Papers with CLoRA
Controlled Low-Rank Adaptation with Subspace Regularization for Continued Training on Large Language Models (2025.acl-long)
Copied to clipboard
| Challenge: | Existing approaches to mitigate catastrophic forgetting can be broadly categorized into data-based, architecture-based and learning-based methods. |
| Approach: | They propose a subspace regularization method on LoRA structure that imposes constraints on direction of updating matrix’s null space. |
| Outcome: | The proposed method reduces scale of output change while introducing minimal constraint on model capacity. |