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Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment
The demands for fine-tuning PLMs, especially LLMs, have led to a surge in the development of PEFT methods, as depicted in Fig.
Optimal Online Algorithms for Peak-Demand Reduction Maximization with Energy Storage
In this paper, we propose an optimal online algorithm that achieves the best competitive ratio, following the idea of maintaining a constant ratio between the online and the optimal offline peak-reduction performance.
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