3 papers
cs.CV2026
Few-Shot Domain Incremental Learning via Continual Vision-Language Consolidation
Naeem Paeedeh, Mahardhika Pratama, Wolfgang Mayer +3
Existing domain-incremental learning (DIL) strategies call for massive amounts of data to adapt to new domains and suffer from the overfitting problem in the case of data scarcity.…
cs.CV2025
Cross-Domain Few-Shot Learning with Coalescent Projections and Latent Space Reservation
Naeem Paeedeh, Mahardhika Pratama, Imam Mustafa Kamal +3
Despite the progress in cross-domain few-shot learning, a model pre-trained with DINO combined with a prototypical classifier outperforms the latest SOTA methods. A crucial limitat…
cs.LG2025
Continual Knowledge Consolidation LORA for Domain Incremental Learning
Naeem Paeedeh, Mahardhika Pratama, Weiping Ding +4
Domain Incremental Learning (DIL) is a sub-branch of continual learning that aims to address the never-ending arrival of new domains without catastrophic forgetting. Despite the ad…