Papers with SLoRA-Post

1 papers
SLoRA: Balancing Plasticity and Forgetting in Large Language Models for Continual Learning (2026.acl-long)

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Challenge: Large language models (LLMs) have achieved remarkable success across diverse tasks through large-scale pretraining.
Approach: They propose a framework that filters noisy components from LoRA updates via subspace similarity with the base model.
Outcome: The proposed framework improves accuracy by 12%, reduces forgetting by 29%, and filters out over 30% of LoRA parameters identified as noisy.

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