the shortcut bias incurred b…
cs.LG2023
One Size Fits All for Semantic Shifts: Adaptive Prompt Tuning for Continual Learning
Doyoung Kim, Susik Yoon, Dongmin Park +4
In real-world continual learning (CL) scenarios, tasks often exhibit intricate and unpredictable semantic shifts, posing challenges for fixed prompt management strategies which are…