One Adapter, Many Tasks: Task-Conditioned Feature Transformations for Continual Learning

arXiv:2608.31096 · cs.CV, cs.LG · Submitted 2026-08-31 · Read on arXiv

cs.CV, cs.LG

Submitted: 2026-08-31

Updated: 2026-08-31

Terminology

• Consistency — 33× in this paper · explained in 3 episodes
• Continual Learning — 24× in this paper · explained in 2 episodes
• Accuracy — 16× in this paper · explained in 1 episode
• Ablation — 12× in this paper · explained in 1 episode
• Benchmark — 12× in this paper · explained in 2 episodes
• Transformer — 11× in this paper · explained in 2 episodes
• Robustness — 8× in this paper · explained in 5 episodes
• Latent Representation — 6× in this paper · explained in 2 episodes
• Catastrophic Forgetting — 5× in this paper · explained in 5 episodes
• Parameter Efficiency — 5× in this paper · explained in 3 episodes
• Ablation Studies — 4× in this paper · explained in 1 episode
• Alignment — 4× in this paper · explained in 1 episode
• Distillation — 4× in this paper · explained in 2 episodes
• Adaptation — 3× in this paper · explained in 1 episode
• Latent Space — 3× in this paper · explained in 7 episodes
• Model Merging — 3× in this paper · explained in 2 episodes
• Core — 2× in this paper · explained in 2 episodes
• Generalizability — 2× in this paper · explained in 6 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Regularization — 2× in this paper · explained in 3 episodes
• Activation Function — 1× in this paper · explained in 1 episode
• Adaptivity — 1× in this paper · explained in 1 episode
• Adversarial Examples — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Knowledge Distillation — 1× in this paper · explained in 11 episodes
• Pruning — 1× in this paper · explained in 4 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Vision Transformer (ViT) — 1× in this paper · explained in 2 episodes

Sources

• An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
• Gaussian Error Linear Units (GELUs)
• Scaling Continual Learning to 300+ Tasks with Bi-Level Routing Mixture-of-Experts
• Progressive Neural Networks
• Lifelong Learning with Dynamically Expandable Networks

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