AIBullisharXiv – CS AI · 10h ago6/10
🧠
Attention-Spectrum Regularization for Replay-Free Continual Multimodal LLMs
Researchers propose Attention-Spectrum Regularization (ASR), a new continual learning framework for multimodal large language models that prevents catastrophic forgetting when adapting to new visual domains and tasks without replaying past data. ASR preserves cross-modal attention patterns by storing compact spectral statistics rather than actual training examples, demonstrating improved performance on vision-language benchmarks.