Towards Continual Learning: Mitigating Forgetting With Subspace Tuning
Large language models (LLMs) acquire new skills through fine-tuning, but it can destroy capabilities they already have: catastrophic forgetting remains a central obstacle to continual learning in LLMs. Recent works connect forgetting to how far, and along which directions, fine-tuning moves the weights. On-policy metho...
Arnav Chavan, Kusha Sareen, Rishabh Tiwari et al.
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