Reliable Replay through Spatial Coherence in Online Continual Learning

arXiv:2609.33725 · stat.ML, cs.LG · Submitted 2026-09-27 · Read on arXiv

stat.ML, cs.LG

Submitted: 2026-09-27

Updated: 2026-09-27

Terminology

• Accuracy — 31× in this paper · explained in 1 episode
• Continual Learning — 30× in this paper · explained in 2 episodes
• Aggregation — 15× in this paper · explained in 1 episode
• Reinforcement Learning — 11× in this paper · explained in 4 episodes
• Instruction Tuning — 6× in this paper · explained in 2 episodes
• Optimal Transport — 6× in this paper · explained in 5 episodes
• Ablation — 5× in this paper · explained in 1 episode
• Distillation — 5× in this paper · explained in 2 episodes
• Catastrophic Forgetting — 4× in this paper · explained in 5 episodes
• Core — 4× in this paper · explained in 2 episodes
• Embeddings — 4× in this paper · explained in 2 episodes
• Conference on Computer Vision and Pattern Recognition — 3× in this paper
• GRPO — 3× in this paper · explained in 6 episodes
• Alignment — 2× in this paper · explained in 1 episode
• Generalization — 2× in this paper · explained in 13 episodes
• Regularization — 2× in this paper · explained in 3 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• CVF International Conference on Computer Vision — 1× in this paper
• Computer Vision and Pattern Recognition Workshops — 1× in this paper
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Deep Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Error Decomposition — 1× in this paper · explained in 3 episodes
• LoRA Adapters — 1× in this paper · explained in 3 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Optimal Transport (OT) — 1× in this paper · explained in 4 episodes

Sources

• An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks
• Qwen2.5-Coder Technical Report
• May the Forgetting Be with You: Alternate Replay for Learning with Noisy Labels
• Progressive Neural Networks
• DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

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