Papers with continual learning benchmarks

1 papers
Continual Gradient Low-Rank Projection Fine-Tuning for LLMs (2025.acl-long)

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Challenge: Low-Rank Adaptation (LoRA) offers efficiency but constrains the model’s ability to learn new tasks and transfer knowledge due to its low-rank nature and reliance on explicit parameter constraints.
Approach: They propose a training strategy that synergistically combines full and low-rank parameters and jointly updating within a unified low-ranked gradient subspace.
Outcome: Extensive experiments on continual learning benchmarks show that GORP improves performance compared to state-of-the-art approaches.

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