GRASP: Efficient Fine-tuning and Robust Inference for Transformers
Published:Dec 3, 2025 22:17
•1 min read
•ArXiv
Analysis
The GRASP method offers a promising approach to improve the efficiency and robustness of Transformer models, critical in a landscape increasingly reliant on these architectures. Further evaluation and comparison against existing parameter-efficient fine-tuning techniques are necessary to establish its broader applicability and advantages.
Key Takeaways
- •GRASP is a technique focusing on parameter-efficient fine-tuning for Transformers.
- •It aims to improve both efficiency and robustness in Transformer models.
- •The method is detailed in an ArXiv paper.
Reference
“GRASP leverages GRouped Activation Shared Parameterization for Parameter-Efficient Fine-Tuning and Robust Inference.”